From 255bbf1ac858e6bd444df5267dc9428b0913083a Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Fri, 19 Feb 2021 17:53:54 -0500
Subject: [PATCH 01/38] Deliverable 0 - Natural Disaster Prevention

Deliverable  0 contains updated proposal.
---
 Project Proposal CS506.pdf | Bin 0 -> 80979 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 Project Proposal CS506.pdf

diff --git a/Project Proposal CS506.pdf b/Project Proposal CS506.pdf
new file mode 100644
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From 5673de0acbd8fda374cc01c7d99b7b0c718659fb Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Sat, 27 Feb 2021 11:26:56 -0500
Subject: [PATCH 02/38] Nest in Folder

Deliverable 0
---
 .DS_Store                                        | Bin 0 -> 6148 bytes
 .../Project Proposal CS506.pdf                   | Bin
 README.md => NaturalDisasterProject/README.md    |   0
 3 files changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 .DS_Store
 rename Project Proposal CS506.pdf => NaturalDisasterProject/Project Proposal CS506.pdf (100%)
 rename README.md => NaturalDisasterProject/README.md (100%)

diff --git a/.DS_Store b/.DS_Store
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diff --git a/Project Proposal CS506.pdf b/NaturalDisasterProject/Project Proposal CS506.pdf
similarity index 100%
rename from Project Proposal CS506.pdf
rename to NaturalDisasterProject/Project Proposal CS506.pdf
diff --git a/README.md b/NaturalDisasterProject/README.md
similarity index 100%
rename from README.md
rename to NaturalDisasterProject/README.md

From abecd5d6ff7269790057f5042feec65cd75d0e32 Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Sat, 27 Feb 2021 12:56:02 -0500
Subject: [PATCH 03/38] weather data

---
 .DS_Store                                     | Bin 6148 -> 8196 bytes
 NaturalDisasterProject/.DS_Store              | Bin 0 -> 6148 bytes
 NaturalDisasterProject/Datasets/.DS_Store     | Bin 0 -> 6148 bytes
 .../Datasets/Tornado_Data_2010-2020.csv       | 112 ++++++++++++++++++
 4 files changed, 112 insertions(+)
 create mode 100644 NaturalDisasterProject/.DS_Store
 create mode 100644 NaturalDisasterProject/Datasets/.DS_Store
 create mode 100644 NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv

diff --git a/.DS_Store b/.DS_Store
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+EVENT_ID,CZ_NAME_STR,BEGIN_LOCATION,BEGIN_DATE,BEGIN_TIME,EVENT_TYPE,MAGNITUDE,TOR_F_SCALE,DEATHS_DIRECT,INJURIES_DIRECT,DAMAGE_PROPERTY_NUM,DAMAGE_CROPS_NUM,STATE_ABBR,CZ_TIMEZONE,MAGNITUDE_TYPE,EPISODE_ID,CZ_TYPE,CZ_FIPS,WFO,INJURIES_INDIRECT,DEATHS_INDIRECT,SOURCE,FLOOD_CAUSE,TOR_LENGTH,TOR_WIDTH,BEGIN_RANGE,BEGIN_AZIMUTH,END_RANGE,END_AZIMUTH,END_LOCATION,BEGIN_LAT,BEGIN_LON,END_LAT,END_LON,EVENT_NARRATIVE,EPISODE_NARRATIVE,ABSOLUTE_ROWNUMBER
+224551,YAZOO CO.,ENOLA,04/24/2010,1053,Tornado, ,EF4,4,53,140000000,4000000,MS,CST-6, ,38376,C,163,JAN,0,0,NWS Storm Survey, ,34.85,3080,5,WSW,3,NNW,FORDYKE,32.7003,-90.6783,32.9456,-90.1539,"The tornado moved out of extreme southeast Sharkey County and into west central Yazoo County and gained intensity as it tracked northeast. The tornado caused significant home damage northwest of Satartia, and again as it crossed Highway 3 near the Crupp Community. The tornado then moved through a rural area southwest of Yazoo City, causing major damage or destruction of a number of homes, as well as intense tree damage.  As the tornado approached the intersection of US Highway 49 and Highway 16, on the south side of Yazoo City, it reached its widest point and maximum intensity. Here the rating peaked at EF4 with maximum winds around 170 mph. The tornado had a maximum width of 1.75 miles. Several buildings, including a church and several businesses, were totally destroyed. The tornado continued moving through residential areas on the southeast side of Yazoo City, heavily damaging or destroying numerous homes.  The tornado continued northeast through rural northeastern Yazoo County before it tracked into Holmes County.||A total of four fatalities occurred in Yazoo County. All of the fatalities were individuals who were in mobile homes.","During the midday hours of April 24th, an intense supercell thunderstorm produced a violent, long track tornado, which ripped a path across the center of the NWS Jackson, MS forecast area. This tornado touched down just south of I-20, west of Tallulah, in Madison Parish. The tornado intensified quickly and became large as it tracked at a fast pace to the northeast. The tornado moved at roughly 55 mph and was on the ground for 149 miles. The actual time on the ground was 2 hours and 44 minutes. The tornado touched 9 counties/parishes along it's path with the most significant damage occurring in Madison Parish, Warren, Yazoo, Holmes, Attala and Choctaw Counties. A great deal of the damage was in the EF2 and EF3 range with a couple locations of EF4 damage in Yazoo and Holmes Counties. Maximum winds peaked around 170 mph. Overall, 10 fatalities occurred along with 146 injuries. Five fatalities occurred in Choctaw County, 4 in Yazoo County, and 1 in Holmes County.||As we try and put this tornado into perspective for the state of Mississippi, this long track tornado ranks as the 4th longest in Mississippi history at 149 miles.  It is the widest known tornado with a maximum width of 1.75 miles.  It also ranks as the 9th deadliest tornado with 10 fatalities, making it the most deadly since November 21st 1992.  Lastly, this was the first violent tornado (F4 or greater) in the month of April since April 18th, 1978.",1
+224552,HOLMES CO.,ZEIGLERVILLE,04/24/2010,1133,Tornado, ,EF4,1,40,60000000,4000000,MS,CST-6, ,38376,C,51,JAN,0,0,NWS Storm Survey, ,21.25,2600,2,ESE,3,E,DURANT,32.9456,-90.1539,33.0802,-89.8241,"The tornado continued northeast into rural southern Holmes County, causing intense tree damage and damaging or destroying a number of rural residences. The damage across this area was in the EF3 range. As the tornado moved by the Franklin Community, in rural Holmes county, it again reached EF4 intensity. It completely destroyed two brick homes and heavily damaged or destroyed a number of other homes. The tornado then crossed Interstate 55, causing significant tree damage and blowing a number of vehicles off the road. As the tornado approached the area just south of Durant and crossed US Highway 51, it narrowed and reached one of its weakest points. One fatality occurred in Holmes County.","During the midday hours of April 24th, an intense supercell thunderstorm produced a violent, long track tornado, which ripped a path across the center of the NWS Jackson, MS forecast area. This tornado touched down just south of I-20, west of Tallulah, in Madison Parish. The tornado intensified quickly and became large as it tracked at a fast pace to the northeast. The tornado moved at roughly 55 mph and was on the ground for 149 miles. The actual time on the ground was 2 hours and 44 minutes. The tornado touched 9 counties/parishes along it's path with the most significant damage occurring in Madison Parish, Warren, Yazoo, Holmes, Attala and Choctaw Counties. A great deal of the damage was in the EF2 and EF3 range with a couple locations of EF4 damage in Yazoo and Holmes Counties. Maximum winds peaked around 170 mph. Overall, 10 fatalities occurred along with 146 injuries. Five fatalities occurred in Choctaw County, 4 in Yazoo County, and 1 in Holmes County.||As we try and put this tornado into perspective for the state of Mississippi, this long track tornado ranks as the 4th longest in Mississippi history at 149 miles.  It is the widest known tornado with a maximum width of 1.75 miles.  It also ranks as the 9th deadliest tornado with 10 fatalities, making it the most deadly since November 21st 1992.  Lastly, this was the first violent tornado (F4 or greater) in the month of April since April 18th, 1978.",2
+220277,DEKALB CO.,RODENTOWN,04/24/2010,2301,Tornado, ,EF4,0,5,3000000,0,AL,CST-6, ,37834,C,49,HUN,0,0,NWS Storm Survey, ,16.62,880,3,E,1,ESE,DOG TOWN,34.2203,-85.9602,34.3439,-85.7105,"A long track tornado began it's 16.6 mile path about a half mile west of Hendrixville.  The tornado intensified and knocked several trees down and damaged a chicken farm about 2 miles east northeast of Hendrixville just west of Interstate 59.  The tornado continued sporadically into the town of Collinsville where it knocked three trees down and lifted several canopies at a campground.  The tornado intensified and became violent just northeast of Collinsville reaching EF-4 intensity with winds of 170 mph with a path width of 1/4 to 1/2 miles.  This path impacted areas from Mount Vernon to Dog Town in extreme southeastern DeKalb County.  The tornado destroyed several single wide manufactured homes along County Road 60, between County Roads 822 and 892.  Numerous large trees were snapped or uprooted.  The McNutt Memorial United Methodist Church and a two-story residence across the street were destroyed near the intersection of County Roads 80 and 55.  Oak trees nearby were debarked as well.  The tornado produced structural damage to residences along County Road 79 just west of Highway 176.  The tornado lifted about 1.4 miles east southeast of Dog Town.","Four damaging tornadoes tore tracks through north central and northeast Alabama during the evening and overnight hours of the 24th.   These tornadoes were part of a larger regional tornado outbreak across the lower Mississippi and Tennessee Valleys.   The tornadoes were associated with three separate long track supercell thunderstorms that thrived upon a very unstable and high shear environment.  One of the longer track tornadoes tore through several successive communities with up to EF-3 strength in Marshall and DeKalb Counties, including the towns of Albertville, Geraldine and Pine Ridge, lifting just before reaching Fort Payne.  A tornado from the same storm then touched down again in the Mentone area before crossing the Georgia state line.  Another supercell produced yet another tornado southwest of Collinsville, tracking just a few miles south of the earlier damaging tornado.  This tornado reached EF-4 strength when it completely leveled the McNutt United Methodist Church on County Road 55.    Fortunately, no fatalities occurred with these particular tornadoes, but damages were severe.||In Marshall County, total costs from the tornado had exceeded $14 million, which included 1032 homes experiencing at least some damage, and 93 homes destroyed.  In DeKalb County, damage losses were still being tallied.  Debris removal costs alone have exceeded $3 million.",3
+231948,CLEVELAND CO.,NORMAN,05/10/2010,1632,Tornado, ,EF4,1,32,0,0,OK,CST-6, ,39859,C,27,OUN,0,0,NWS Storm Survey, ,17,880,3,SSE,5,ENE,LAKE THUNDERBIRD DAM,35.1808,-97.4273,35.249,-97.142,"This tornado is labeled #J1, and moved into Pottawatomie County near state highway 9. The tornado a few hundred yards east of the National Weather Center in Norman, Oklahoma. The damage intensity increased gradually along the path with significant damage beginning as the tornado approached Lake Thunderbird. This tornado crossed Lake Thunderbird, severely damaging two campgrounds and the marina where about 300 boats were docked.  The most severe damage occurred from the Little Axe School to the Cleveland/Pottawatomie county line. Trees were stripped of some bark and branches. Large objects were thrown considerable distances, including some concrete pillars. The metal bleachers near the school were tossed or rolled several hundred yards. Some appliances were also lofted as a dryer was found about 50 feet up in a tree. Considerable structural damage also occurred, as some foundation homes were mostly destroyed.  In addition to the damage, one person lost their life as a result of the tornado.","A significant outbreak of severe thunderstorms and tornadoes affected a large part of northern, central, and southern Oklahoma. Tornadoes were most numerous across central and southern Oklahoma, with significant damage occurring over many areas. |Severe thunderstorms erupted by mid afternoon across northern and western Oklahoma. Given the potent combination of ingredients in place, storms began to produce tornadoes quickly after initiation. Storm motions of 50 to 60 mph were common.||During the mid afternoon hours, severe weather was confined to northern Oklahoma. It was there a long track supercell storm produced tornadoes near the Kansas border - including one rated EF3 - from near Wakita to north of Braman.||The capping inversion that had delayed thunderstorm development into central Oklahoma weakened, allowing for explosive supercell development along the dry line along and west of the Interstate 35 corridor. Rapid development and intensification was common with the late afternoon storms, with storms becoming tornadic within a very short time after initiation. This round of storms would directly impact a large part of the Oklahoma City metro area at rush hour, and posed a significant threat to the area. The first tornado in this area occurred in Canadian County.||During the next several hours, tornadoes were clustered around the metro area, and at times there were multiple significant damaging tornadoes occurring simultaneously. Several of the tornadoes had long tracks. Damage from the tornadoes was substantial, with numerous structures, vehicles, trees and power poles/lines significantly damaged or destroyed. One of the more intense tornadoes moved across Lake Thunderbird east of Norman destroying numerous boats.||More storms developed across southwest and south central Oklahoma, and also quickly became tornadic. ||By 9 pm, 35 tornadoes had been reported. While the loss of three lives was tragic, the casualties could have been much higher given the storm's fast motions, their intensity, the time of day and the areas impacted. ||While exact monetary damage figures were not available, it is estimated that losses were in excess of $595 million. At least 450 sustained injuries, most of them minor. Unfortunately three people lost their lives. ||Note: The large number of injuries and tornadoes made it difficult to associate injuries with specific tornadoes. Injury numbers were included when we had confidence in the numbers. ||Note: The complex nature of storm evolutions and interactions made the job of classifying tornadoes difficult. This represents our best scientific assessment based on ground and aerial surveys, data from multiple radars, photographic and video evidence and anecdotal information.",4
+231939,OKLAHOMA CO.,(TIK)TINKER AFB,05/10/2010,1635,Tornado, ,EF4,2,29,0,0,OK,CST-6, ,39859,C,109,OUN,0,0,NWS Storm Survey, ,11,2000,5,ESE,1,SSE,HARRAH,35.377,-97.305,35.47,-97.155,"This tornado is a continuation of the tornado that began in Cleveland County, labeled  #I1. This long-tracked and devastating tornado developed west of I-35, northwest of Max Westheimer airport. Widespread tree, power line/pole damage was reported from near I-35 to the east side of Stanley Draper Lake. Several homes also sustained damage, mainly with mostly roofs receiving significant damage, and some siding was ripped off. Several fences were also knocked down as the tornado moved northeast. From the east side of Lake Stanley Draper, near Hiwassee Road and SE 89th Street, to just south of Harrah, the damage path became more severe and focused. The tree damage became more severe, breaking at various heights of the tree or being uprooted. Walls of homes collapsed, and debris from the homes scattered in all directions. Several 2x4's punctured roofs and ceilings over numerous structures. A few mobile homes in this area were also completely destroyed. Where the tornado crossed I-40, a gas station and drive-in restaurant sustained up to EF3 damage. The most severe damage, one of the two EF4 tornadoes of the day, occurred in the Deerfield West Subdivision. A well-built residence here was completely destroyed, with most exterior and interior walls collapsing. The tornado finally lifted 2 miles south of Harrah. In addition to the incredible damage, two people lost their lives as a result of the tornado.","A significant outbreak of severe thunderstorms and tornadoes affected a large part of northern, central, and southern Oklahoma. Tornadoes were most numerous across central and southern Oklahoma, with significant damage occurring over many areas. |Severe thunderstorms erupted by mid afternoon across northern and western Oklahoma. Given the potent combination of ingredients in place, storms began to produce tornadoes quickly after initiation. Storm motions of 50 to 60 mph were common.||During the mid afternoon hours, severe weather was confined to northern Oklahoma. It was there a long track supercell storm produced tornadoes near the Kansas border - including one rated EF3 - from near Wakita to north of Braman.||The capping inversion that had delayed thunderstorm development into central Oklahoma weakened, allowing for explosive supercell development along the dry line along and west of the Interstate 35 corridor. Rapid development and intensification was common with the late afternoon storms, with storms becoming tornadic within a very short time after initiation. This round of storms would directly impact a large part of the Oklahoma City metro area at rush hour, and posed a significant threat to the area. The first tornado in this area occurred in Canadian County.||During the next several hours, tornadoes were clustered around the metro area, and at times there were multiple significant damaging tornadoes occurring simultaneously. Several of the tornadoes had long tracks. Damage from the tornadoes was substantial, with numerous structures, vehicles, trees and power poles/lines significantly damaged or destroyed. One of the more intense tornadoes moved across Lake Thunderbird east of Norman destroying numerous boats.||More storms developed across southwest and south central Oklahoma, and also quickly became tornadic. ||By 9 pm, 35 tornadoes had been reported. While the loss of three lives was tragic, the casualties could have been much higher given the storm's fast motions, their intensity, the time of day and the areas impacted. ||While exact monetary damage figures were not available, it is estimated that losses were in excess of $595 million. At least 450 sustained injuries, most of them minor. Unfortunately three people lost their lives. ||Note: The large number of injuries and tornadoes made it difficult to associate injuries with specific tornadoes. Injury numbers were included when we had confidence in the numbers. ||Note: The complex nature of storm evolutions and interactions made the job of classifying tornadoes difficult. This represents our best scientific assessment based on ground and aerial surveys, data from multiple radars, photographic and video evidence and anecdotal information.",5
+235969,EDMUNDS CO.,BOWDLE,05/22/2010,1729,Tornado, ,EF4,0,0,0,0,SD,CST-6, ,40558,C,45,ABR,0,0,NWS Storm Survey, ,3.86,1200,2,W,2,NE,BOWDLE,45.45,-99.71,45.4791,-99.642,"An EF2 tornado in eastern Walworth county crossed into western Edmunds county and intensified into a large EF4 tornado as it struck several farms in its path. At the first farm, several large cottonwood trees were uprooted along with damage to several trailers. Three grain bins were also destroyed with debris located several hundred yards to the northeast. The residence suffered some shingle and antenna damage. The tornado then tracked northeast to a second farm where several outbuildings were damaged or destroyed along with widespread tree damage. The main residence at this location suffered no damage. Several grain cars were also rolled about 100 yards into the trees behind the house.||The large tornado continued to track northeast to a third farm to the north of Bowdle. The main residence suffered major damage to walls with part of the roof structure removed. Widespread tree damage was sustained with many of the |trees completely debarked with only the stumps of the largest branches |remaining. Two large garages were completely destroyed with the |concrete slab wiped clean. The vehicles in one garage were |rolled or tossed from 25 to 100 yards away. It is estimated that one |vehicle flew through the air 75 to 100 yards resting in the tree |shelter belt to the north of the residence. Several other outbuildings were completely destroyed.||The tornado then toppled six to eight metal power transmission towers as it moved to the north of the farm. One tower was sheared off from the concrete footings and traveled an estimated 400 yards. Ground scouring was visible along the path of these towers.||The large tornado continued to track east crossing over State Highway 47 where a state radio tower was toppled. The tornado lifted shortly thereafter.  The highest wind speeds were estimated to be from 166 to 200 mph.","Several supercell thunderstorms developed along a very strong warm front and produced nine tornadoes from Akaska to Bowdle to Hecla. The largest of the tornadoes was an EF4 tornado which occurred near Bowdle. This tornado produced devastating damage in the Bowdle area. The other tornadoes ranged from EF0 to EF2 and caused extensive tree and building damage.  Nearly one-hundred power poles were downed along with several high line towers leaving nearly a thousand customers without power. Also, very strong straight line winds and large hail up to the size of golfballs affected parts of the area causing some damage.",6
+239602,WOOD CO.,MOLINE,06/05/2010,2220,Tornado, ,EF4,7,28,100000000,0,OH,EST-5, ,39815,C,173,CLE,0,0,NWS Storm Survey, ,6.5,400,2,SW,1,E,MILLBURY,41.5512,-83.538,41.5716,-83.4153,"A devastating tornado moved across portions of northern Wood County during the late evening hours of June 5th.  The tornado reached a peak intensity of EF4 and was responsible for the deaths of seven people.  Five of the victims died immediately with the other two passing away from their injuries at later dates.  The initial touchdown occurred east of Perrysburg along Oregon Road just to the north of the Ohio Turnpike.  The tornado then moved east northeast toward Toledo Metcalf Field as an EF0 to EF1.  The tornado intensified to an EF2 as it crossed East Broadway Street.  Over two dozen homes in a neighborhood bordered by East Broadway to the west and State Route 795 to the north and east were heavily damaged or destroyed.  The worst of the damage was along Shawnee and Neill Avenues in this neighborhood.  The tornado then crossed State Route 795 and followed the highway toward Metcalf Field.  The tornado intensified to EF3 at that time.  Several homes along Moline-Martin Road were destroyed between State Route 795 and Metcalf Field.  An occupant of one of the homes, an 87 year old man, was injured by the tornado and later died.  As the tornado approached Metcalf Field it crossed a railroad yard and overturned a couple dozen railroad cars.  The tornado then moved across the southern end of the airport grounds and destroyed the Lake Township Administrative and Police Department building located just northwest of the intersection of Cummings Road and State Route 795.  A 20 year old female was killed by the tornado just outside of the police department.  She had left her vehicle along with her boyfriend and child to seek refuge in the police station.  She was caught outside and was reportedly killed by flying debris.  At the police station, the tornado destroyed at least six police vehicles and one emergency response vehicle. The emergency response vehicle was found over 1000 feet away from its original position. One police vehicle was found wrapped around a large tree. After doing extensive damage to an agricultural business, the tornado struck the Lake Local School District complex along State Route 795 and Lemoyne Road.  Lake High School took a direct hit from the tornado and was damaged enough to be considered destroyed.  The nearby middle and elementary schools sustained considerable roof damage.  The high school gymnasium was scheduled to hold a commencement ceremony for the graduating senior class on June 6th.  Large sections of the gymnasium collapsed.  A field house, cafeteria and auditorium adjacent to the high school were destroyed.  At least eight school buses were overturned and destroyed by the tornado.  The tornado continued to move parallel to and just north of State Route 795 at EF3 intensity.  A 56 year old female was killed by flying debris while driving her car on State Route 795 near the school complex.  The woman's daughters were following in another car which was also destroyed.  The daughters both sustained minor injuries.  The tornado continued east northeast and crossed Interstate 280 just north of the State Route 795 interchange before moving across open fields for about a mile.  The tornado may have briefly weakened to EF2 intensity, but then strengthened back to EF3 intensity as it crossed Bradner Road to the west of Millbury.  The tornado destroyed several homes in a neighborhood bordered by Bradner Road to the west and Cherry Street to the south.  A 47 year old man was killed in house on Case Road in this neighborhood.  The man's daughter was the valedictorian of the graduating senior class at Lake High School which was destroyed by the tornado.  The tornado then intensified to EF4 as it approached Main Street on the north side of Millbury.  Over a dozen homes were destroyed or heavily damaged along Main Street.  A 36 year old woman and her four year old son were killed in one of the destroyed homes on Main Street.  The woman's 37 year old husband died on June 12th from injuries sustained from the tornado.  Several more homes were destroyed or heavily damaged on Hille Drive and Woodville Road before the tornado crossed North Fostoria Road and moved into Ottawa County as a weak EF3 or strong EF2 tornado.   This tornado was on the ground for around six and a half miles in Wood County and destroyed or heavily damaged over 60 homes.  Dozens of additional homes sustained minor damage with another couple hundred homes affected by the storm.  Dozens of vehicles were also destroyed.  Hundreds of trees were toppled or snapped by the tornado along the damage path which was up to 400 yards in width.  The tornado debarked some of the larger trees along the damage path.  At least one high tension utility pole was toppled by the tornado and widespread power outages occurred in Millbury and Walbridge.   Damage to the Lake Township infrastructure was estimated at five million dollars with tens of millions of losses to the Lake Local School District. The exact number of injuries caused by this tornado is unknown, but at least 17 people had to be hospitalized in nearby Toledo.  Debris from this tornado has been found dozens of miles away, including on some of the islands in western Lake Erie.","A stationary frontal system stretched across the lower Great Lakes on the morning of Saturday, June 5th.  This resulted in a very warm and humid airmass over northern Ohio.  Outflow boundaries from earlier storms interacted with the stationary front to initiate thunderstorm development during the afternoon hours across inland northern Ohio.  One of the stronger thunderstorms produced tornadoes in Richland and Holmes Counties.  There were also a few reports of straight line thunderstorm wind damage.  A rapidly deepening area of low pressure moved quickly east across southern lower Michigan during the evening hours.  This low eventually moved across Lake Erie during the early morning hours of the 6th.  Showers and thunderstorms developed across northern Indiana during the evening hours.  These storms intensified and moved east along the stationary front and into Northwest Ohio.  A devastating EF4 tornado developed over Wood County a little before midnight.  This tornado moved into Ottawa County before dissipating.  Seven people were killed and dozens of homes destroyed by the tornado.  A weaker tornado also moved across portions of Lucas County.  A third round of storms developed during the early morning hours of the 6th ahead of a cold front trailing the low.  These storms moved across northern Ohio and produced pockets of damage.  An EF1 tornado occurred in Ashtabula County around daybreak.  A total of five tornadoes occurred in northern Ohio on June 5th and 6th.  These tornadoes killed seven people, injured dozens and destroyed or damaged over a 100 homes.  A school and a public administration building were also leveled.  Damage estimates easily topped $100 million.",7
+245530,OTTER TAIL CO.,URBANK,06/17/2010,1445,Tornado, ,EF4,1,5,0,0,MN,CST-6, ,42071,C,111,FGF,0,0,NWS Storm Survey, ,38,2288,5,ESE,5,S,HILLVIEW,46.11,-95.425,46.6147,-95.25,"This tornado began in Douglas County, Minnesota. It moved northward into Otter Tail County and produced an additional 38 miles of continuous damage path. The tornado destroyed numerous homes and farmsteads along its path, completely sweeping 7 homes from their foundations. At times, this multi-vortex tornado complex consisted of multiple tornadic tubes pivoting around a common center. Peak winds were estimated at 175 mph.","Conditions were ripe by the afternoon of the 17th for a major severe weather outbreak. A surface low had moved into east central North Dakota with an occluded front extending to the southeast. Warm and humid air was in place ahead of the front, with a much drier airmass pushing in behind it. The 500mb low was located over northwest North Dakota with a nice southwest to northeast upper jet pushing into eastern North Dakota. Two lines of convection formed by late afternoon, one from Roseau County down toward Eastern Otter Tail County and the other over east central North Dakota. Nearly all the cells that formed took on a classic hook shape with rotation very evident on radar imagery. Multiple tornado warnings were issued before the event wound down by mid evening. The strongest tornadoes were determined to be EF4 tornadoes, two in west central Minnesota and one in northeast North Dakota.",8
+245496,TRAILL CO.,PORTLAND JCT,06/17/2010,1449,Tornado, ,EF4,0,1,0,0,ND,CST-6, ,42070,C,97,FGF,0,0,NWS Storm Survey, ,9,150,3,SE,2,SE,HATTON ARPT,47.54,-97.3,47.68,-97.32,"The tornado tracked northward for nearly 9 miles to about 12 miles north of Mayville by 405 PM CDT and crossed into Grand Forks County. It then continued for another 8 miles to around 10 miles west of Thompson by 418 PM CDT, for a total track length of nearly 17 miles. Trees in shelterbelts and farmsteads were snapped, uprooted, or sheared off. One well constructed house near Holmes was completely swept from its foundation and destroyed. Peak winds were estimated at 185 mph. A farm shop about five and one-half miles north of Mayville was hit by the tornado, destroying the shop. A man inside survived with cuts on his hand.","Conditions were ripe by the afternoon of the 17th for a major severe weather outbreak. A surface low had moved into east central North Dakota with an occluded front extending to the southeast. Warm and humid air was in place ahead of the front, with a much drier airmass pushing in behind it. The 500mb low was located over northwest North Dakota with a nice southwest to northeast upper jet pushing into eastern North Dakota. Two lines of convection formed by late afternoon, one from Roseau County down toward Eastern Otter Tail County and the other over east central North Dakota. Nearly all the cells that formed took on a classic hook shape with rotation very evident on radar imagery. Multiple tornado warnings were issued before the event wound down by mid evening. The strongest tornadoes were determined to be EF4 tornadoes, two in west central Minnesota and one in northeast North Dakota.",9
+245497,GRAND FORKS CO.,HOLMES,06/17/2010,1505,Tornado, ,EF4,0,0,0,0,ND,CST-6, ,42070,C,35,FGF,0,0,NWS Storm Survey, ,8,150,3,SSW,10,W,THOMPSON,47.68,-97.32,47.78,-97.3154,"This tornado began in Traill County about 3 miles north-northeast of Mayville at 349 PM CDT. The tornado crossed into Grand Forks County and tracked for an additional 8 miles to about 10 miles west of Thompson. The total track length was roughly 17 miles. One well constructed house near Holmes was completely swept from its foundation and destroyed along with several other farm buildings. Peak winds were estimated at 185 mph.","Conditions were ripe by the afternoon of the 17th for a major severe weather outbreak. A surface low had moved into east central North Dakota with an occluded front extending to the southeast. Warm and humid air was in place ahead of the front, with a much drier airmass pushing in behind it. The 500mb low was located over northwest North Dakota with a nice southwest to northeast upper jet pushing into eastern North Dakota. Two lines of convection formed by late afternoon, one from Roseau County down toward Eastern Otter Tail County and the other over east central North Dakota. Nearly all the cells that formed took on a classic hook shape with rotation very evident on radar imagery. Multiple tornado warnings were issued before the event wound down by mid evening. The strongest tornadoes were determined to be EF4 tornadoes, two in west central Minnesota and one in northeast North Dakota.",10
+245557,OTTER TAIL CO.,BLUFFTON,06/17/2010,1559,Tornado, ,EF4,0,0,0,0,MN,CST-6, ,42071,C,111,FGF,0,0,Trained Spotter, ,2,1936,5,SSE,5,SE,BLUFFTON,46.41,-95.18,46.43,-95.15,"This tornado touched down in Otter Tail County and tracked northeastward for about 2 miles before crossing into Wadena County just southwest of the Wadena city limits. The tornado developed rapidly into a multi-vortex wedge type tornado as it approached Wadena. The tornado continued in Wadena County another 8 miles and ended about 516 PM CDT. Otter Tail County received mainly extreme tree damage with peak winds estimated at 170 mph.","Conditions were ripe by the afternoon of the 17th for a major severe weather outbreak. A surface low had moved into east central North Dakota with an occluded front extending to the southeast. Warm and humid air was in place ahead of the front, with a much drier airmass pushing in behind it. The 500mb low was located over northwest North Dakota with a nice southwest to northeast upper jet pushing into eastern North Dakota. Two lines of convection formed by late afternoon, one from Roseau County down toward Eastern Otter Tail County and the other over east central North Dakota. Nearly all the cells that formed took on a classic hook shape with rotation very evident on radar imagery. Multiple tornado warnings were issued before the event wound down by mid evening. The strongest tornadoes were determined to be EF4 tornadoes, two in west central Minnesota and one in northeast North Dakota.",11
+245562,WADENA CO.,WADENA,06/17/2010,1602,Tornado, ,EF4,0,20,0,0,MN,CST-6, ,42071,C,159,FGF,0,0,Storm Chaser, ,8,1936,2,SW,7,NE,WADENA,46.43,-95.15,46.5216,-95.026,"This multi-vortex wedge tornado began in Otter Tail County about 3 miles southwest of the city of Wadena at 459 PM CDT. It tracked for about 2 miles in Otter Tail County, then it continued for another 8 miles in Wadena County. The tornado ravaged the western half of the community of Wadena. Numerous homes were flattened to the ground and at least one was completely swept from its foundation and destroyed. Public and industrial buildings were wrecked, the fairgrounds were damaged, and headstones in the cemetery were overturned. School buses and vehicles were propelled through the air for hundreds of yards. The tornado hit on the day of the Wadena all-school reunion, so many additional people were in the area. Roughly 100 people were displaced from their homes. Peak winds were estimated at 170 mph.","Conditions were ripe by the afternoon of the 17th for a major severe weather outbreak. A surface low had moved into east central North Dakota with an occluded front extending to the southeast. Warm and humid air was in place ahead of the front, with a much drier airmass pushing in behind it. The 500mb low was located over northwest North Dakota with a nice southwest to northeast upper jet pushing into eastern North Dakota. Two lines of convection formed by late afternoon, one from Roseau County down toward Eastern Otter Tail County and the other over east central North Dakota. Nearly all the cells that formed took on a classic hook shape with rotation very evident on radar imagery. Multiple tornado warnings were issued before the event wound down by mid evening. The strongest tornadoes were determined to be EF4 tornadoes, two in west central Minnesota and one in northeast North Dakota.",12
+231404,FREEBORN CO.,MANSFIELD,06/17/2010,1733,Tornado, ,EF4,1,14,0,0,MN,CST-6, ,38893,C,47,MPX,0,0,NWS Storm Survey, ,16.91,1760,1,WNW,2,W,HARTLAND,43.5755,-93.6404,43.8037,-93.5181,"The tornado initially moved northeast to approximately 3.5 miles west of Conger, where at about (43.6156, -93.6015), it began to move more to the east-northeast. West of Armstrong, at about (43.6597, -93.4938), it began tracking nearly due north to just west of Manchester, where at about (43.7357, -93.4801), it began to move to the north-northwest, before dissipating 1.5 miles west of Hartland.  Accounting for the changes in direction of this track, the actual path length covered by the tornado was 19.95 miles.||Near 180th Street and County Road 2, a home was likely in the outer circulation of the tornado, as it sustained some roof and siding damage.  A barn was also destroyed to its brick foundation and a car was also flipped over lengthwise. Some evidence of tree debarking was noted.  The tornado continued to the northeast and caused extensive crop damage approximately 500 yards in width. Near County Roads 17 and 63, the tornado intensified to produce EF-3 damage, impacting a farmstead and causing the complete destruction of three swine barns and the loss of 12 head of swine. Two empty grain bins were completely blown away at this location. The house at this location had some roof damage but appeared to be northwest of the main tornado path. Approximately 100 feet northeast of the house, a 150 foot tripod style wind turbine tower was twisted and toppled. This location also marked the beginning of crops being completely raked, with only stalks of corn left, and soybean fields being almost unrecognizable.||After passing through this farmstead the tornado took a more easterly path across County Road 63, and maintained EF-3 strength. After passing County Road 63, another farmstead was hit, and two empty harvester silos were toppled.  The tornado continued to the northeast across County Road 4, where continued raking of the fields was noted with significant deposition of debris along the tornado path. Numerous trees were toppled at County Road 89 where it turns to the north. The tornado continued to the north-northeast, grew to 1000 yards, and around 1750 LST impacted a farmstead along County Road 12 two miles north of Conger, where EF-4 damage was observed. The house at this location was completely destroyed, as was the barn and several other buildings. Extensive tree damage was noted with nearly all branches being removed from the trunks.  Debarking of trees was widespread at this location. A car was also tumbled a distance of 3200 feet, coming to rest in a field east of County Road 12.||The tornado continued to the northeast across County Road 69 and County Road 46, where it weakened slightly to EF-3 intensity. As it crossed County Road 46, a house was rotated off the foundation. The tornado was approximately 700 yards wide at this point. To the north-northeast, a swine barn was destroyed with sheet metal being carried off to Interstate 90. At this same time, a satellite tornado developed and caused damage in the town of Armstrong (see separate entry).||The main tornado continued to the north-northeast and was 500 yards in width. The tornado crossed County Road 74 and caused EF-2 damage to three farmsteads. One farmstead with a manufactured home was hit, resulting in one fatality and one severe injury.  The tornado crossed Interstate 90 just west of County Road 14 as it grew to one third of a mile in width and re-strengthened to EF-3 intensity. Several farmsteads saw significant damage between Sugar Lake and County Road 14, with a house and two barns completely destroyed. From this point the tornado continued to the north, growing to one mile in width. Around 1800 LST, a house and barn were destroyed approximately one mile west of Manchester on County Road 25, where extensive tree and structural damage was also noted at several properties in the area. Additionally, west of this tornadic damage, a separate area of tree and structural damage was caused by strong thunderstorm winds associated with a rear flank downdraft (see separate entry).||About one mile north, the tornado weakened slightly to EF-2 Intensity, where it damaged three full grain bins near County Road 29. The tornado was approximately 1300 yards at this point.  Further north, at County Road 95, the tornado continued to weaken, although a farmstead still received EF-1 damage to trees and structures.  Finally, the tornado continued north and began to narrow and weaken. It dissipated west of Hartland. One person was killed and 14 injured from this tornado.","Several strong storms developed in west-central Minnesota during the mid afternoon hours of June 17th.  ||These storms quickly become severe and produced softball size hail northwest of Alexandria and a tornado near Leaf Valley that became the EF-4 that moved through Wadena, Minnesota.  ||By the late afternoon, numerous thunderstorms developed across southern Minnesota along the leading edge of extreme instability. ||Numerous funnel cloud reports and a few brief tornado touchdowns were noted prior to 5 pm, but once the low level shear (0-1 km) increased significantly from 15 knots, to over 35 knots, strong tornadoes developed along the Iowa border.| |These storms along the Iowa border produced a series of long-lived tornadoes near Albert Lea, Minnesota. Very large hail also accompanied some tornadoes along with flash flooding.",13
+245834,OSCEOLA CO.,SIBLEY,06/25/2010,2110,Tornado, ,EF4,0,13,3000000,0,IA,CST-6, ,42126,C,143,FSD,0,0,NWS Storm Survey, ,8.47,800,5,W,2,N,CLOVERDALE,43.404,-95.8605,43.377,-95.696,"A tornado, moving into Osceola County from Lyon County, destroyed at least two houses, injuring two people in one of them. the tornado also destroyed several garages and severely damaged several other homes, destroyed at least 4 hog confinement buildings, several barns and silos, and numerous outbuildings. The tornado destroyed three vehicles that had been parked under an Iowa Highway 60 overpass, injuring 11 people in the vehicles, and removing the engine from one of the vehicles. The tornado damaged power lines, causing power outages, and caused damage to trees and crops. The tornado also destroyed a shelter belt and severely damaged heavy farm equipment, removing the wheels from some of the vehicles. Much of the damage occurred a short distance west to south of the town of Sibley.","Thunderstorms produced tornadoes, one that caused considerable damage and at least two injuries along a 14 mile path, along with damaging winds, in northwest Iowa during the evening of June 25th.",14
+239944,RICHLAND CO.,TYLER,08/07/2010,1725,Tornado, ,EF4,0,0,0,0,ND,CST-6, ,41239,C,77,FGF,0,0,Trained Spotter, ,2.5,600,3,SSW,3,SSE,TYLER,46.11,-96.63,46.11,-96.563,"This tornado touched down south of Tyler and tracked to the east for roughly 2.5 miles before crossing the Bois de Sioux River into Wilkin County, Minnesota. In Wilkin County, the tornado continued for another 2.5 miles and lifted about 650 pm CDT. The total track length was about 5 miles and peak winds were estimated at 175 mph.","By late in the day on the 7th, an east-west lying warm front had set up just north of the South Dakota border, extending eastward into west central Minnesota. South of the warm front, temperatures were in the mid to upper 80s with dew points in the lower 70s. Thunderstorms formed along and north of the warm front and several produced tornadoes.",15
+239948,WILKIN CO.,DORAN,08/07/2010,1737,Tornado, ,EF4,0,0,0,0,MN,CST-6, ,41241,C,167,FGF,0,0,NWS Storm Survey, ,2.5,600,5,SW,3,SW,DORAN,46.13,-96.563,46.1544,-96.5169,"This tornado began in Richland County, North Dakota, at 625 pm CDT, where it had a path length of 2.5 miles. It continued in Wilkin County, Minnesota, where it finally lifted about 2.5 miles southwest of Doran. The total path length was roughly five miles and peak winds were estimated at 175 mph.","By late in the day on the 7th, an east-west lying warm front had set up just north of the South Dakota border, extending eastward into west central Minnesota. South of the warm front, temperatures were in the mid to upper 80s with dew points in the lower 70s. Thunderstorms formed along and north of the warm front and several produced tornadoes.",16
+263493,WINN PAR.,ATLANTA,11/29/2010,1512,Tornado, ,EF4,0,0,750000,0,LA,CST-6, ,45412,C,127,SHV,0,0,NWS Storm Survey, ,13.96,400,3,W,0,SW,WINNFIELD JOYCE ARPT,31.7947,-92.808,31.9479,-92.6528,"Numerous trees were snapped near the intersection of Collier and Water Well Roads. The tornado then crossed Gum Springs Road, where it completely destroyed one well-built two story brick home and an adjacent brick garage. The home was approximately 4000 sq. ft in size, built in 1997, and its destruction was the basis of the EF-4 rating. Many of the nearby trees were completely snapped, with several near the home snapped off at the base. One single wide mobile home was also destroyed, with its remnants blown into a wooded area about 300 yards away. Another nearby home was moderately damaged, while two other homes suffered minor damage. The tornado then crossed into an open field, before entering a heavily wooded area, traveling northeast across Highways 84 and 167, where sporadic minor tree damage was observed just west and north of Winnfield.  Maximum winds are estimated around 170 mph, with a maximum width of 400 yards.","A potent...upper level short wave accompanied a prefrontal feature during the afternoon hours of November 29th across north central Louisiana.  These thunderstorms developed in a weakly unstable airmass across the region.  However...there was strong wind shear present...especially in the lowest 3 kilometers of the atmosphere.  A broken line of thunderstorms developed across east central Texas into northwest Louisiana along the prefrontal trough axis.  These thunderstorms quickly became supercells.  One of these storms produced a significant tornado in Winn Parish which traveled northeast and dropped again in southern Ouachita Parish.  Other storms downed powerlines in northwest Louisiana and minor flooding problems.",17
+283450,POCAHONTAS CO.,VARINA,04/09/2011,2054,Tornado, ,EF4,0,0,2500000,0,IA,CST-6, ,48468,C,151,DMX,0,0,NWS Storm Survey, ,3.2,587,5,NNE,6,SSW,WARE,42.7293,-94.8557,42.721,-94.7937,"An intense EF4 satellite tornado on the west flank of a large wedge tornado passing through western Pocahontas county.  This tornado approached from the northwest and completely destroyed a home leaving little debris at the site.  Grove of mature hardwood trees near the home was decimated and debarked and a large combine in the machine shed was tossed and rolled several hundred feet.  This tornado also absorbed the circulation of an EF2 satellite tornado.","A very dynamic weather pattern set up over the central U.S. during the day on the 9th. A deep trough formed aloft over the southeast U.S. with a strong southwest flow setting up over Iowa at all levels.  During the afternoon and evening, the low level jet increased steadily and reached 50 to 70 kts by midnight.  Considerable moisture advection took place with surface dewpoints rising into the low to middle 60s by evening.  A strong warm front lifted north into Iowa during the afternoon.  By the early evening hours it extended from west central Iowa into the east central and southeast counties of the state.  This front served as a focusing mechanism for thunderstorm development.  A strong elevated mixed layer was in place over the state during the afternoon of the 9th.  This kept convection from developing until the evening hours.  The freezing level was quite high for mid April, around 13,000 feet.  By early evening, at the initiation of storm development, the atmosphere had become very unstable.  Lifted indices were in the -9 to -12 C range with elevated CAPE feeding into the state in the 3000 to 5000 J/kg range.  The atmosphere was very sheared with effective shear of 60 to 65 kts.  As the moisture increased, precipitable water values increased to between 0.8 and 1.1 inches.  There was considerable downdraft CAPE available, with 1100 J/kg available.  CAPE in the -10 to -30 C layer of the atmosphere was between 500 and 1000 J/kg.  The effective helicity in the low layers of the atmosphere was around 800 J/Kg.  The LCL was around 1250 meters.  Thunderstorms developed along the warm frontal boundary during the very late afternoon and evening hours.  The storms formed more as discrete supercells rather than forming into a line.  The strongest supercells moved through Onawa County along the northern Crawford County line into Sac County.  Another strong supercell moved through Kossuth County.  In addition to the tornadoes that occurred, there were scattered reports of hail ranging from golf ball to baseball size with the storms.  There were a few reports of wind damage, however most of the damage that occurred was tornadic in nature.  On the north edge of the storms, what appeared to be a gravity wave lifted northeast along the back side of the line.  It produced a wind gust of near 60 MPH for a short period of time in Emmet County.  Several tornadoes touched down across western into northwest Iowa.  In Sac County, an EF3 tornado touched down with peak winds of 140 MPH. The path length was about 13 miles long and reached a mile in width at its widest.  The tornado began north of Odebolt and ended about 6 miles northwest of Early.  Damage was done to a farmstead and one home was totally destroyed.  Shortly before that, a tornado touched down in Crawford County from northwest of Ricketts to to about 4 miles northeast of Schleswig.  Damage was done to farmsteads along its path.   Another tornado touched down in Sac County northwest of Odeboldt and tracked to just northeast of Early.  This tornado had winds of 132 MPH, EF2 strength, with a half mile wide peak width.  It was on the ground for about 13 miles.  In what was the longest tornado track of the day, about 30 miles in length, a tornado touched down just west of Nemaha and tracked to about 3 1/2 miles southwest of Havelock through Sac, Buena Vista, and Pocahontas Counties.  The tornado was EF3 in strength and had a peak width of 2 to 3 miles.  Major damage occurred along the route with hog buildings destroyed, several farmsteads damaged or destroyed, and residential damage reported.  A turkey containment was destroyed, with the building completely removed.  Numerous hogs died in the tornado was well.  There were at least 4 satellite tornadoes associated with this long track tornado.  Two of the satellite tornadoes were a cyclonic/anticyclonic pair as they pushed north into Pocahontas County.  Another tornado, related to the same parent cell, tracked southeast and crossed paths with the long track tornado in Pocahontas County.  This tornado had peak winds of 170 MPH and was rated EF4.  Several farmsteads were destroyed by the tornado.  The path width was nearly 600 yards wide.  Yet another tornado touched down in Sac County northwest of Nemaha, and tracked to about 9 miles northeast of Nemaha.  It was on the ground for about 12 miles and had a peak width of 1/2 mile.  Damage was done to farms and a hog confinement building.  In Kossuth County, a tornado touched down briefly south of Algona and was on the ground for about a mile.  It was 200 yards wide and was EF1 strength with 90 MPH winds.  A smaller tornado touched down briefly southwest of Algona in Kossuth County.  Damage occurred to a hog confinement building and to power lines.  Following the NWS storm survey, there were two other tracks of EF-0 strength tornadoes discovered.  One occurred in farm fields of Sac County, north-northwest of Odebolt.  The path was about a mile long and 200 yards wide at its widest, with peak winds estimated at 65 MPH.  The tornado had an erratic track which actually looped back on itself.  Another tornado touched down in farm fields in Pocahontas County.  It was also an EF-0 tornado with a path length of about 2.5 miles and maximum width of 250 yards.  Winds with the tornado were around 100 MPH.  Governor Terry Branstad proclaimed a State Disaster Declaration for Buena Vista, Sac, Calhoun, and Pocahontas Counties.",18
+317910,ST. LOUIS CO.,VIGUS,04/22/2011,1859,Tornado, ,EF4,0,5,250000000,0,MO,CST-6, ,52847,C,189,LSX,0,0,NWS Storm Survey, ,15.39,880,1,WNW,1,ESE,RIVERVIEW,38.7364,-90.4863,38.746,-90.201,"During the evening of Friday April 22nd, an intense supercell thunderstorm produced a long-track tornado which tore a path of destruction from west to east across the St. Louis Metropolitan Area, from St. Louis County Missouri eastward through the far northern portions of the City of St. Louis, then across the Mississippi River into Madison County Illinois. The tornado reached a maximum intensity of EF4 on the Enhanced Fujita Scale as it tracked through the community of Bridgeton, just west of Lambert St. Louis International Airport, in St. Louis County. The total path length was 21.3 miles, with a width of up to half a mile.||The tornado initially touched down along the northern edge of Creve Coeur Lake at approximately 759 pm.  It tracked nearly due east at about 40 mph, and intensified as it entered Maryland Heights. There it produced up to EF3 damage to many homes and businesses with a damage swath of 200 to 400 yards wide.  Damage continued eastward in an unbroken track, crossing I-270 about 1 mile south of I-70. The tornado reached peak intensity of EF4 as it devastated the community of Bridgeton along Old St. Charles Road.  From there the tornado paralleled Interstate 70 through the community of St. Ann, and then took aim directly on Lambert-St. Louis International Airport.  Many of the large windows in the main terminal building were blown out or damaged by flying debris and a large section of roof was peeled from Concourse C.  Although the vast majority of people were evacuated to lower levels and to interior rooms before the tornado hit, five people were treated and released from area hospitals for injuries due to flying debris. The airport was closed due to the extensive damage.  Damage at the airport was estimated to be between $35 to 40 million.|    |The tornado exited Lambert-St. Louis International Airport crossing near the McDonnell Boulevard/Harmon Lane intersection.  It then moved into Berkeley where it crossed Interstate 170 between Airport Road and Scudder Avenue. Extensive damage was noted along Fourth Avenue, especially at the Garfield Avenue and Hancock Avenue intersections where a vacant house and several homes lost their entire roof structure. The greatest damage in this neighborhood was rated EF2.  The tornado continued to the northeast through neighborhoods south of Airport Road producing significant tree damage including many large trees falling on homes.  The tornado then crossed Airport Road near Abston Street.  The tornado crossed North Florissant Road where it caused extensive roof damage to the Newger Materials building and the First Baptist Church of Ferguson.  Across the road, a Little Caesars Restaurant lost its entire roof. Damage to these structures was rated EF1. The tornado then continued through neighborhoods along and just the north of Hereford Avenue/Chambers Road where it continued to cause extensive tree damage as well as additional partial roof damage to homes along the path toward West Florissant Road.  Also along this part of its path, it partially removed the roof at the Griffith Elementary School which was rated as EF1. This is also where the tornado widened to one quarter of a mile with damage noted to trees and some homes on both sides of Chambers Road.  Along the entire path from Berkeley to Dellwood, damage varied in intensity from EF1 to low end EF2 with a maximum estimated wind speed of 120 mph, and included numerous snapped power poles in addition to the extensive number of snapped and downed trees.||EF2 damage was uncovered at three different locations east of Dellwood. One area was located one quarter mile south of Chambers Road on Halls Ferry Road where four large utility poles were snapped. The second area of EF2 damage was located a quarter of a mile south of Chambers Road along Bellefontaine Road where significant tree damage occurred. The last area of damage was located in Bellefontaine Neighbors just south of Chambers Road on La Roux Court. Roofs were removed from three homes at this location, while other homes sustained varying degrees of damage.  The width of the damage area varies from 100 yards to four tenths of a mile with the widest area of damage east of Halls Ferry and south of Chambers Road. ||The tornadic damage continued as the tornado traveled eastward south of Chambers road, crossing into the far northern portions of the city of St. Louis. The majority of the damage in this area was rated EF1 due to fallen trees. Some of these trees fell on homes while a few others fell through homes causing damage not directly relating to the intensity of the wind within the tornado.  ||Overall, in St. Louis County, 233 structures (homes and businesses) sustained major damage, 776 structures sustained moderate damage, and 1,487 structures sustained minor damage.  Estimated dollar amount damage is $250 million.","A strong cold front moved through region. With plenty of moisture, instability and decent low level shear, severe storms developed along the Interstate 70 corridor in Missouri and Illinois.  Numerous reports of large hail and 5 tornadoes occurred with this event.  One of the tornadoes was a long track one that moved through the St. Louis metropolitan area with it being rated an EF4, with only a few minor injuries and no deaths. Also, quite a bit of rain fell during this event and caused flash flooding.  The flash flooding persisted for several days as additional rounds of heavy rain fell over the same region through the 26th of April.",19
+309257,NESHOBA CO.,LONGINO,04/27/2011,1330,Tornado, ,EF5,0,0,500000,0,MS,CST-6, ,51541,C,99,JAN,0,0,NWS Storm Survey, ,13.33,900,1,W,7,NE,CENTER,32.7992,-89.1088,32.902,-88.9145,"This tornado caused a path of extensive damage in northeast Neshoba, extreme northwest Kemper, extreme southeast Winston, and southwest Noxubee Counties. The most intense damage occurred in a several mile area from extreme northeast Neshoba County into extreme southeast Winston County. Much of the damage in the core of the tornado in this area was rated as high end EF-3 to EF-5. The three fatalities occurred in northwest Kemper County when a strapped down double-wide mobile home was thrown a distance of approximately 300 yards into a treeline, and then obliterated with the debris and framing scattered many hundreds of yards down the path. There was no indication of ground impacts between the original site of the mobile home and where it ended up to indicate that the mobile home bounced extensively as it traveled. Two traditional frame brick homes in southeast Winston County were completely leveled with only a few small parts of interior walls standing. New vehicles were thrown or rolled hundreds of yards before being wrapped into trees and left almost beyond recognition. In parts of northeast Neshoba and northwest Kemper Counties, there was very high end tree damage with extensive denuding and debarking of trees, along with areas where the ground was scoured out to a depth of two feet in places, and asphalt was scoured off pavement. Maximum sustained winds were estimated at 205 mph. Total path length was 29 miles.||This was the first EF-5 tornado in Mississippi since the Candlestick Park tornado on May 3, 1966. Additionally, this was the first time since statistics have been kept that two EF-5 tornadoes have been recorded on the same day in Mississippi, with the tornado in Smithville also rated as an EF-5.","A historic outbreak of tornadoes across the Ark-La-Miss began late on Tuesday, April 26th continuing into the early morning hours of Wednesday, April 27th. The event ramped up again during the early afternoon of April 27th continuing into the early evening.  The activity on April 26th began as supercell thunderstorms producing large hail and tornadoes across northeast Texas and portions of Arkansas before evolving into a squall line as it moved east. This line of storms had multiple stages of evolution and moved across several states before dissipating. This line was very efficient in producing wind damage as it pushed east. More impressively, this line was responsible for 23 of the 32 tornadoes that occurred across the Ark-La-Miss during this event. Of those 23, 12 were rated as strong (EF2, EF3) tornadoes and had fairly long path lengths.||The atmosphere reloaded quickly Wednesday morning and became increasingly favorable for more severe storms by early afternoon. The driving force for the activity Wednesday afternoon was a potent shortwave and deep surface low that intensified during the day. The winds in the mid levels of the atmosphere increased to 80-100 mph helping to deepen the surface low further, which in turn caused the low level winds to become stronger. The wind shear caused by the turning of the winds from south near the surface to westerly aloft was at rare levels for late April over the Deep South. In addition, an abundance of low level moisture returned to the area in wake of the morning complex. Sunny skies during the morning interacted with the high levels of low level moisture eventually leading to a very unstable air mass by early afternoon. The result was an extremely rare mix of instability and wind shear. These ingredients, along with lift from a potent upper disturbance, ultimately led to the historic tornado outbreak of April 27, 2011.||By early afternoon, several discrete supercell thunderstorms were developing across central and eastern Mississippi. It did not take long for these storms to take on ���classic��� supercell structures and begin producing tornadoes. The first tornado of the afternoon started in Neshoba County on the north side of Philadelphia. This tornado ended up producing EF-5 damage and tracked for 29 miles across Neshoba, Kemper, Winston and Noxubee Counties. Through the rest of the afteroon multiple tornadoes developed, stemming from multiple supercell storms. Nearly all of the storms produced tornadoes, with many of them long track and significant. The other violent tornado to impact the Jackson, MS forecast area occurred across Smith, Jasper, and Clarke Counties. This tornado continued into Alabama and had a total path length of 124 miles across both states.||Loss of life during this historic event was staggering. Unfortunately, 321 people lost their lives making this the second deadliest tornado outbreak in U.S. history. The March 18, 1925 Tri-State tornado outbreak is first with 747 fatalities. This marks the first EF-5 tornado in Mississippi since the Candlestick Park tornado on May 3, 1966, and this marks the first time since statistics have been kept that two EF-5 tornadoes have been recorded on the same day in Mississippi, with the tornado in Smithville also rated as EF-5. Incredibly, 4 tornadoes had path lengths over 100 miles across the southern states during this event, and all 4 of these were rated either EF-4 or EF-5.",20
+301943,CULLMAN CO.,CRANE HILL,04/27/2011,1340,Tornado, ,EF4,1,0,0,0,AL,CST-6, ,50516,C,43,HUN,0,0,NWS Storm Survey, ,25.75,880,3,SE,3,E,COUNTY LINE,34.0757,-87.0097,34.3054,-86.6549,"A violent long track tornado developed on the north side of Lewis Smith Lake along County Road 310 where some light damage was found.  The tornado tracked northeast snapping numerous large trees and causing significant structural damage to residences along County Roads 222 and 436 near Grandview.  The tornado tracked northeast into the city of Cullman.  Some of the worst damage occurred just northeast of U.S. Highways 31 and 278.  Several small retail buildings were completely destroyed. along with the near total destruction of a large church.  The tornado tracked across State Highway 157, then caused additional damage north of State Highway 69 between Simcoe and Pleasant View.  Just north of Fairview along County Roads 1559 and 1564, 2 homes were destroyed with significant portions of the homes not found.  Further northeast along County Road 1589, the tornado caused major structural damage to several old (early 1900s) homes.  Numerous hardwood trees were debarked.  A 1/4 to 1/2 mile wide corridor of significant damage persisted between Fairview and the Morgan County line.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",21
+309261,KEMPER CO.,PRINCE CHAPEL,04/27/2011,1343,Tornado, ,EF5,3,6,100000,0,MS,CST-6, ,51541,C,69,JAN,0,0,NWS Storm Survey, ,2.89,900,1,W,2,NE,PRINCE CHAPEL,32.9017,-88.9145,32.926,-88.8739,"This tornado caused a path of extensive damage in northeast Neshoba, extreme northwest Kemper, extreme southeast Winston, and southwest Noxubee Counties. The most intense damage occurred in a several mile area from extreme northeast Neshoba County into extreme southeast Winston County. Much of the damage in the core of the tornado in this area was rated as high end EF-3 to EF-5. The three fatalities occurred in northwest Kemper County when a strapped down double-wide mobile home was thrown a distance of approximately 300 yards into a treeline, and then obliterated with the debris and framing scattered many hundreds of yards down the path. There was no indication of ground impacts between the original site of the mobile home and where it ended up to indicate that the mobile home bounced extensively as it traveled. Two traditional frame brick homes in southeast Winston County were completely leveled with only a few small parts of interior walls standing. New vehicles were thrown or rolled hundreds of yards before being wrapped into trees and left almost beyond recognition. In parts of northeast Neshoba and northwest Kemper Counties, there was very high end tree damage with extensive denuding and debarking of trees, along with areas where the ground was scoured out to a depth of two feet in places, and asphalt was scoured off pavement. Maximum sustained winds were estimated at 205 mph. Total path length was 29 miles.||This was the first EF-5 tornado in Mississippi since the Candlestick Park tornado on May 3, 1966. Additionally, this was the first time since statistics have been kept that two EF-5 tornadoes have been recorded on the same day in Mississippi, with the tornado in Smithville also rated as an EF-5.","A historic outbreak of tornadoes across the Ark-La-Miss began late on Tuesday, April 26th continuing into the early morning hours of Wednesday, April 27th. The event ramped up again during the early afternoon of April 27th continuing into the early evening.  The activity on April 26th began as supercell thunderstorms producing large hail and tornadoes across northeast Texas and portions of Arkansas before evolving into a squall line as it moved east. This line of storms had multiple stages of evolution and moved across several states before dissipating. This line was very efficient in producing wind damage as it pushed east. More impressively, this line was responsible for 23 of the 32 tornadoes that occurred across the Ark-La-Miss during this event. Of those 23, 12 were rated as strong (EF2, EF3) tornadoes and had fairly long path lengths.||The atmosphere reloaded quickly Wednesday morning and became increasingly favorable for more severe storms by early afternoon. The driving force for the activity Wednesday afternoon was a potent shortwave and deep surface low that intensified during the day. The winds in the mid levels of the atmosphere increased to 80-100 mph helping to deepen the surface low further, which in turn caused the low level winds to become stronger. The wind shear caused by the turning of the winds from south near the surface to westerly aloft was at rare levels for late April over the Deep South. In addition, an abundance of low level moisture returned to the area in wake of the morning complex. Sunny skies during the morning interacted with the high levels of low level moisture eventually leading to a very unstable air mass by early afternoon. The result was an extremely rare mix of instability and wind shear. These ingredients, along with lift from a potent upper disturbance, ultimately led to the historic tornado outbreak of April 27, 2011.||By early afternoon, several discrete supercell thunderstorms were developing across central and eastern Mississippi. It did not take long for these storms to take on ���classic��� supercell structures and begin producing tornadoes. The first tornado of the afternoon started in Neshoba County on the north side of Philadelphia. This tornado ended up producing EF-5 damage and tracked for 29 miles across Neshoba, Kemper, Winston and Noxubee Counties. Through the rest of the afteroon multiple tornadoes developed, stemming from multiple supercell storms. Nearly all of the storms produced tornadoes, with many of them long track and significant. The other violent tornado to impact the Jackson, MS forecast area occurred across Smith, Jasper, and Clarke Counties. This tornado continued into Alabama and had a total path length of 124 miles across both states.||Loss of life during this historic event was staggering. Unfortunately, 321 people lost their lives making this the second deadliest tornado outbreak in U.S. history. The March 18, 1925 Tri-State tornado outbreak is first with 747 fatalities. This marks the first EF-5 tornado in Mississippi since the Candlestick Park tornado on May 3, 1966, and this marks the first time since statistics have been kept that two EF-5 tornadoes have been recorded on the same day in Mississippi, with the tornado in Smithville also rated as EF-5. Incredibly, 4 tornadoes had path lengths over 100 miles across the southern states during this event, and all 4 of these were rated either EF-4 or EF-5.",22
+309265,WINSTON CO.,FEARNS SPGS,04/27/2011,1346,Tornado, ,EF5,0,0,100000,0,MS,CST-6, ,51541,C,159,JAN,0,0,NWS Storm Survey, ,4.24,900,7,S,4,SSE,FEARNS SPGS,32.9262,-88.8719,32.9635,-88.8139,"This tornado caused a path of extensive damage in northeast Neshoba, extreme northwest Kemper, extreme southeast Winston, and southwest Noxubee Counties. The most intense damage occurred in a several mile area from extreme northeast Neshoba County into extreme southeast Winston County. Much of the damage in the core of the tornado in this area was rated as high end EF-3 to EF-5. The three fatalities occurred in northwest Kemper County when a strapped down double-wide mobile home was thrown a distance of approximately 300 yards into a treeline, and then obliterated with the debris and framing scattered many hundreds of yards down the path. There was no indication of ground impacts between the original site of the mobile home and where it ended up to indicate that the mobile home bounced extensively as it traveled. Two traditional frame brick homes in southeast Winston County were completely leveled with only a few small parts of interior walls standing. New vehicles were thrown or rolled hundreds of yards before being wrapped into trees and left almost beyond recognition. In parts of northeast Neshoba and northwest Kemper Counties, there was very high end tree damage with extensive denuding and debarking of trees, along with areas where the ground was scoured out to a depth of two feet in places, and asphalt was scoured off pavement. Maximum sustained winds were estimated at 205 mph. Total path length was 29 miles.||This was the first EF-5 tornado in Mississippi since the Candlestick Park tornado on May 3, 1966. Additionally, this was the first time since statistics have been kept that two EF-5 tornadoes have been recorded on the same day in Mississippi, with the tornado in Smithville also rated as an EF-5.","A historic outbreak of tornadoes across the Ark-La-Miss began late on Tuesday, April 26th continuing into the early morning hours of Wednesday, April 27th. The event ramped up again during the early afternoon of April 27th continuing into the early evening.  The activity on April 26th began as supercell thunderstorms producing large hail and tornadoes across northeast Texas and portions of Arkansas before evolving into a squall line as it moved east. This line of storms had multiple stages of evolution and moved across several states before dissipating. This line was very efficient in producing wind damage as it pushed east. More impressively, this line was responsible for 23 of the 32 tornadoes that occurred across the Ark-La-Miss during this event. Of those 23, 12 were rated as strong (EF2, EF3) tornadoes and had fairly long path lengths.||The atmosphere reloaded quickly Wednesday morning and became increasingly favorable for more severe storms by early afternoon. The driving force for the activity Wednesday afternoon was a potent shortwave and deep surface low that intensified during the day. The winds in the mid levels of the atmosphere increased to 80-100 mph helping to deepen the surface low further, which in turn caused the low level winds to become stronger. The wind shear caused by the turning of the winds from south near the surface to westerly aloft was at rare levels for late April over the Deep South. In addition, an abundance of low level moisture returned to the area in wake of the morning complex. Sunny skies during the morning interacted with the high levels of low level moisture eventually leading to a very unstable air mass by early afternoon. The result was an extremely rare mix of instability and wind shear. These ingredients, along with lift from a potent upper disturbance, ultimately led to the historic tornado outbreak of April 27, 2011.||By early afternoon, several discrete supercell thunderstorms were developing across central and eastern Mississippi. It did not take long for these storms to take on ���classic��� supercell structures and begin producing tornadoes. The first tornado of the afternoon started in Neshoba County on the north side of Philadelphia. This tornado ended up producing EF-5 damage and tracked for 29 miles across Neshoba, Kemper, Winston and Noxubee Counties. Through the rest of the afteroon multiple tornadoes developed, stemming from multiple supercell storms. Nearly all of the storms produced tornadoes, with many of them long track and significant. The other violent tornado to impact the Jackson, MS forecast area occurred across Smith, Jasper, and Clarke Counties. This tornado continued into Alabama and had a total path length of 124 miles across both states.||Loss of life during this historic event was staggering. Unfortunately, 321 people lost their lives making this the second deadliest tornado outbreak in U.S. history. The March 18, 1925 Tri-State tornado outbreak is first with 747 fatalities. This marks the first EF-5 tornado in Mississippi since the Candlestick Park tornado on May 3, 1966, and this marks the first time since statistics have been kept that two EF-5 tornadoes have been recorded on the same day in Mississippi, with the tornado in Smithville also rated as EF-5. Incredibly, 4 tornadoes had path lengths over 100 miles across the southern states during this event, and all 4 of these were rated either EF-4 or EF-5.",23
+309488,MARION CO.,BARNESVILLE,04/27/2011,1405,Tornado, ,EF5,18,100,160000000,0,AL,CST-6, ,50455,C,93,BMX,0,0,NWS Storm Survey, ,25.14,1320,4,WSW,3,N,TESSNER,34.1043,-88.1479,34.3109,-87.7858,"A tornado initially touched down west of Hamilton in southwest Marion County and moved northeast where it caused devastating damage to the city of Hackleburg. The tornado continued into Franklin County and tracked through Lawrence, Morgan, Limestone, and Madison Counties in Alabama. The tornado continued into Lincoln County Tennessee and finally dissipated in Franklin County Tennessee (See Storm Data Huntsville). The average path width of the tornado while in Marion County was 0.5 mile (880 yds).  The tornado touched down west of AL Hwy 19 near Sipsey Creek and moved northeast and crossed Corridor X/Future Interstate 22. Here it caused significant tree damage. The tornado strengthened north of Hamilton and caused roof damage to at least one home. The storm strengthened further as it approached US Hwy 43, southwest of Hackleburg, to a violent EF4 rating with winds estimated at 170 mph. The tornado tracked parallel to US Hwy 43 toward Hackleburg and strengthened more to an EF5 with winds up to 210 mph, as its path widened to 0.75 mile (1320 yds). Several subdivisions and businesses, Hackleburg High School, Middle School, and Elementary School, and the Wrangler Plant were destroyed. Vehicles were tossed up to 200 yards. One well built home with 4 brick sides was completely leveled and the debris from the home was tossed over 40 yards to the north. The tornado moved northeast of Hackleburg and  continued to parallel US Hwy 43. It crossed into Franklin County just east of the highway. Along the damage path in Marion County, thousands of trees were downed, several hundred structures were damaged, and at least 100 of these structures were completely destroyed as many homes were leveled. Eighteen fatalities are attributed to this tornado in Marion County, as well as numerous injuries.","A powerful storm system crossed the Southeast United States on Wednesday, April 27, 2011, resulting in a large and deadly tornado outbreak.  This epic event broke the record for number of tornadoes in a day for the state of Alabama, becoming the most significant tornado outbreak in the state���s history. ||Central Alabama had two rounds of severe weather that day. During the early morning hours, a Quasi-Linear Convective System quickly moved across the northern half of the National Weather Service, Birmingham county warning area. Straight line winds of 90 mph (78kts) or greater and 11 tornadoes lead to widespread damage and power outages. During the afternoon, long-lived supercell thunderstorms produced long-track, strong and violent tornadoes. Destruction and loss of life across many towns and communities was devastating. ||The hardest hit areas included Shottsville and Hackleburg, both in Marion County, where winds of 160 mph and 210 mph respectively, caused unimagineable damage. Cordova, in Walker County, was hit twice; by a tornado along the Quasi-Linear Convective System during the early morning hours and again in the afternoon by a long-track EF4 tornado. A long track tornado moved across the city of Tuscaloosa and the western suburbs of Birmingham, resulting in the complete destruction of whole neighborhoods and numerous injuries and fatalities in those heavily populated areas. The same parent supercell produced another violent tornado in east Central Alabama as it tracked across St. Clair and Calhoun Counties, resulting in additional fatalities and incredible damage to a number of neighborhoods. Another violent EF4 tornado tracked across portions of Elmore and Tallapoosa Counties, including Lake Martin, destroying numerous homes and a large section of a mobile home park. ||Most of the violent tornadoes from this day were captured on video by a number of people, including storm spotters and chasers, as well as numerous television news crews and remotely controlled web-enabled video cameras.  This allowed unprecedented coverage and viewing of this historic event in real time from people worldwide.",24
+301946,MORGAN CO.,GUM POND,04/27/2011,1412,Tornado, ,EF4,0,0,0,0,AL,CST-6, ,50516,C,103,HUN,0,0,NWS Storm Survey, ,5.33,880,2,SSE,2,NE,RYAN XRDS,34.3054,-86.6549,34.3528,-86.5813,"A violent tornado tracked from Cullman County into extreme southeast Morgan County near the town of Hulaco.  Peak wind speeds of up to 175 mph caused significant damage between Hyatt Bottom Road and Blocker Road, just east of State Highway 67.  Several cinder block and old construction homes were destroyed, and numerous trees were snapped and sheared toward the base.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",25
+302067,MARSHALL CO.,RUTH,04/27/2011,1416,Tornado, ,EF4,5,48,0,0,AL,CST-6, ,50516,C,95,HUN,0,0,NWS Storm Survey, ,15.8,880,1,SSW,1,NE,HEBRON,34.3528,-86.5813,34.4935,-86.3628,"A violent tornado with peak wind speeds of 190 mph crossed into northwest Marshall County (from Morgan County).  The most severe damage occurred on either side of U.S. Highway 231 north of Arab -- particularly in the Ruth community and along Hog Jaw Road -- about 3 miles north of Arab.  Along Hog Jaw Road, a large storage shed with farm equipment was destroyed with some of the large machinery tossed 10 to 20 yards around the shed.  In the Ruth community, Mount Oak and Frontier Roads were hardest hit where a cinder block/cement home was nearly wiped clean.  Debris from a home on Frontier Road was thrown 50 to 100 yards away.  A family of 9 was in this house and 5 were killed. A trailer was missing and a metal-bolted garage was wiped clean of its foundation.  Along Frontier Road, a large brick home was nearly wiped clean off its foundation with several large trees ripped out of the ground and missing.  Further northeast along the path, along Walnut Ridge, a one-story home was severely damaged with the roof missing and a trailer that was tossed into a tree.  Several concrete power poles were bent over as the tornado crossed U.S. Highway 231, some bent at the base.  One the east side of Highway 231, a gas station building was completely demolished and two gas pumps were ripped from the ground and missing. The canopy over the pumps remained mostly intact.||The tornado continued toward Union Grove.  The degree of damage weakened somewhat but several homes had significant damage where the top stories and roofs were destroyed and the external walls had collapsed.  Along County Road 240, a double-wide manufactured home was destroyed and a large garage collapsed but the well-built roof remained intact.||The tornado significantly weakened as it crossed the Tennessee River.  On the other side of the river, the tornado snapped and uprooted numerous trees as it crossed Walker Road and just across U.S. Highway 431 before lifting just northeast of Highway 431.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",26
+301811,FRANKLIN CO.,NIX,04/27/2011,1428,Tornado, ,EF5,27,0,50000000,0,AL,CST-6, ,50516,C,59,HUN,0,0,NWS Storm Survey, ,16.95,1760,3,S,3,ENE,OAK GROVE,34.3109,-87.7858,34.4368,-87.5307,"A violent long track tornado continued it's path from Marion County into southern Franklin County north of Hackleburg.  Significant devastation occurred throughout the city of Phil Campbell. Prolific damage was noted from the intersection of CR 51 and Alabama Highway 237, to the intersection of CR 81 and CR 75. Within a two mile corridor of either side of the railroad tracks the damage was significant. Within this corridor, several well constructed houses were destroyed.  Along Bonner Street, multiple block homes were leveled to the ground with the block foundations destroyed.  A twenty-five foot section of pavement was sucked up and scattered. Chunks of the pavement were found in a home over 1/3 of a mile down the road. The damage in this area was consistent with EF-5 damage. ||In addition, at least three churches along the path sustained significant damage.   One church in Phil Campbell was completely destroyed with only the slab remaining.||Multiple mobile homes throughout the path were completely destroyed, and their mangled frames were tossed 25 to 50 yards.  Cars were tossed and destroyed throughout the path of the tornado, with one car wrapped around a debarked tree in Phil Campbell.   All along the path length, thousands of hardwood and softwood trees were snapped.  Hundreds of trees were also debarked and twisted, and had only stubs of the largest branches remaining.  EF-5 damage continued similarly northeast from Phil Campbell, roughly along County Roads 81 and 82 toward the community of Oak Grove.||In Oak Grove, the tornado may have reached a relative maximum in intensity well into the EF-5 category as the damage was slightly more intense and the path width was at a maximum of greater than one mile.  A large swath of complete devastation was noted in Oak Grove along County Roads 38 and Smith Lane.  A large well-constructed home with extensive anchoring was razed with debris carried well away from the site.  A Corvette sports car was mangled and thrown 641 feet (measured). A block home next door was also disintegrated.  Along Smith Lane a block home was wiped out and the only remains of a nearby chicken house was a small piece of a metal truss.  In this same area, the tree damage was significant and a large percentage of trees were stripped bare.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",27
+303562,MONROE CO.,SMITHVILLE,04/27/2011,1442,Tornado, ,EF5,16,37,2500000,0,MS,CST-6, ,50307,C,95,MEG,0,0,NWS Storm Survey, ,6.05,1320,3,WSW,3,ENE,SMITHVILLE,34.0455,-88.445,34.0891,-88.36,"After lifting for 4 miles, a violent EF-5 tornado touched back down southwest of Smithville and moved northeast. The town of Smithville was almost completely destroyed by the tornado. Homes and businesses were completely wiped off of their foundations. The town hall, post office, police station, and four churches were destroyed. All appliances and plumbing fixtures in the direct path of the tornado were shredded or missing. Granite tombstones were knocked down in the opposite direction of the tornado passage. A ford explorer that was parked a half mile away from the town's water tower was picked up by the tornado and thrown into the top of the water tower. The vehicle was then thrown an additional few hundred feet. In total, 117 structures were destroyed with an additional 50 structures sustaining major damage. Numerous other structures sustained minor damage. Trees were debarked, twisted, and snapped. Power lines were knocked down and the town's water system was destroyed. A lot of the homes that were destroyed were well built, bolted to their foundations and were less than 10 years old. A total of 16 fatalities occurred from the tornado. Thirty-seven injuries occurred as well. The tornado continued northeast after destroying Smithville and crossed into Itawamba County, Mississippi.","A stationary front remained draped across Southern Missouri into Western Kentucky from April 24th, 2011 into April 25th, 2011. A very warm and unstable atmosphere was in place across the Mid-South ahead of the front. A low pressure system developed along the front and interacted with the unstable environment which helped produce several rounds of severe storms into the evening of April 26th, 2011. As a result of the severe storms, the front sank south during the early morning hours of April 27th, 2011 as a secondary low pressure system developed along the front. As a result, another round of severe storms fired during the afternoon hours ahead of the low pressure center. Additional severe storms fired along the trailing cold front. Tornadoes, large hail, damaging winds, flash flooding occurred as a result of the severe storms.",28
+301846,LAWRENCE CO.,MT HOPE,04/27/2011,1445,Tornado, ,EF5,14,0,40000000,0,AL,CST-6, ,50516,C,79,HUN,0,0,NWS Storm Survey, ,28.19,2200,3,WSW,1,ESE,FISH POND,34.4368,-87.5307,34.6459,-87.1055,"The violent tornado continued to track northeast from Franklin County into Lawrence County as an EF-5 near the Mt. Hope area where significant devastation was incurred to single family homes and a restaurant.  Nothing but the foundation and a pile of debris remained in this area, and a small portion of the restaurant foundation buckled.  Thousands of hardwood and softwood trees were snapped, with a significant number of trees twisted and debarked with only stubs of branches remaining.  Many mobile homes were also destroyed with the frames mangled, and a single family home was completely destroyed with the walls and contents strewn over a hundred yards.  Further northeast the damage was slightly less intense, with more trees snapped and twisted as the tornado reached Highway 24.  At this location multiple chicken houses were completely destroyed with much of the debris wrapped around debarked trees.  TVA high voltage power line trusses were also destroyed at this location.  As the tornado continued northeast more significant damage occurred in and around the Langtown community north of Moulton.  On the west side of Alabama Highway 33, several homes sustained significant damage with roofs missing or only interior rooms remaining.  A nearby store and gas station also sustained significant damage.  The tornado strengthened again to a high end EF-4 as it moved over County Roads 214 and 298, where multiple houses and mobile homes were completely destroyed.  Several cars were tossed into fields and wrapped around trees along County Road 291 and 292.  One vehicle was tossed into a large hardwood tree that was also debarked.  Tree and mobile home damage continued along County Roads 217 and 222, where a handful of large high tension TVA power poles were destroyed.  Sustained EF-4 damage continued northeast towards Alabama Highway 20, where a restaurant was completely destroyed and two single family houses were significantly damaged.  Tree damage continued into extreme northeastern Morgan County.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",29
+303563,ITAWAMBA CO.,NEW SALEM,04/27/2011,1448,Tornado, ,EF5,0,0,100000,0,MS,CST-6, ,50307,C,57,MEG,0,0,NWS Storm Survey, ,10.98,1320,4,S,6,SE,TREMONT,34.0891,-88.36,34.1677,-88.1932,"A violent tornado moved northeast from Monroe County, Mississippi into Southeast Itawamba County. The tornado weakened as it moved through Itawamba County. Numerous trees and power lines were knocked down. One home sustained roof damage. The tornado continued northeast and crossed over into Marion County, Alabama.","A stationary front remained draped across Southern Missouri into Western Kentucky from April 24th, 2011 into April 25th, 2011. A very warm and unstable atmosphere was in place across the Mid-South ahead of the front. A low pressure system developed along the front and interacted with the unstable environment which helped produce several rounds of severe storms into the evening of April 26th, 2011. As a result of the severe storms, the front sank south during the early morning hours of April 27th, 2011 as a secondary low pressure system developed along the front. As a result, another round of severe storms fired during the afternoon hours ahead of the low pressure center. Additional severe storms fired along the trailing cold front. Tornadoes, large hail, damaging winds, flash flooding occurred as a result of the severe storms.",30
+301925,JACKSON CO.,HODGE,04/27/2011,1501,Tornado, ,EF4,6,0,0,0,AL,CST-6, ,50516,C,71,HUN,0,0,NWS Storm Survey, ,24.18,1260,1,W,2,S,HIGDON,34.6208,-85.9814,34.82,-85.6314,"A violent long track tornado began it's life about 3 miles northeast of Section producing damage of EF-0 to EF-1 intensity with peak wind speeds of 70 to 90 mph, snapping or uprooting several softwood and hardwood trees.  The tornado rapidly intensified and began producing high end EF-3 to low end EF-4 damage within a matter of minutes, with peak wind speeds of 150 to 170 mph, and a path width of 1/2 to 3/4 mile as it roared into areas northeast of Pisgah and north of Rosalie.  Residents interviewed remarked that up to 3 tornadoes merged into one very large tornado.  There was evidence of this in the damage swath.||The tornado swarmed several mobile homes and block foundation homes in its path, snapping or uprooting thousands of trees.  Numerous trees were debarked in the process.  The tornado leveled at least 2 mobile homes and swept their remains hundreds of yards downwind.  Three were killed in 3 separate residences (6 total fatalities - 2 in Pisgah and 4 in the Higdon/Flat Rock communities).  Several vehicles were launched or swept several yards in different directions, in a few cases up to 50 yards.  The Friendship Church roof was heavily damaged.  Several farms were also affected, with barns and chicken houses heavily damaged or destroyed.||As the tornado continued its path, it intensified further on approach to Flat Rock and Higdon, producing damage of high end EF-4 intensity with peak winds up to 190 mph.  The tornado killed three from the same family at a residence southwest of Flat Rock.  The tornado mowed thousands in up to a 3/4 mile wide path.  One well-built block foundation home literally exploded as the tornado struck, lifting and sweeping all its structure and contents downwind, in some cases several hundred yards.  Miraculously, a mother and 3 children taking refuge in a hallway were completely unharmed.  At this farm, all fencing was destroyed and up to 19 cattle perished.  Two chicken barns were completely obliterated and swept away and unidentifiable.  A propane tank was lifted from the previous location of chicken barns and dropped over 100 yards away in front of the destroyed home.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",31
+301902,LIMESTONE CO.,LAWNGATE,04/27/2011,1517,Tornado, ,EF4,4,45,1000000000,0,AL,CST-6, ,50516,C,83,HUN,30,0,NWS Storm Survey, ,18.86,1320,4,S,2,NNE,CAPSHAW,34.662,-87.0705,34.8017,-86.7855,"The violent tornado continued it's path from the Tennessee River along the Lawrence/Limestone county line northeast through Tanner and into the east Central portion of Limestone County.   Homes were completely obliterated along a wide swath in the Tanner community.  Nearly a dozen high tension power lines were snapped or taken to the ground in Limestone County.  Concrete power poles were also snapped off at their base.  A subsequent ground team, aided by a storm survey expert from the University of Alabama in Huntsville, surveyed the most intense damage in Limestone County.  High end EF-3 damage was noted over a large area in eastern Limestone County along and north of the East Limestone High School.  The intensity was maximized in Limestone County in the community of Tanner, with a large swath of EF-4 damage and a narrow corridor of high end EF-4 damage.  Several well-constructed homes with anchor bolting were completely wiped clean.  One home had the debris lofted over 300 hundred yards with large items carried completely away.  Intense ground scarring was noted in this area.  In addition, a large cargo container was picked up and blown approximately 600 yards and several cars were carried airborne for hundreds of yards.  In all, hundreds of homes received moderate to major damage along the path with many of these being total losses.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",32
+301929,DEKALB CO.,IDER,04/27/2011,1530,Tornado, ,EF4,6,0,0,0,AL,CST-6, ,50516,C,49,HUN,0,0,NWS Storm Survey, ,3.48,1260,7,NNE,10,N,SULPHUR SPGS,34.82,-85.6314,34.8431,-85.5799,"A violent tornado continued its wide path of violent destruction across the northern tip of DeKalb County in the Shiloh community.  The tornado killed 6 people in this area (12 total along its path across Jackson and DeKalb counties).  Several cinder block foundation homes and mobile homes were completely destroyed or swept away.  In addition, thousands of large trees were sheared off toward the base.  An older two-story and fairly well-built log cabin home was destroyed.  The top story of this home was lifted off, moved about 20 yards and twisted 180 degrees.  The lower story collapsed and was shifted off its foundation.  A senior citizen van was lofted and dropped into a field nearly 400 yards away.  At least 3 chicken barns collapsed with a high loss of livestock noted.  The tornado crossed into Dade County Georgia with a 1/4 to 1/2 mile wide path along County Road 155 north of Highway 75.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",33
+309071,WALKER CO.,MARIETTA,04/27/2011,1535,Tornado, ,EF4,9,40,115000000,0,AL,CST-6, ,50455,C,127,BMX,0,0,NWS Storm Survey, ,29.02,1056,4,SSW,5,NE,DILWORTH,33.6448,-87.4238,33.8668,-86.995,"The sixth segment of this long track tornado entered southwest Walker County south of Blue Water Rd and moved northeast, where it eventually exited the northeast portion of the county east of Phillipstown Rd. This tornado began in Pickens County, 5 miles northeast of Pickensville, and tracked through Tuscaloosa, Fayette, Walker, Cullman (See Storm Data for Huntsville), and Blount Counties, before it dissipated in Marshall (See Storm Data for Huntsville) County. While the average path width of this tornado in Walker County was around 0.3 miles (528 yds), the tornado widened as it approached the city of Cordova to a path width maximum of 0.6 mile (1056 yds). Shortly after it entered the county, the tornado knocked down a cell phone tower, caused minor roof damage to a mobile home and single family home, and completely destroyed a mobile home as it approached AL Hwy 69. As the storm continued northeast crossing Earnest Chapel Rd southeast of Oakman, several vehicles were rolled and a home was destroyed. This resulted in 1 fatality and 2 injuries. The tornado continued east northeast where it crossed CR 35 and AL Hwy 269 south of Parrish. The tornado weakened to an EF0 as it approached Corridor X/future Interstate 22, with only minor tree damage noted, before it strengthened significantly as it neared Cordova. A 0.6 mile wide swath of EF3 damage, with winds of 140 mph, was noted in downtown Cordova. Numerous homes and buildings sustained significant damage, if not complete destruction, resulting in 4 fatalities. The tornado continued northeastward across Burton Chapel Loop Road and crossed the Mulberry Fork of the Black Warrior River. As it crossed Mountain View Road, the tornado increased to a violent EF4 rating, with winds of 170 mph, and destroyed 2 mobile homes, as well as a single family home. One of the mobile home undercarriages was missing, having been tossed at least 500 yards. At this site, a small bulldozer was flipped over, a pickup truck was tossed 200 yards, and an International 4700 dump truck was tossed 50 yards and was destroyed upon landing. A 2 ton utility trailer from this location was found a mile away, with a 2.5 ft impact crater where it landed. As the tornado neared Old Hwy 78, it tossed two double wide mobile homes at least 100 yards, resulting in their complete destruction. Two fatalities occurred here. The tornado continued toward Sipsey, where an unanchored double wide mobile home was tossed 100 feet up a 50 foot embankment. Two fatalities occurred in this area. The tornado continued at a minimum of EF2 strength to the northeast where it destroyed several homes and tossed a double wide mobile home 100 ft, south of Campbellville. Along this path, significant tree damage was noted, as well as damage to or the complete destruction of numerous other single family homes and manufactured homes.||This was the second tornado to hit downtown Cordova on this day. At 418AM-436AM CST, a tornado with winds of 120 mph moved through the same area causing significant structural damage.","A powerful storm system crossed the Southeast United States on Wednesday, April 27, 2011, resulting in a large and deadly tornado outbreak.  This epic event broke the record for number of tornadoes in a day for the state of Alabama, becoming the most significant tornado outbreak in the state���s history. ||Central Alabama had two rounds of severe weather that day. During the early morning hours, a Quasi-Linear Convective System quickly moved across the northern half of the National Weather Service, Birmingham county warning area. Straight line winds of 90 mph (78kts) or greater and 11 tornadoes lead to widespread damage and power outages. During the afternoon, long-lived supercell thunderstorms produced long-track, strong and violent tornadoes. Destruction and loss of life across many towns and communities was devastating. ||The hardest hit areas included Shottsville and Hackleburg, both in Marion County, where winds of 160 mph and 210 mph respectively, caused unimagineable damage. Cordova, in Walker County, was hit twice; by a tornado along the Quasi-Linear Convective System during the early morning hours and again in the afternoon by a long-track EF4 tornado. A long track tornado moved across the city of Tuscaloosa and the western suburbs of Birmingham, resulting in the complete destruction of whole neighborhoods and numerous injuries and fatalities in those heavily populated areas. The same parent supercell produced another violent tornado in east Central Alabama as it tracked across St. Clair and Calhoun Counties, resulting in additional fatalities and incredible damage to a number of neighborhoods. Another violent EF4 tornado tracked across portions of Elmore and Tallapoosa Counties, including Lake Martin, destroying numerous homes and a large section of a mobile home park. ||Most of the violent tornadoes from this day were captured on video by a number of people, including storm spotters and chasers, as well as numerous television news crews and remotely controlled web-enabled video cameras.  This allowed unprecedented coverage and viewing of this historic event in real time from people worldwide.",34
+309095,MADISON CO.,CLUTTSVILLE,04/27/2011,1536,Tornado, ,EF4,9,0,0,0,AL,CST-6, ,50516,C,89,HUN,0,0,NWS Storm Survey, ,27.2,880,2,SSW,2,ENE,ROSEBORO,34.8017,-86.7855,34.9915,-86.365,"The tornado crossed in Madison County east of Limestone County Prison���along Orvil Smith Road with a path width of �� mile.  The tornado maintained an EF-3 strength with winds of 140 to 160 MPH and a path width between �� and �� mile for much of its track northeast across Old Railroad Bed Road and Ford Chapel Road, before narrowing to around 300 yards in Anderson Hills. Dozens of well-constructed homes were destroyed, in some cases with all exterior walls collapsing in both single and two-story homes. At least 3-5 mobile homes were either destroyed or swept completely clean with no evidence of debris.  At least 2 other well-constructed homes had complete wall collapse in Anderson Hills and were shifted off their foundation. This damage was once again consistent with low end EF-4 wind speeds of around 170 MPH.||Numerous tall pines and other hardwood trees were snapped, uprooted and debarked along the entire path. The path width widened once again to around �� mile as the tornado tracked through residential areas along Bald Eagle Lane, Old Eli Road and Ginnery Row.  At least 2 of these homes had complete wall collapse, but these structures had foundation straps and nails in lieu of bolts. At least one fatality was confirmed at one of these residences. Eight additional fatalities occurred in Madison County along the track of this violent tornado. The damage was consistent with high end EF-3 wind speeds between 140 and 160 MPH. The tornado lifted just south of the Patterson Lane after twisting irrigation equipment and snapping additional trees. Just to the northeast of this location, the tornado touched down again as an EF-0 tornado with peak wind speeds of 70 MPH. Along Grimwood Road and Walker Lane, south of Hazel Green, the tornado uprooted and snapped several trees. The tornado weakened or may have lifted briefly across extreme northeast Madison County before re-strengthening again as it entered Lincoln County in Southern Middle Tennessee.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",35
+314662,TUSCALOOSA CO.,RALPH,04/27/2011,1548,Tornado, ,EF4,44,800,1500000000,0,AL,CST-6, ,50455,C,125,BMX,0,8,NWS Storm Survey, ,41.79,1760,4,WNW,4,NNE,YOLANDE,33.0606,-87.8315,33.3512,-87.1975,"This tornado initially touched down in rural northern Greene County and moved northeast through southern Tuscaloosa and western Jefferson Counties, causing devastating damage consistent with a violent EF4 rating to portions of the city of Tuscaloosa and western suburbs of Birmingham, before it lifted northeast of downtown Birmingham. The tornado entered Tuscaloosa County just north of CR 60, west northwest of Ralph, and moved northeast causing tree damage and minor structural damage consistent with an EF2 rating and winds of 125 mph. The tornado strengthened as it crossed the Black Warrior River, north of Interstate 20 and approached Tuscaloosa. As the tornado approached Interstate 359, several buildings were destroyed including the Tuscaloosa County Emergency Operations Center. The tornado strengthened further to a violent EF4 with winds of 190 mph. Along 15th St E. and McFarland Blvd E., several small restaurants and stores were destroyed, with only a wall or two still standing. The tornado devastated the Cedar Crest neighborhood just north of 15th St, leveling many cinder block homes and causing at least 3 fatalities. The tornado crossed McFarland Blvd, destroying additional stores and restaurants. The tornado crossed University Blvd in the Alberta City community. Alberta Elementary School suffered nearly complete destruction, with only a few portions of walls still standing. A nearby two story apartment building was reduced to rubble sitting on the foundation. The Alberta Park Shopping Center was completely destroyed with no walls standing and a pile of debris on the foundation. Cinder block construction homes in the surrounding neighborhood were completely destroyed, and in a few cases debris was swept away from the site. The tornado continued northeast and struck the Chastain Manor Apartments at the north end of 34th Ave E. Buildings on the east side of this new 2 story apartment complex were completely destroyed, with only a pile of debris remaining and a few walls set into the hillside. A small club house that was anchored to a foundation, but with apparently no interior walls, was completely destroyed and swept from its foundation. Similar devastation to homes and businesses was noted along both sides of CR 45 near 1st St E. and locations to the northeastward. East of Holt, the tornado path width widened from 0.5 mile to around 1 mile. The tornado crossed Holt Peterson Rd just northwest of Clinker Rd, where two homes were completely destroyed. One home on a foundation was swept clean, with only floor joists remaining attached to the foundation. Almost all trees were blown down or snapped in the vicinity, as well as in the bottom of a narrow ravine nearly 100 feet below the house. The tornado continued to Holt Lock and Dam Road near its intersection with Recreation Area Road. Numerous mobile homes and several cinder block homes were destroyed in this area, which resulted in several fatalities. The tornado struck a marina on Holt Lake at the end of Recreation Area Road where it caused significant damage to a restaurant as well as numerous boats. Several injuries were noted in this area. The tornado continued northeastward and weakened to an EF3 rating with winds of 130 mph. As its path narrowed to 0.5 mile, the tornado passed north of Brookwood, near the intersection of Hannah Creek Rd and CR 59. Several mobile homes were destroyed, cinder block homes received heavy damage, and significant tree damage was noted in this area. The tornado moved parallel to Hannah Creek Rd where it caused extensive tree damage and destroyed at least one mobile home. The tornado crossed CR 99 and moved into western Jefferson County, 4 miles north of Abernant. A person died (indirect) several weeks after the event as a result of contracting pneumonia from exposure to the elements after his home was destroyed. An additional 6 people died (indirect) in the months following the tornado from the stress of the event, not direct injury.||This tornado was produced by a supercell thunderstorm that began in Newton County Mississippi at 13:54 pm CST, finally dissipating in Macon County, North Carolina at approximately 21:18 pm CST. This supercell spawned several strong to violent tornadoes along its long path.","A powerful storm system crossed the Southeast United States on Wednesday, April 27, 2011, resulting in a large and deadly tornado outbreak.  This epic event broke the record for number of tornadoes in a day for the state of Alabama, becoming the most significant tornado outbreak in the state���s history. ||Central Alabama had two rounds of severe weather that day. During the early morning hours, a Quasi-Linear Convective System quickly moved across the northern half of the National Weather Service, Birmingham county warning area. Straight line winds of 90 mph (78kts) or greater and 11 tornadoes lead to widespread damage and power outages. During the afternoon, long-lived supercell thunderstorms produced long-track, strong and violent tornadoes. Destruction and loss of life across many towns and communities was devastating. ||The hardest hit areas included Shottsville and Hackleburg, both in Marion County, where winds of 160 mph and 210 mph respectively, caused unimagineable damage. Cordova, in Walker County, was hit twice; by a tornado along the Quasi-Linear Convective System during the early morning hours and again in the afternoon by a long-track EF4 tornado. A long track tornado moved across the city of Tuscaloosa and the western suburbs of Birmingham, resulting in the complete destruction of whole neighborhoods and numerous injuries and fatalities in those heavily populated areas. The same parent supercell produced another violent tornado in east Central Alabama as it tracked across St. Clair and Calhoun Counties, resulting in additional fatalities and incredible damage to a number of neighborhoods. Another violent EF4 tornado tracked across portions of Elmore and Tallapoosa Counties, including Lake Martin, destroying numerous homes and a large section of a mobile home park. ||Most of the violent tornadoes from this day were captured on video by a number of people, including storm spotters and chasers, as well as numerous television news crews and remotely controlled web-enabled video cameras.  This allowed unprecedented coverage and viewing of this historic event in real time from people worldwide.",36
+302149,CULLMAN CO.,ARKADELPHIA,04/27/2011,1605,Tornado, ,EF4,0,0,20000000,0,AL,CST-6, ,50516,C,43,HUN,0,0,NWS Storm Survey, ,4.42,440,3,SSW,2,E,ARKADELPHIA,33.8668,-86.995,33.8975,-86.9274,"A large violent tornado continued it's track from Walker County into the Huntsville County Warning Area (CWA) across the very southern tip of Cullman County, from about 3 miles southwest of Arkadelphia to just over 2 miles ESE of Arkadelphia. This tornado then tracked out of the Huntsville CWA into Blount County. In Cullman County, a wide swath of pine and hardwood trees was found snapped at the bases or splintered several feet off the ground, with some debarking of trees. South of Hwy 91 along Washington Loop, several homes were damaged or destroyed. A mobile home was obliterated and the frame was found at least 200 yards to the east up a hill. A cinder block home was wiped out, with the contents landing across the road, while the cars nearby were tossed. A truck landed in a nearby hollow at least 50 yards away while a sedan was smashed as it landed about 130 yards away. Farming equipment in a barn was displaced into the hollow, including a hay baler and a tractor. The storm shelter by the residence was partially lifted and damaged. The person inside received minor injuries. Additional homes and buildings nearby were destroyed and only a few trees were left standing or not debarked. The main damage path was fairly well confined, as a well built home just at the edge of the track only sustained minor roof damage.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",37
+301882,JACKSON CO.,FACKLER,04/27/2011,1605,Tornado, ,EF4,1,0,0,0,AL,CST-6, ,50516,C,71,HUN,0,0,NWS Storm Survey, ,20.24,1320,2,SE,3,ENE,LONG IS,34.7948,-85.909,34.9854,-85.6377,"A violent tornado touched down northeast of Fackler along County Road 42 where several large trees were snapped and minor damage occurred to mobile homes.  The tornado continued east-northeast producing tree damage as it crossed U.S. Highway 72 near the intersection of State Highway 117.  On Oak Hill Road just east of Highway 72, large trees were snapped and several roofs were damaged.  On County Road 286, a trailer was tipped over and a shed was partially destroyed.||The tornado continued northeast producing heavy tree damage.  The tornado produced EF-3 damage along County Road 96 just northeast of the Stevenson Airport, where 24 high tension electrical truss towers were twisted and flattened.  Just south of the intersection of County Road 96 and State Highway 277, a mobile home was obliterated and another home collapsed.  Two other homes sustained structural damage along this section of road, two mobile homes were rolled on their side, and a metal barn was destroyed.||The tornado continued northeast and at the intersection of County Roads 255 and 256, the most significant damage was encountered and rated EF-4.  A residence just to the south of this intersection was reduced to its foundation.  A concrete slab at the front of the home was pulled up, and a set of concrete stairs was ripped from the foundation.  A compact car was thrown about 50 yards.||To the northeast of the intersection, two well-built and well-anchored homes were also reduced to their foundations.  A car was thrown approximately 50 yards across the street from one residence.  Several large trees were snapped off a few feet above the ground.  A third residence along County Road 256 had zero walls left standing.  Across the street from this home, a mobile home was completely demolished and strewn along County Road 256.||The tornado continued northeastward, destroying a cinder block garage and damaging a mobile home along 6th Street just southeast of Bridgeport.  The tornado crossed the Tennessee River, producing significant tree damage along County Road 91 before crossing into Marion County in Tennessee.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",38
+314663,JEFFERSON CO.,WELLER,04/27/2011,1635,Tornado, ,EF4,20,700,700000000,0,AL,CST-6, ,50455,C,73,BMX,0,0,NWS Storm Survey, ,32.53,2600,3,WNW,1,W,BLACK CREEK,33.3512,-87.1975,33.6311,-86.7436,"This tornado initially touched down in rural northern Greene County and moved northeast through southern Tuscaloosa and western Jefferson Counties. The tornado caused devastating damage consistent with a violent EF4 rating to portions of the city of Tuscaloosa and western suburbs of Birmingham and then lifted northeast of downtown Birmingham. The tornado entered western Jefferson County 5.5 miles west of North Johns. The tornado continued to cause significant tree damage as it crossed Sealy Ann Mountain Rd and CR 23. As the tornado crossed Valley Creek and the far northern portion of Virginia, several homes sustained minor damage. The tornado strengthened to a violent EF4 rating with winds of 190 mph as it approached Concord. Several retail stores were destroyed along CR 46 and only piles of debris were left on their foundations. Several cinder block homes were completely destroyed with debris swept away. In addition, numerous other homes in the area were destroyed with only a few interior walls left standing. At least five fatalities occurred in Concord. The violent tornado continued northeastward toward Pleasant Grove, where extensive damage occurred across western and northern parts of town. Numerous homes were destroyed and foundations swept clean of debris. Several vehicles were picked up and tossed 15 yds. At least 11 fatalities occurred in Pleasant Grove. The tornado quickly moved into McDonald Chapel, near the intersection of CR 80 and Vicksburg St, killing one person. The tornado weakened to an EF2 with winds of 125 mph, but still damaged many homes and destroyed several others. The tornado moved through the Smithfield Estates area where it caused significant damage along Cherry Ave between Daniel Payne Dr and US Hwy 78 and resulted in one fatality. Numerous homes and a 2-story apartment complex sustained significant damage, consistent with an EF2 rating. As the tornado moved northeast, it crossed Interstate 65 near mile marker 266 and into the city of Fultondale. The path width increased to around 1.5 miles. Hundreds of trees were downed along the interstate and several light poles were folded over. Several buildings along US Hwy 31 sustained significant roof and structural damage. The tornado continued northeast where it crossed CR 124, and lifted just west of AL Hwy 79, 4 miles north of Tarrant. ||This tornado was produced by a supercell thunderstorm that began in Newton county Mississippi at 13:54 pm CST, finally dissipating in Macon county, North Carolina at approximately 21:18 pm CST. This supercell spawned several strong to violent tornadoes along its long path, including another violent EF4 tornado that crossed portions of east Central Alabama.","A powerful storm system crossed the Southeast United States on Wednesday, April 27, 2011, resulting in a large and deadly tornado outbreak.  This epic event broke the record for number of tornadoes in a day for the state of Alabama, becoming the most significant tornado outbreak in the state���s history. ||Central Alabama had two rounds of severe weather that day. During the early morning hours, a Quasi-Linear Convective System quickly moved across the northern half of the National Weather Service, Birmingham county warning area. Straight line winds of 90 mph (78kts) or greater and 11 tornadoes lead to widespread damage and power outages. During the afternoon, long-lived supercell thunderstorms produced long-track, strong and violent tornadoes. Destruction and loss of life across many towns and communities was devastating. ||The hardest hit areas included Shottsville and Hackleburg, both in Marion County, where winds of 160 mph and 210 mph respectively, caused unimagineable damage. Cordova, in Walker County, was hit twice; by a tornado along the Quasi-Linear Convective System during the early morning hours and again in the afternoon by a long-track EF4 tornado. A long track tornado moved across the city of Tuscaloosa and the western suburbs of Birmingham, resulting in the complete destruction of whole neighborhoods and numerous injuries and fatalities in those heavily populated areas. The same parent supercell produced another violent tornado in east Central Alabama as it tracked across St. Clair and Calhoun Counties, resulting in additional fatalities and incredible damage to a number of neighborhoods. Another violent EF4 tornado tracked across portions of Elmore and Tallapoosa Counties, including Lake Martin, destroying numerous homes and a large section of a mobile home park. ||Most of the violent tornadoes from this day were captured on video by a number of people, including storm spotters and chasers, as well as numerous television news crews and remotely controlled web-enabled video cameras.  This allowed unprecedented coverage and viewing of this historic event in real time from people worldwide.",39
+312007,JASPER CO.,HAMLET,04/27/2011,1655,Tornado, ,EF4,2,0,900000,800000,MS,CST-6, ,51541,C,61,JAN,0,0,NWS Storm Survey, ,24.12,1050,4,NNW,3,N,ORANGE,32.0712,-89.3201,32.1444,-88.9172,"This tornado started by downing some trees just southeast of Raleigh, near and across Highway 18. As the tornado moved northeast along Bailey Road and crossed County Road 130, it intensified and produced high end EF-1 damage, snapping and uprooting trees, taking shingles off roofs, and blowing skirting out from mobile homes. The tornado continued to strengthen as it moved northeast, and along County Roads 136, 107, and 105, it produced damage indicative of high end EF-2. A few mobile homes were destroyed and several homes and buildings sustained significant roof damage, along with extensive tree damage. Along County Road 105, a mobile home was picked up by the tornado, bounced along the ground a couple of times, and was then thrown into woods across the road, with debris scattered for at least a mile downstream, including the frame of the mobile home. The occupant of the mobile home was the first fatality of this tornado. The tornado continued northeast, and reached its most intense and widest point in the Smith County portion of the tornado just before crossing the county line at County Road 103. Here, in the central core of the tornado there was an area of completely mowed down pine trees in which everyone was snapped and many were denuded, and two frame homes had the roofs and exterior walls completely destroyed with extensive damage to interior walls. In addition, many power poles were snapped, a mobile home was annihilated, and a large shop building was completely destroyed. The damage here was rated high end EF-3 with maximum estimated winds of 160 mph.||The tornado remained intense as it crossed into Jasper County and moved across County Road 13, causing very impressive tree damage with nearly every pine tree snapped and extensive evidence of denuding and debarking. Power poles were also snapped. The tornado produced similar type damage as it crossed County Road 16. The tornado then produced its first area of EF-4 damage just northwest of Louin along County Road 164. Here, the tornado struck an area with several mobile homes and one frame home. The frame home was completely destroyed, with most interior walls down and some of the foundation pushed clean. Several mobile homes in the area, including two double wides which the residents said were well strapped down, were completely destroyed with the debris and frames blown great distances. In fact, all of the debris was so dispersed and mixed that it was impossible for the surveyors to reconstruct the positions of the mobile homes and house without explanations from the residents. Two people were killed in a mobile home at this spot; however, several other people abandoned their mobile homes after hearing warnings to shelter in a nearby brick home, and were certainly saved from serious injury or death. ||After crossing Highway 15, the tornado weakened and narrowed somewhat. As it crossed County Road 23, it produced EF-2 damage, destroying two mobile homes and causing extensive tree and powerline damage. The tornado then produced a relatively narrow path of EF-1 tree and powerline damage for several miles, until reintensifying near Rose Hill. As the tornado crossed Highway 18 southeast of Rose Hill, it removed most of the roof of a frame home and caused heavy damage to the exterior walls, took a large section of roof off another frame home, completely destroyed a large tied down mobile home, and caused extensive tree damage. This damage was rated at the low end of EF-3. After causing this damage, the tornado weakened again, causing mainly EF-1 type tree damage until it reached the Clarke County line, with the last point inside the county line on County Road 22 rated as EF-0, with just a few trees and limbs down. ||The tornado then continued into Clarke County and reintensified somewhat, causing tree and powerline damage as it crossed Interstate 59 and US Highway 11. The tornado then became much more intense as it moved along the south side of the town of Enterprise. A number of homes and mobile homes were heavily damaged or destroyed along County Road 320 and State Highway 513. This damage was rated as high EF-2 to low end EF-3. As the tornado passed along a two mile stretch of State Highway 519 east of Enterprise, it heavily damaged several frame homes and caused extensive tree damage. One spot here was the other area of EF-4 damage produced by this tornado. A new construction frame home was completely leveled with the debris swept off the foundation. Residents in the area reported that the house was nearly completed. Based on these reports and the extent of other nearby, primarily tree, damage, this damage is being rated EF-4 with maximum winds of 175 mph. Other damage in this general area was rated as high end EF-2 or low end EF-3. ||The tornado weakened slightly again as it crossed US Highway 45 and State Highway 145, and then caused high end EF-2 and low end EF-3 damage at County Roads 456 and 457. Here, several strapped down double wide mobile homes were destroyed with debris strewn over long distances. Nearby residents reported that one of the mobile homes was occupied by 11 persons at the time of the tornado, and that this was the location where 4 people were killed. Another resident of a nearby mobile home was critically injured. From here, the tornado passed east northeast, just north of the Energy and Snell communities, causing EF-2 damage to a number of frame homes along with extensive tree and powerline damage. The tornado crossed Highway 514 northeast of Snell, still causing extensive tree damage and significant roof damage to several large frame homes, before moving across the state line into Choctaw County, Alabama. The tornado continued into Alabama for 59 miles, bringing the total path length to 124 miles.","A historic outbreak of tornadoes across the Ark-La-Miss began late on Tuesday, April 26th continuing into the early morning hours of Wednesday, April 27th. The event ramped up again during the early afternoon of April 27th continuing into the early evening.  The activity on April 26th began as supercell thunderstorms producing large hail and tornadoes across northeast Texas and portions of Arkansas before evolving into a squall line as it moved east. This line of storms had multiple stages of evolution and moved across several states before dissipating. This line was very efficient in producing wind damage as it pushed east. More impressively, this line was responsible for 23 of the 32 tornadoes that occurred across the Ark-La-Miss during this event. Of those 23, 12 were rated as strong (EF2, EF3) tornadoes and had fairly long path lengths.||The atmosphere reloaded quickly Wednesday morning and became increasingly favorable for more severe storms by early afternoon. The driving force for the activity Wednesday afternoon was a potent shortwave and deep surface low that intensified during the day. The winds in the mid levels of the atmosphere increased to 80-100 mph helping to deepen the surface low further, which in turn caused the low level winds to become stronger. The wind shear caused by the turning of the winds from south near the surface to westerly aloft was at rare levels for late April over the Deep South. In addition, an abundance of low level moisture returned to the area in wake of the morning complex. Sunny skies during the morning interacted with the high levels of low level moisture eventually leading to a very unstable air mass by early afternoon. The result was an extremely rare mix of instability and wind shear. These ingredients, along with lift from a potent upper disturbance, ultimately led to the historic tornado outbreak of April 27, 2011.||By early afternoon, several discrete supercell thunderstorms were developing across central and eastern Mississippi. It did not take long for these storms to take on ���classic��� supercell structures and begin producing tornadoes. The first tornado of the afternoon started in Neshoba County on the north side of Philadelphia. This tornado ended up producing EF-5 damage and tracked for 29 miles across Neshoba, Kemper, Winston and Noxubee Counties. Through the rest of the afteroon multiple tornadoes developed, stemming from multiple supercell storms. Nearly all of the storms produced tornadoes, with many of them long track and significant. The other violent tornado to impact the Jackson, MS forecast area occurred across Smith, Jasper, and Clarke Counties. This tornado continued into Alabama and had a total path length of 124 miles across both states.||Loss of life during this historic event was staggering. Unfortunately, 321 people lost their lives making this the second deadliest tornado outbreak in U.S. history. The March 18, 1925 Tri-State tornado outbreak is first with 747 fatalities. This marks the first EF-5 tornado in Mississippi since the Candlestick Park tornado on May 3, 1966, and this marks the first time since statistics have been kept that two EF-5 tornadoes have been recorded on the same day in Mississippi, with the tornado in Smithville also rated as EF-5. Incredibly, 4 tornadoes had path lengths over 100 miles across the southern states during this event, and all 4 of these were rated either EF-4 or EF-5.",40
+301829,DEKALB CO.,TEN BROECK,04/27/2011,1719,Tornado, ,EF5,25,0,0,0,AL,CST-6, ,50516,C,49,HUN,0,0,NWS Storm Survey, ,33.66,1320,2,S,3,NE,SULPHUR SPGS,34.3907,-85.9784,34.7333,-85.5578,"A violent long track tornado began in the Lakeview community northeast of Geraldine before tracking northeastward, generally parallel to and just east of State Route 75.  Along this line, the tornado passed through Fyffe, Rainsville, Sylvania, and eventually into northern DeKalb County south of the Cartersville community, killing 25 people. On the first day of surveys, the survey team noticed initial damage in the Lakeview community where the path width was generally around 50 yards.  This initial damage included mostly felled and snapped trees and structural damage to small buildings.  Extensive damage was noted especially in Rainsville and Sylvania where the path width was estimated to over 1/2 mile wide.  Damage in Rainsville included houses that were completely removed from foundations, with debris scattered for about one mile.  Near this location, trees were debarked and a few mobile homes were completely destroyed, with debris strewn for about a mile downstream.||A narrow corridor of intense damage extended from Skaggs Road to Lingerfeldt Road (also known as County Road 180), extending toward County Road 514.  Along Skaggs Road, a stone house was completely obliterated with much of the interior debris strewn well away from the structure.  A supporting large cement stone pillar was ripped completely out of the ground.  Another home along Skaggs Road was also leveled completely to the ground. The NOAA overflight showed significant ground scarring in this area and a walk through the nearby fields showed large pot marks and other sections of disturbed ground. ||Slightly northeast along Lingerfeldt Road, numerous homes were leveled completely to their foundation with vehicles and debris strewn for hundreds of feet.  Overhead photos and follow-up visual confirmation revealed a mangled vehicle tossed well into a ravine and resting up in the remainder of trees.  At  1608 Lingerfeldt Road/County Road 180, a large two story brick home was completely obliterated with several of the supporting anchors ripped of the ground.  A concrete porch was ripped off with pieces strewn up to 150 yards.  A section of the asphalt driveway was pulled up.  In addition, an anchored liberty safe weighing 800 pounds was pulled off its anchorage and thrown into a wooded area 600 feet away.  When found, the safe's door had been ripped open and completely off.  A large pick-up truck at this residence was found mangled in pieces over 250 yards away in the same wooded area.  The residents of the home survived in a nearby storm pit.  Of note, the storm pit was partially exposed by the tornado with dirt being sucked up and pulled away around the opening.  Next door, a mobile home was completely disintegrated.  The residents of the mobile there also survived in a storm pit.  The section of damage from Skaggs Road to Lingerfeldt Road near the intersection with Crow Lane was deemed to be EF-5 intensity.   Severe damage with high end EF-4 damage was noted in a corridor from County Road 515 through a neighborhood along County Road 441.  In the east and south ends of the neighborhood, many one and two story homes were leveled to their foundation with debris scattered some distance.  Several cars were thrown a large distance in this area.  There was evidence of ground scarring as well as some sidewalk pavement pulled up in this location.  However, some of the homes in this area appeared to be pushed off their foundation initially with limited anchorage. ||In the Sylvania community, similar situation occurred with houses completely removed from foundations and debris blown far downstream.  Some of these houses were connected to their foundations with anchor bolts and foundation straps, indicating a stronger construction of the homes. ||Tornado damage continued from the Blake community, intersecting County Road 27, running parallel between State Highway 75 and Interstate 59 through Henager, Ider, to south of Cartersville.  ||In the Blake community, the tornado path width was estimated to be one half to three quarters of a mile.  Along County Road 27 just southeast of Sylvania, significant damage was observed .  All exterior and interior walls of several homes were completely destroyed with partial block and mortar foundations remaining.  In one instance, a concrete slab that served as a porch was displaced a few feet and broken in half.  Some hardwood trees in the area were stripped with no stubs of any branches remaining and were partially debarked.  The Mountain View Baptist Church sustained significant damage.  An old, one-story portion of the church dating back to 1902 and constructed of a brick and mortar exterior on wood frame walls was completely destroyed.  A recent two-story addition to the church was constructed in 2004 and consisting of similar building materials was partially destroyed, with most exterior walls and nearly all interior walls fallen.  A concrete block and mortar foundation was all that remained of a hallway adjoining the two buildings.","A powerful storm system roared across the Southeast United States on Wednesday, April 27, 2011. In the wake of this system, hundreds of people were left injured and/or homeless, along with approximately 100 people who lost their lives in the northern Alabama area alone. Some of the devastation was literally unimaginable with countless homes, neighborhoods and even portions of cities or towns either partially or completely destroyed. This storm system would be responsible for one of the largest and deadliest tornado outbreaks to ever impact much of the southeastern region.| |The powerful storm system that affected the National Weather Service, Huntsville service area would actually occur in three separate waves of severe weather that day. The first occurred during the early morning hours of April 27, 2011 roughly between the hours of 2 AM and 8 AM CDT, while the second occurred during the late-morning to early afternoon period. The third and most devastating wave occurred during the afternoon hours on Wednesday, with some of the most violent and destructive tornadoes to affect the central Tennessee Valley area in recent decades.| |The worst areas impacted by these storms included the towns of Phil Campbell and Oak Grove in eastern Franklin County Alabama, Mt. Hope in western Lawrence County and the Tanner Community in eastern Limestone County. Along a line connecting these areas tracked an EF5 tornado with peak winds around 210 mph, the strongest and most violent on the Enhanced Fujita Scale. ||Other areas impacted by the storms include the city of Cullman, where extensive damage occurred to buildings in the downtown area, and to the town of Fairview, both of which are located in Cullman County. Downstream, further significant damage occurred to the Ruth and Oak Grove communities in Marshall County. In addition, the communities of Rainsville and Sylvania along with the towns of Henagar and Ider in DeKalb County were severely impacted. Fatalities in DeKalb County alone numbered at least 33 people. Furthermore, the towns of Flat Rock, Higdon and Pisgah in Jackson County sustained incredible damage. The tornadoes that affected these areas were rated as an EF4 with maximum winds near 190 mph.||In most of these areas alone, numerous people lost their lives. These represent just several of the communities and towns impacted by the events of April 27, 2011. While the majority of the analysis and survey work conducted by the National Weather Service, Huntsville and its partners have been completed, there will undoubtedly be countless research studies conducted by both academia and operational personnel in order to further evaluate and understand the complex processes associated with this near unprecedented severe weather outbreak.",41
+312009,CLARKE CO.,WAUTUBBEE,04/27/2011,1726,Tornado, ,EF4,4,14,900000,800000,MS,CST-6, ,51541,C,23,JAN,0,0,NWS Storm Survey, ,28.76,1050,4,WNW,1,ESE,HURRICANE CREEK,32.1439,-88.9154,32.2143,-88.4327,"This tornado started by downing some trees just southeast of Raleigh, near and across Highway 18. As the tornado moved northeast along Bailey Road and crossed County Road 130, it intensified and produced high end EF-1 damage, snapping and uprooting trees, taking shingles off roofs, and blowing skirting out from mobile homes. The tornado continued to strengthen as it moved northeast, and along County Roads 136, 107, and 105, it produced damage indicative of high end EF-2. A few mobile homes were destroyed and several homes and buildings sustained significant roof damage, along with extensive tree damage. Along County Road 105, a mobile home was picked up by the tornado, bounced along the ground a couple of times, and was then thrown into woods across the road, with debris scattered for at least a mile downstream, including the frame of the mobile home. The occupant of the mobile home was the first fatality of this tornado. The tornado continued northeast, and reached its most intense and widest point in the Smith County portion of the tornado just before crossing the county line at County Road 103. Here, in the central core of the tornado there was an area of completely mowed down pine trees in which everyone was snapped and many were denuded, and two frame homes had the roofs and exterior walls completely destroyed with extensive damage to interior walls. In addition, many power poles were snapped, a mobile home was annihilated, and a large shop building was completely destroyed. The damage here was rated high end EF-3 with maximum estimated winds of 160 mph.||The tornado remained intense as it crossed into Jasper County and moved across County Road 13, causing very impressive tree damage with nearly every pine tree snapped and extensive evidence of denuding and debarking. Power poles were also snapped. The tornado produced similar type damage as it crossed County Road 16. The tornado then produced its first area of EF-4 damage just northwest of Louin along County Road 164. Here, the tornado struck an area with several mobile homes and one frame home. The frame home was completely destroyed, with most interior walls down and some of the foundation pushed clean. Several mobile homes in the area, including two double wides which the residents said were well strapped down, were completely destroyed with the debris and frames blown great distances. In fact, all of the debris was so dispersed and mixed that it was impossible for the surveyors to reconstruct the positions of the mobile homes and house without explanations from the residents. Two people were killed in a mobile home at this spot; however, several other people abandoned their mobile homes after hearing warnings to shelter in a nearby brick home, and were certainly saved from serious injury or death. ||After crossing Highway 15, the tornado weakened and narrowed somewhat. As it crossed County Road 23, it produced EF-2 damage, destroying two mobile homes and causing extensive tree and powerline damage. The tornado then produced a relatively narrow path of EF-1 tree and powerline damage for several miles, until reintensifying near Rose Hill. As the tornado crossed Highway 18 southeast of Rose Hill, it removed most of the roof of a frame home and caused heavy damage to the exterior walls, took a large section of roof off another frame home, completely destroyed a large tied down mobile home, and caused extensive tree damage. This damage was rated at the low end of EF-3. After causing this damage, the tornado weakened again, causing mainly EF-1 type tree damage until it reached the Clarke County line, with the last point inside the county line on County Road 22 rated as EF-0, with just a few trees and limbs down. ||The tornado then continued into Clarke County and reintensified somewhat, causing tree and powerline damage as it crossed Interstate 59 and US Highway 11. The tornado then became much more intense as it moved along the south side of the town of Enterprise. A number of homes and mobile homes were heavily damaged or destroyed along County Road 320 and State Highway 513. This damage was rated as high EF-2 to low end EF-3. As the tornado passed along a two mile stretch of State Highway 519 east of Enterprise, it heavily damaged several frame homes and caused extensive tree damage. One spot here was the other area of EF-4 damage produced by this tornado. A new construction frame home was completely leveled with the debris swept off the foundation. Residents in the area reported that the house was nearly completed. Based on these reports and the extent of other nearby, primarily tree, damage, this damage is being rated EF-4 with maximum winds of 175 mph. Other damage in this general area was rated as high end EF-2 or low end EF-3. ||The tornado weakened slightly again as it crossed US Highway 45 and State Highway 145, and then caused high end EF-2 and low end EF-3 damage at County Roads 456 and 457. Here, several strapped down double wide mobile homes were destroyed with debris strewn over long distances. Nearby residents reported that one of the mobile homes was occupied by 11 persons at the time of the tornado, and that this was the location where 4 people were killed. Another resident of a nearby mobile home was critically injured. From here, the tornado passed east northeast, just north of the Energy and Snell communities, causing EF-2 damage to a number of frame homes along with extensive tree and powerline damage. The tornado crossed Highway 514 northeast of Snell, still causing extensive tree damage and significant roof damage to several large frame homes, before moving across the state line into Choctaw County, Alabama. The tornado continued into Alabama for 59 miles, bringing the total path length to 124 miles.","A historic outbreak of tornadoes across the Ark-La-Miss began late on Tuesday, April 26th continuing into the early morning hours of Wednesday, April 27th. The event ramped up again during the early afternoon of April 27th continuing into the early evening.  The activity on April 26th began as supercell thunderstorms producing large hail and tornadoes across northeast Texas and portions of Arkansas before evolving into a squall line as it moved east. This line of storms had multiple stages of evolution and moved across several states before dissipating. This line was very efficient in producing wind damage as it pushed east. More impressively, this line was responsible for 23 of the 32 tornadoes that occurred across the Ark-La-Miss during this event. Of those 23, 12 were rated as strong (EF2, EF3) tornadoes and had fairly long path lengths.||The atmosphere reloaded quickly Wednesday morning and became increasingly favorable for more severe storms by early afternoon. The driving force for the activity Wednesday afternoon was a potent shortwave and deep surface low that intensified during the day. The winds in the mid levels of the atmosphere increased to 80-100 mph helping to deepen the surface low further, which in turn caused the low level winds to become stronger. The wind shear caused by the turning of the winds from south near the surface to westerly aloft was at rare levels for late April over the Deep South. In addition, an abundance of low level moisture returned to the area in wake of the morning complex. Sunny skies during the morning interacted with the high levels of low level moisture eventually leading to a very unstable air mass by early afternoon. The result was an extremely rare mix of instability and wind shear. These ingredients, along with lift from a potent upper disturbance, ultimately led to the historic tornado outbreak of April 27, 2011.||By early afternoon, several discrete supercell thunderstorms were developing across central and eastern Mississippi. It did not take long for these storms to take on ���classic��� supercell structures and begin producing tornadoes. The first tornado of the afternoon started in Neshoba County on the north side of Philadelphia. This tornado ended up producing EF-5 damage and tracked for 29 miles across Neshoba, Kemper, Winston and Noxubee Counties. Through the rest of the afteroon multiple tornadoes developed, stemming from multiple supercell storms. Nearly all of the storms produced tornadoes, with many of them long track and significant. The other violent tornado to impact the Jackson, MS forecast area occurred across Smith, Jasper, and Clarke Counties. This tornado continued into Alabama and had a total path length of 124 miles across both states.||Loss of life during this historic event was staggering. Unfortunately, 321 people lost their lives making this the second deadliest tornado outbreak in U.S. history. The March 18, 1925 Tri-State tornado outbreak is first with 747 fatalities. This marks the first EF-5 tornado in Mississippi since the Candlestick Park tornado on May 3, 1966, and this marks the first time since statistics have been kept that two EF-5 tornadoes have been recorded on the same day in Mississippi, with the tornado in Smithville also rated as EF-5. Incredibly, 4 tornadoes had path lengths over 100 miles across the southern states during this event, and all 4 of these were rated either EF-4 or EF-5.",42
+314886,ST. CLAIR CO.,SANIE,04/27/2011,1732,Tornado, ,EF4,13,30,200000000,0,AL,CST-6, ,50455,C,115,BMX,0,0,NWS Storm Survey, ,28.85,1760,3,NW,1,ENE,HENRY LAKE,33.6839,-86.5234,33.8291,-86.0526,"This tornado initially touched down in eastern Jefferson County, north northeast of Trussville and moved northeast through portions of St. Clair, Calhoun, Etowah and Cherokee Counties. The tornado then moved into Georgia, across Polk, Floyd and Bartow (See Storm Data Peachtree City) Counties. The tornado crossed into St. Clair County near Argo where it caused mostly tree damage consistent with an EF1 rating as it tracked north of Margaret. The tornado began to strengthen as it neared US Hwy 411 where it caused minor roof damage to one home. The tornado crossed US Hwy 411 north of Odenville, taking a turn to the northeast, and then moved parallel to Shoal Creek. The tornado strengthened rapidly to an EF4 with winds of 170 mph, and caused extensive damage along Shoal Creek Rd, east of CR 26. At least 6 homes were destroyed, with only small interior rooms remaining. At least one home was swept clean from the foundation. Many mobile homes were also destroyed. In addition, tree damage was extensive in this area, with every tree left mangled. At least 14 fatalities occurred along Shoal Creek Rd. The path width increased to around 1 mile as the tornado approached Neely Henry Lake and the Calhoun County line. The tornado maintained a path along Shoal Creek Rd until it crossed the lake. ||This tornado was produced by a supercell thunderstorm that began in Newton County Mississippi at 13:54 pm CST, and dissipated in Macon County, North Carolina at approximately 21:18 pm CST. This supercell spawned several strong to violent tornadoes along its long path, including another violent EF4 tornado that crossed portions of Tuscaloosa and western suburbs of the Birmingham.","A powerful storm system crossed the Southeast United States on Wednesday, April 27, 2011, resulting in a large and deadly tornado outbreak.  This epic event broke the record for number of tornadoes in a day for the state of Alabama, becoming the most significant tornado outbreak in the state���s history. ||Central Alabama had two rounds of severe weather that day. During the early morning hours, a Quasi-Linear Convective System quickly moved across the northern half of the National Weather Service, Birmingham county warning area. Straight line winds of 90 mph (78kts) or greater and 11 tornadoes lead to widespread damage and power outages. During the afternoon, long-lived supercell thunderstorms produced long-track, strong and violent tornadoes. Destruction and loss of life across many towns and communities was devastating. ||The hardest hit areas included Shottsville and Hackleburg, both in Marion County, where winds of 160 mph and 210 mph respectively, caused unimagineable damage. Cordova, in Walker County, was hit twice; by a tornado along the Quasi-Linear Convective System during the early morning hours and again in the afternoon by a long-track EF4 tornado. A long track tornado moved across the city of Tuscaloosa and the western suburbs of Birmingham, resulting in the complete destruction of whole neighborhoods and numerous injuries and fatalities in those heavily populated areas. The same parent supercell produced another violent tornado in east Central Alabama as it tracked across St. Clair and Calhoun Counties, resulting in additional fatalities and incredible damage to a number of neighborhoods. Another violent EF4 tornado tracked across portions of Elmore and Tallapoosa Counties, including Lake Martin, destroying numerous homes and a large section of a mobile home park. ||Most of the violent tornadoes from this day were captured on video by a number of people, including storm spotters and chasers, as well as numerous television news crews and remotely controlled web-enabled video cameras.  This allowed unprecedented coverage and viewing of this historic event in real time from people worldwide.",43
+314900,CALHOUN CO.,MIDDLETON,04/27/2011,1804,Tornado, ,EF4,8,25,122000000,0,AL,CST-6, ,50455,C,15,BMX,0,0,NWS Storm Survey, ,17.62,1760,4,NNW,5,N,TREDEGAR,33.8291,-86.0526,33.9419,-85.7771,"This tornado initially touched down in eastern Jefferson County, north northeast of Trussville and moved northeast through portions of St. Clair, Calhoun, Etowah and Cherokee Counties, before it moved into Georgia, across Polk, Floyd and Bartow (See Storm Data Peachtree City) Counties. The tornado crossed Neely Henry Lake and into Calhoun County at Eagle Cove Rd., northwest of Ohatchee. At this point, the tornado had winds of 180 mph, an EF4 rating, and a path width of 1 mile. As the tornado crossed AL Hwy 77, numerous homes were leveled and mobile homes were demolished. Trees were left as stumps. Four fatalities occurred in this area. The tornado continued to cause extensive damage as it moved northeast crossing US Hwy 431 at Colwell and CR 23, where several homes and one church were destroyed. Four fatalities occurred in this area. As the tornado approached the Etowah County line, it weakened to an EF2 with winds of 120 mph, but continued to cause damage. Several homes were damaged and one mobile home destroyed along CR 64. The tornado moved into Etowah County east of Cannonball Rd. ||This tornado was produced by a supercell thunderstorm that began in Newton County Mississippi at 13:54 pm CST, and dissipated in Macon County, North Carolina at approximately 21:18 pm CST. This supercell spawned several strong to violent tornadoes along its long path, which included another violent EF4 tornado that crossed portions of Tuscaloosa and western suburbs of the Birmingham.","A powerful storm system crossed the Southeast United States on Wednesday, April 27, 2011, resulting in a large and deadly tornado outbreak.  This epic event broke the record for number of tornadoes in a day for the state of Alabama, becoming the most significant tornado outbreak in the state���s history. ||Central Alabama had two rounds of severe weather that day. During the early morning hours, a Quasi-Linear Convective System quickly moved across the northern half of the National Weather Service, Birmingham county warning area. Straight line winds of 90 mph (78kts) or greater and 11 tornadoes lead to widespread damage and power outages. During the afternoon, long-lived supercell thunderstorms produced long-track, strong and violent tornadoes. Destruction and loss of life across many towns and communities was devastating. ||The hardest hit areas included Shottsville and Hackleburg, both in Marion County, where winds of 160 mph and 210 mph respectively, caused unimagineable damage. Cordova, in Walker County, was hit twice; by a tornado along the Quasi-Linear Convective System during the early morning hours and again in the afternoon by a long-track EF4 tornado. A long track tornado moved across the city of Tuscaloosa and the western suburbs of Birmingham, resulting in the complete destruction of whole neighborhoods and numerous injuries and fatalities in those heavily populated areas. The same parent supercell produced another violent tornado in east Central Alabama as it tracked across St. Clair and Calhoun Counties, resulting in additional fatalities and incredible damage to a number of neighborhoods. Another violent EF4 tornado tracked across portions of Elmore and Tallapoosa Counties, including Lake Martin, destroying numerous homes and a large section of a mobile home park. ||Most of the violent tornadoes from this day were captured on video by a number of people, including storm spotters and chasers, as well as numerous television news crews and remotely controlled web-enabled video cameras.  This allowed unprecedented coverage and viewing of this historic event in real time from people worldwide.",44
+353666,MONROE CO.,CITICO BEACH,04/27/2011,1831,Tornado, ,EF4,0,0,50000,0,TN,EST-5, ,49915,C,123,MRX,0,0,NWS Storm Survey, ,1.7,1320,4,E,5,NNW,CALDERWOOD DAM,35.5324,-84.0504,35.5459,-84.0274,"A massive EF-4 tornado quickly spun up just west of Chilhowee Lake in northern Monroe County that scoured the forest in the Cherokee National Forest.  The tornado entered the Lake (at the Blount County line) and smashed a large steel transmission tower.  The tornado then entered the Great Smoky Mountains National Park on the other side of the lake and again began to rip through heavy forest.","Favorable atmospheric conditions resulted in a deadly tornado outbreak across east Tennessee on the 27th.  The thunderstorms produced more than 50 tornadoes across the east Tennessee area with 32 deaths and more than 200 injured.  The tornadoes produced from light to heavy damage to hundreds of homes and businesses.  Hail as large as baseballs was also reported.",45
+300456,BLOUNT CO.,CHILHOWEE,04/27/2011,1833,Tornado, ,EF4,0,0,1000000,0,TN,EST-5, ,49915,C,9,MRX,0,0,NWS Storm Survey, ,12.75,1320,1,SW,2,WNW,LAWSON XRDS,35.5459,-84.0274,35.6633,-83.846,"Chilhowee EF4 Tornado.  An NWS survey team reported an EF4 tornado touched down west of Chilhowee Lake in northern Monroe County. The max wind of 170 mph smashed a TVA transmission tower in the Lake, and ground up miles of forest in both Cherokee National Forest, then in Great Smoky Mountains National Park.   ||This tornado started in northern Monroe County in the Cherokee National Forest, then crossed Chilhowee Lake where it smash the tower, entering into Blount County. On the far shore of the lake (now in Blount County and also entering the Great Smoky Mountains National Park), it took a right turn at 33.5574/84.0061, traveled ENE deeper into the park, towards Cades Cove.  Before getting to Cades Cove it took a left turn near 35.5794/83.9878 and headed to the NE.  It finally dissipated about 4 miles north of Cades Cove, still in the Park.  Its total path was 14.5 miles long.","Favorable atmospheric conditions resulted in a deadly tornado outbreak across east Tennessee on the 27th.  The thunderstorms produced more than 50 tornadoes across the east Tennessee area with 32 deaths and more than 200 injured.  The tornadoes produced from light to heavy damage to hundreds of homes and businesses.  Hail as large as baseballs was also reported.",46
+300459,SEQUATCHIE CO.,DAUS,04/27/2011,1906,Tornado, ,EF4,0,0,250000,0,TN,CST-6, ,49915,C,153,MRX,0,0,NWS Storm Survey, ,7.86,880,1,NNE,3,ESE,MT AIRY,35.34,-85.42,35.41,-85.31,"New Harmony Tornado.  A NWS storm survey reported an EF2 tornado initially developed near Dunlap.  It tracked northeast across Sequatchie, Bledsoe and into Rhea County.  It had a path length of 7.9 miles in Sequatchie county and a 1/2 mile path width.  Numerous trees and powerlines were downed and a few homes suffered some damage. The tornado intensified to an EF4 in Bledsoe County.  While in Sequatchie County...the tornado initially started on a more northerly track then turned to almost straight northeast at about 35.377N/85.380W.","Favorable atmospheric conditions resulted in a deadly tornado outbreak across east Tennessee on the 27th.  The thunderstorms produced more than 50 tornadoes across the east Tennessee area with 32 deaths and more than 200 injured.  The tornadoes produced from light to heavy damage to hundreds of homes and businesses.  Hail as large as baseballs was also reported.",47
+300460,BLEDSOE CO.,HENDON,04/27/2011,1913,Tornado, ,EF4,4,10,15000000,0,TN,CST-6, ,49915,C,7,MRX,0,0,NWS Storm Survey, ,16.3,880,5,WSW,1,E,NEW HARMONY,35.3969,-85.3253,35.5535,-85.1077,"New Harmony Tornado.  A NWS storm survey reported a tornado path in Sequatchie county and continued its track northeast into and across southeastern Bledsoe County.  It had a path length of 16.3 miles in Bledsoe county and a 1/2 mile path width.  The 190 mph wind destroyed several homes up on Waldens Ridge, with continuous damage noted into Rhea county. Numerous trees and barns were also downed in the path of the large tornado. Vehicles were picked up and thrown.  ||Four people died in the Pitts Gap area just before the tornado reached New Harmony.  The fatalities included a married couple--a 43 year old woman and a 39 year old man in their mobile home.  A man, his wife (64 years old), and her sister (70 years old, visiting from Nashville) were in a camper, camping on Waldens Ridge when the tornado struck, killing the two sisters, and injuring the man.  Another 10 people were injured.","Favorable atmospheric conditions resulted in a deadly tornado outbreak across east Tennessee on the 27th.  The thunderstorms produced more than 50 tornadoes across the east Tennessee area with 32 deaths and more than 200 injured.  The tornadoes produced from light to heavy damage to hundreds of homes and businesses.  Hail as large as baseballs was also reported.",48
+305268,CATOOSA CO.,BLUE SPRING,04/27/2011,1915,Tornado, ,EF4,8,30,25000000,0,GA,EST-5, ,50924,C,47,FFC,0,0,NWS Storm Survey, ,10.7,586,2,E,4,NNE,POST OAK,34.8744,-85.1785,34.9868,-85.0485,"A survey conducted by the National Weather Service Forecast Office in Peachtree City, Georgia confirmed that an EF4 tornado, the first of this intensity to occur within the Peachtree City, Georgia county warning area (CWA), touched down in Catoosa county, just southwest of Ringgold along Davis Ridge Road.  The tornado tracked across Interstate-75 at mile marker 348 then continued on into and through the city of Ringgold before tracking northeast toward Cohutta and then into Hamilton and eventually Bradley county, Tennessee.  The tornado tracked nearly 12 miles through Catoosa county.  Major devastation was observed throughout the north side of the city of Ringgold.  The worst damage occurred on Cherokee Valley Road on the north side of Ringgold where 12 homes were obliterated.  An additional 80 to 90 homes sustained major damage from the tornado.  In addition, several commercial businesses, including restaurants and motels, at exit 348 on Interstate-75 were destroyed.  There were eight fatalities and 30 injuries reported with this tornado.  Seven of the eight deaths occurred on Cherokee Valley Road, which was heavily devastated by the tornado.  Most of the tornado victims lived within 200 yards of each other and were killed when their homes collapsed around them.  Finally, hundreds of trees and dozens of power lines and utility poles were also destroyed by the tornado.  This was by far the deadliest and most devastating of the 15 tornadoes to affect north and central Georgia during this tornado outbreak.||Total damages from Catoosa county consist of 74 destroyed homes and/or businesses, 60 with major damage, and 118 with minor damage for a total of 252 affected structures.||[04/27-04/28/11: Tornado #4, County #1-1, EF4, Catoosa, 2011:013].","A highly diffluent, deep upper trough, centered across Texas, took on a negative tilt and began to rotate northeast during this period.  A strong maritime-Pacific (mP) cold front accompanied the upper trough through the mid-south into the southeast from the early morning hours of the 27th to the early morning hours of the 28th.  An intense low-level jet with winds in excess of 70 knots was noted in advance of this system and tracked across the mid-south early on the 27th, across north Alabama and north Georgia into the early morning hours of the 28th.  West-southwest winds aloft were highly diffluent and near 200 mph across this same region.  The strong low-level jet brought unseasonably, warm, moist Gulf air northward in advance of the mP cold front.  Dewpoints in the 70s and maximum temperatures in the 80s combined with the extremely strong low-level and upper jets to create an almost perfect environment for severe thunderstorms and large devastating tornadoes.  Indeed, the tornado outbreak that affected much of the eastern U.S., but particularly the south central and southeastern U.S. during this period, was unprecedented and likely the largest recorded in U.S. history.  The tornado outbreak that accompanied this combination of weather features has been termed the 2011 Super Outbreak, an outbreak even worse than the 1994 and 1974 super tornado outbreaks across the eastern U.S.  The outbreak affected the South Central, Southeast, Midwest, and even the usually less tornado prone Northeastern United States.  Over 330 tornadoes were reported during this outbreak which began on April 25th and continued into the 28th affecting 21 states from Texas to New York.  Even isolated tornadoes were noted in Canada.  Nearly 350 people died from these tornadoes, of which over 230 of these were in Alabama alone.  Four tornadoes on April 27th in Alabama and Mississippi were ranked EF5, the highest tornado damage rating on the Enhanced Fujita Scale.  On average, there is only one EF5 tornado per year in the entire U.S.||Widespread and destructive tornadoes occurred on each day of the outbreak, but April 27th was clearly one of the most prolific and destructive tornado days in U.S. history, probably only surpassed by the Tri-State outbreak of 1925 and the Tupelo-Gainesville outbreak of 1936.  The 24-hour period from 8 am April 27th to 8 a.m. April 28th is listed by the National Oceanic and Atmospheric Administration (NOAA) as the fourth deadliest tornado outbreak in U.S. history, with the 24 hours commencing April 28th at 8 a.m. as the fifth deadliest tornado day in U.S. history.  It has also been determined to be the costliest tornado outbreaks and one of the costliest natural disasters in the U.S., even after adjustments for inflation, with total damages estimated to exceed $10 billion. ||Georgia was heavily impacted by this tornado outbreak, especially the northwest part of the state which bore the brunt of the massive supercell thunderstorms producing killer tornadoes that tracked east-northeast from northern Alabama during the late evening.  All together, there were 15 tornadoes affecting 28 counties within the Peachtree City, Georgia 96-county warning area (CWA) of North and Central Georgia.  All of these occurred within a 24-hour period commencing at 8 am April 27th.  One of these tornadoes was rated an EF4, the first EF4 tornado in Georgia since the Palm Sunday outbreak in 1994.  In addition, there were also four EF3 tornadoes.  Fifteen tornado-related deaths were observed in north and central Georgia, the most tornado-related deaths within the Peachtree City, Georgia forecast area since its inception in 1994.  The previous highest tornado-related death total was 12 on March 20, 1998, when a tornado struck Gainesville, Georgia.||Finally, it should be noted that while the most significant period of severe weather during this outbreak for Georgia was from the afternoon of the 27th through the early morning hours of the 28th, there was an initial round of severe weather across northwest Georgia early on the 27th as a decaying line of severe thunderstorms moved into the region from northeast Alabama.  Widespread wind damage and even a few brief weaker tornadoes accompanied this system into the northwest counties of the state.",49
+296789,HAMILTON CO.,APISON,04/27/2011,1927,Tornado, ,EF4,8,100,20000000,0,TN,EST-5, ,49915,C,65,MRX,0,0,NWS Employee, ,4.9,800,3,SW,2,ESE,COLLEGEDALE ARPK,34.9868,-85.0485,35.0371,-84.9875,"Ringgold-Apison Tornado.  An EF4 tornado touched down in north Georgia and continued into southeast Hamilton county, just south of Apison, Tennessee. It tracked northeast across SE Hamilton County before moving across Bradley County and into Polk County.  It had a path length of 4.9 mile path length in Hamilton county and a path width of 800 yards.  The 190 mph wind completely leveled several homes and an additional 150 homes were damaged. Eight fatalities were attributed directly to the tornado along with 100 injuries.  Victims from Apison include a 77 year old grandmother along with her 17 year old grandson as well the 56 year old mother and 31 year old male cousin who died in their home.  In addition, a 63 year old man along with his 60 wife died in their home.  Also, a 70 year old man died with his 62 year old wife died in their home.","Favorable atmospheric conditions resulted in a deadly tornado outbreak across east Tennessee on the 27th.  The thunderstorms produced more than 50 tornadoes across the east Tennessee area with 32 deaths and more than 200 injured.  The tornadoes produced from light to heavy damage to hundreds of homes and businesses.  Hail as large as baseballs was also reported.",50
+300457,BRADLEY CO.,PINE HILL,04/27/2011,1934,Tornado, ,EF4,4,200,23000000,0,TN,EST-5, ,49915,C,11,MRX,0,0,NWS Storm Survey, ,20.4,800,2,SSE,4,E,HAUN MILL,35.0371,-84.9875,35.218,-84.703,"Ringgold-Apison Tornado.  This tornado touched down in north Georgia and tracked northeast into Hamilton County, Tennessee, and then into Bradley County. In Bradley County, the max intensity still caused EF4 damage with the max wind extimated at 170 mph and did extensive damage to many homes and businesses. An additional 4 people were killed by the tornado in Bradley County in the Blue Springs Community. The fatalities included a 42 year old women from Wisconsin visiting her son in the Blue Springs community as well as the 3 month old boy in the same house she was trying to protect.  In addition, a 40 year old women died in her home.  Also, a 67 year old woman died in her home.","Favorable atmospheric conditions resulted in a deadly tornado outbreak across east Tennessee on the 27th.  The thunderstorms produced more than 50 tornadoes across the east Tennessee area with 32 deaths and more than 200 injured.  The tornadoes produced from light to heavy damage to hundreds of homes and businesses.  Hail as large as baseballs was also reported.",51
+315334,TALLAPOOSA CO.,BARNESVILLE,04/27/2011,1936,Tornado, ,EF4,1,10,115000000,0,AL,CST-6, ,50455,C,123,BMX,0,0,NWS Storm Survey, ,19.03,880,6,NW,2,S,DUDLEYVILLE,32.7545,-85.8826,32.8843,-85.5936,"A tornado touched down in central Elmore County, north of Wetumpka, and moved northeast through central Tallapoosa and western Chambers Counties, before it lifted west northwest of Lafayette. The tornado crossed into Tallapoosa County near Stoney Ridge Rd, south of CR 34, and intensified to EF4 strength with winds of 170 mph. Damage was widespread and severe with several well built multi-story homes destroyed with no walls remaining on floors above basement level. The tornado continued at this strength but became narrower to nearly 400 yards wide as it crossed AL Hwy 49 south of Dadeville where it destroyed 2 homes and rolled a pick-up truck 120 yards. The tornado continued northeast and weakened to EF3 strength with winds of 155 mph. It crossed U.S. Hwy 280 just east of Dadeville where it produced significant damage to several homes and businesses, and caused one fatality. The tornado crossed into Chambers County west of Lafayette, south of CR 48.","A powerful storm system crossed the Southeast United States on Wednesday, April 27, 2011, resulting in a large and deadly tornado outbreak.  This epic event broke the record for number of tornadoes in a day for the state of Alabama, becoming the most significant tornado outbreak in the state���s history. ||Central Alabama had two rounds of severe weather that day. During the early morning hours, a Quasi-Linear Convective System quickly moved across the northern half of the National Weather Service, Birmingham county warning area. Straight line winds of 90 mph (78kts) or greater and 11 tornadoes lead to widespread damage and power outages. During the afternoon, long-lived supercell thunderstorms produced long-track, strong and violent tornadoes. Destruction and loss of life across many towns and communities was devastating. ||The hardest hit areas included Shottsville and Hackleburg, both in Marion County, where winds of 160 mph and 210 mph respectively, caused unimagineable damage. Cordova, in Walker County, was hit twice; by a tornado along the Quasi-Linear Convective System during the early morning hours and again in the afternoon by a long-track EF4 tornado. A long track tornado moved across the city of Tuscaloosa and the western suburbs of Birmingham, resulting in the complete destruction of whole neighborhoods and numerous injuries and fatalities in those heavily populated areas. The same parent supercell produced another violent tornado in east Central Alabama as it tracked across St. Clair and Calhoun Counties, resulting in additional fatalities and incredible damage to a number of neighborhoods. Another violent EF4 tornado tracked across portions of Elmore and Tallapoosa Counties, including Lake Martin, destroying numerous homes and a large section of a mobile home park. ||Most of the violent tornadoes from this day were captured on video by a number of people, including storm spotters and chasers, as well as numerous television news crews and remotely controlled web-enabled video cameras.  This allowed unprecedented coverage and viewing of this historic event in real time from people worldwide.",52
+300461,RHEA CO.,MORGAN SPGS,04/27/2011,2026,Tornado, ,EF4,0,2,2000000,0,TN,EST-5, ,49915,C,143,MRX,0,0,NWS Storm Survey, ,16,880,1,SSW,1,S,SPRING CITY,35.5535,-85.1077,35.68,-84.87,"New Harmony Tornado.  This tornado continued its destuctive path into Rhea County.  The 190 mph wind destroyed 19 roofs and 21 homes had damage. Trees and powerlines were also downed. Two people were injured.||This tornado had a total path length of 40.2 miles and was responsible for four deaths in Bledsoe County.","Favorable atmospheric conditions resulted in a deadly tornado outbreak across east Tennessee on the 27th.  The thunderstorms produced more than 50 tornadoes across the east Tennessee area with 32 deaths and more than 200 injured.  The tornadoes produced from light to heavy damage to hundreds of homes and businesses.  Hail as large as baseballs was also reported.",53
+296617,JASPER CO.,CENTRAL CITY,05/22/2011,1640,Tornado, ,EF5,158,1150,2800000000,0,MO,CST-6, ,49972,C,97,SGF,0,3,NWS Storm Survey, ,8.8,1600,2,SE,2,SSE,DUENWEG,37.056,-94.5701,37.0544,-94.4105,"National Weather Service survey teams rated the tornado that tracked across the southwest through east central portion of Joplin, Missouri, as an EF5 tornado.  Maximum winds were estimated to have exceeded 200 miles per hour. The tornado had a maximum width of one mile and an overall path length of nearly 21.6 miles, nearly nine miles of which occurred in Jasper County.||The tornado killed 158 directly, three indirectly, and injured over 1150 people.  Sadly, on May 24 a police officer who was volunteering from another department, was struck by lightning while serving in the response efforts and later died.  Equally, a 56 year old man who had been included as a direct fatality was later determined to have died of a heart attack.  Over 10,200 people filed for disaster assistance following the tornado.||The EF-5 rating (greater than 200 mph wind speeds) was mainly arrived at by the total destruction of vehicles, including some vehicles tossed several blocks and semi trucks thrown a quarter of a mile. Parking stops weighing over 300 pounds and re-barred into asphalt were uprooted and tossed.  Other factors in the rating included damage to reinforced concrete structures, and that St. John���s Hospital building structure was compromised.  ||Seven thousand homes were severely damaged or destroyed and another 900 damaged.  Other substantial buildings damaged or destroyed included the Joplin High School and Technical Center along with five other city schools.  Numerous retailers including Home Depot, Sports Academy, Dillons, and Walmart were also destroyed.  The most substantial building impacted was St John's hospital which will be razed due to the tornado.  It was calculated that 2 million cubic yards of debris is attributable to the storm across its relatively short length on the ground.||The tornado initially touched down one half mile southwest of the intersection of JJ Highway and Newton Road in Newton County where several large trees were toppled. ||The tornado rapidly intensified as it moved toward the intersection of Country Club Drive and 32nd Street where it crossed into Jasper County. Damage became more widespread as the tornado crossed Maiden Lane, breaking nearly all windows on three sides of St. Johns Hospital as well as damage to the roof and exterior walls on several floors.  Two patients on oxygen were indirectly suffocated when the generator and a backup generator were damaged after power was cut off.  Three additional patients may have succumbed similarly though sufficient data as to the cause of death was not available.  An additional indirect fatality occurred due to psychological trauma.||The tornado further intensified as it destroyed homes and businesses to the immediate east and north of the hospital. A church school was completely destroyed with the exception of a portion of the sanctuary.  Significant damage to the Greenbriar Nursing Home resulted in the death of 20 mostly elderly patients.  ||The tornado continued to destroy hundreds of frame homes between 32nd and 20th Streets, leading to nearly a fifth of the deaths. Three story apartment complexes had the top two floors removed; other two story complexes were partially leveled. Fourteen deaths occurred in apartments along the track.  Eleven additional deaths occurred in churches along this path.  There were two fatalities in a mobile home (Joplin has a city ordinance prohibiting mobile home parks). ||Well built structures that were heavily damaged or destroyed along this area included the Joplin High School, Franklin Technical Center and Irving Elementary, all of which were free of students due to the weekend.  The tornado also damaged three additional elementary schools.  A bank was totally destroyed with the exception of the vault. A large grocery store was also destroyed.  ||The tornado crossed Rangeline Road near 20th Street. Damage included significant to complete damage to several restaurants and large long-span retail buildings; including Home Depot, Sports Academy and Walmart in this area.  Twenty deaths occurred indoors or in the parking lots of these structures.  Semi trucks on the back side of Walmart were thrown more than a quarter mile.||The tornado continued to move eastward along and south of 20th Street destroying numerous warehouse style facilities, a portion of Joplin East Middle School, and residences through Duquesne Road.||The tornado continued destroying numerous homes as it began weakening. It turned southeast toward Interstate 44 where it threw several semi trucks as it crossed the interstate and moved into Newton County at 32nd Street just west of Kodiak Road.","A strong upper level trough across the central plains region and a strong upper level disturbance along with a frontal boundary in the area produced numerous severe storms with a few supercells across southeast Kansas. One cyclic supercell associated with the system produced a very large and deadly EF-5 tornado that hit the city of Joplin and then spawned two separate tornadoes that moved across southwestern Missouri. A separate tornadic supercell produced an EF-3 tornado that moved into McDonald County from Northeastern Oklahoma. ||Continuing thunderstorms lasted into May 23 as another line of thunderstorms moved across the region. This line of storms produced reports of large hail, damaging winds and a weak EF-0 tornado in south central Missouri. As the storms moved over the Joplin area, two police officers were struck by lightning while aiding in the post tornado efforts. One of the two officers later died of injuries from the lightning strike.",54
+315837,CANADIAN CO.,CALUMET,05/24/2011,1450,Tornado, ,EF5,7,112,0,0,OK,CST-6, ,52830,C,17,OUN,0,0,NWS Storm Survey, ,39.6,1760,14,SW,7,NNE,PIEDMONT,35.444,-98.287,35.725,-97.697,"This tornado is labeled Tornado B2 (Segment #1 of the Calumet-El Reno-Piedmont-Guthrie tornado). This tornado began very close to the Caddo/Canadian county border and quickly became a strong/violent tornado. The tornado destroyed numerous trees, many of them were debarked, before crossing Interstate 40. Three people died in vehicles near the I-40 Calumet exit, and two other fatalities occurred just northeast of that location. Cars were thrown thousands of feet off the roadways. It is believed that the tornado reached its maximum intensity just after crossing I-40, and it was here that a mobile radar measured winds of greater than 210 mph just off the surface. The El Reno Oklahoma Mesonet station (5 miles west) measured wind gusts of 131 and 151 mph. From this location, the tornado continued northeast, narrowly missing the town of Piedmont. Widespread EF-3, occasional EF-4 damage occurred between El Reno and Piedmont. More widespread EF-4 damage was seen west and north of Piedmont. Especially hard hit was the Falcon Lake neighborhood, near the Kingfisher county border. Two children were killed at this location. The tornado continued into southeastern Kingfisher County. Monetary damage estimates were not available at this time, but were probably going to be well in the tens of millions.","A tornado outbreak occurred over parts of northern and central Oklahoma during the day on the 24th, with violent tornadoes devastating several communities. By the end of the day, one EF-5, two EF-4, and two EF-3 tornadoes destroyed buildings, ripped up trees and power poles, and unfortunately, resulted in 11 deaths. The day began with a strong upper level trough ejecting out of the southwest United States. The trough took on a negative tilt as it approached the southern Plains. A strong jet stream was located at both the middle and upper levels rotating around the upper trough. At the surface, a low pressure strengthened rapidly over northwest Oklahoma, keeping the low-level flow of warm, moist air to flow east of a dry line that had moved into western Oklahoma. Thunderstorms developed by early afternoon over western Oklahoma, and quickly became supercellular as they moved northeast. Strong low-level rotation developed early, with the first tornado occurring over Blaine county, and moved northeast into Major county. Another supercell rapidly gained low-level rotation as it moved from Caddo into Canadian County. This tornado became the strongest of them all as it moved north of El Reno, west of Piedmont, and to south of Guthrie in Logan county. Nine people died as a result of this tornado. Two more powerful supercells developed over Grady county, and they moved northeast into McClain and Cleveland counties. Finally, the final tornado occurred east of Norman into Pottawatomie county. The timing of this outbreak could not have come at a worse time, as rush hour was just unfolding as the tornadoes neared the Oklahoma City metro area.",55
+315858,GRADY CO.,NORGE,05/24/2011,1606,Tornado, ,EF4,1,48,0,0,OK,CST-6, ,52830,C,51,OUN,0,0,NWS Storm Survey, ,21,880,3,ENE,4,SE,BRIDGE CREEK,35.008,-97.961,35.189,-97.67,"This tornado is labeled C1 (Segment #1 of the Chickasha-Blanchard-Newcastle tornado). The tornado formed on the south side of Chickasha, quickly doing EF-2 damage. Mobile homes were damaged and destroyed, trees were uprooted/destroyed, outbuildings were destroyed, and many buildings lost significant portions of their roofs. One fatality occurred as a mobile home was destroyed in the south portion of Chickasha. As the tornado moved northeast of Chickasha, it gained significant strength, with several areas receiving EF-4 damage. Well-built homes were destroyed. Trees were debarked with only stumps remaining. Cars were thrown hundreds of feet. Almost continuous EF-3/occasional EF-4 damage occurred northeast until it crossed into McClain county 1.5 miles south of Highway 9. The tornado was probably at its strongest as it neared/crossed the McClain county line. Wind speeds there were estimated near 200 mph. Monetary damage estimates were not available.","A tornado outbreak occurred over parts of northern and central Oklahoma during the day on the 24th, with violent tornadoes devastating several communities. By the end of the day, one EF-5, two EF-4, and two EF-3 tornadoes destroyed buildings, ripped up trees and power poles, and unfortunately, resulted in 11 deaths. The day began with a strong upper level trough ejecting out of the southwest United States. The trough took on a negative tilt as it approached the southern Plains. A strong jet stream was located at both the middle and upper levels rotating around the upper trough. At the surface, a low pressure strengthened rapidly over northwest Oklahoma, keeping the low-level flow of warm, moist air to flow east of a dry line that had moved into western Oklahoma. Thunderstorms developed by early afternoon over western Oklahoma, and quickly became supercellular as they moved northeast. Strong low-level rotation developed early, with the first tornado occurring over Blaine county, and moved northeast into Major county. Another supercell rapidly gained low-level rotation as it moved from Caddo into Canadian County. This tornado became the strongest of them all as it moved north of El Reno, west of Piedmont, and to south of Guthrie in Logan county. Nine people died as a result of this tornado. Two more powerful supercells developed over Grady county, and they moved northeast into McClain and Cleveland counties. Finally, the final tornado occurred east of Norman into Pottawatomie county. The timing of this outbreak could not have come at a worse time, as rush hour was just unfolding as the tornadoes neared the Oklahoma City metro area.",56
+315875,MCCLAIN CO.,CRINER,05/24/2011,1635,Tornado, ,EF4,0,61,0,0,OK,CST-6, ,52830,C,87,OUN,0,0,NWS Storm Survey, ,17.6,880,7,WSW,1,SW,GOLDSBY,34.939,-97.67,35.141,-97.491,"This tornado is labeled D1 (Segment #2 of the Washington-Goldsby tornado). Widespread tree damage and ground scouring was ongoing as the tornado crossed into McClain county. As the tornado crossed Highway 76, even more intense damage occurred. EF-4 damage was surveyed at several locations. Several homes were reduced to a pile of rubble, or were wiped clean off of their foundations. Automobiles were mangled and almost unrecognizable. The tornado weakened and narrowed as it crossed CR 410. Even though the tornado had weakened, EF-2 to EF-3 damage was still occurring as it approached Highway 39. The tornado increased in intensity once again near the Highway, with EF-4 damage surveyed for the 2nd time. Well constructed homes were destroyed, with several wiped clean off of their foundations. This also began a longer streak of higher end damage, with EF-3 to EF-4 damage occurring until it crossed Highway 74B, west of High Avenue. Equally devastating destruction occurred over the areas of EF-4 damage. The tornado lifted west of Goldsby with still EF-3 damage occurring prior to lifting. It should be noted that this tornado had estimated winds up to 200 mph at times, falling just short of the damage indicator for an EF-5 tornado. Monetary damage estimates were not available.","A tornado outbreak occurred over parts of northern and central Oklahoma during the day on the 24th, with violent tornadoes devastating several communities. By the end of the day, one EF-5, two EF-4, and two EF-3 tornadoes destroyed buildings, ripped up trees and power poles, and unfortunately, resulted in 11 deaths. The day began with a strong upper level trough ejecting out of the southwest United States. The trough took on a negative tilt as it approached the southern Plains. A strong jet stream was located at both the middle and upper levels rotating around the upper trough. At the surface, a low pressure strengthened rapidly over northwest Oklahoma, keeping the low-level flow of warm, moist air to flow east of a dry line that had moved into western Oklahoma. Thunderstorms developed by early afternoon over western Oklahoma, and quickly became supercellular as they moved northeast. Strong low-level rotation developed early, with the first tornado occurring over Blaine county, and moved northeast into Major county. Another supercell rapidly gained low-level rotation as it moved from Caddo into Canadian County. This tornado became the strongest of them all as it moved north of El Reno, west of Piedmont, and to south of Guthrie in Logan county. Nine people died as a result of this tornado. Two more powerful supercells developed over Grady county, and they moved northeast into McClain and Cleveland counties. Finally, the final tornado occurred east of Norman into Pottawatomie county. The timing of this outbreak could not have come at a worse time, as rush hour was just unfolding as the tornadoes neared the Oklahoma City metro area.",57
+315859,MCCLAIN CO.,BLANCHARD,05/24/2011,1638,Tornado, ,EF4,0,0,0,0,OK,CST-6, ,52830,C,87,OUN,0,0,NWS Storm Survey, ,9.6,650,3,N,4,N,NEWCASTLE,35.189,-97.67,35.305,-97.589,"This tornado is labeled C1 (Segment #2 of the Chickasha-Blanchard-Newcastle tornado). Significant damage continued as the violent tornado moved over the McClain county border. This may have been the strongest portion of this tornado, with wind speeds near 200 mph. Well-built homes were destroyed, with some cleaned off of their foundation. A concrete dome home was severely damage, mainly by the flying debris. Trees were debarked or destroyed. Very little was left standing for the first few miles into McClain county. Fairly consistent EF-3, with brief periods of EF-4 damage occurred as the tornado neared/crossed Highway 9, near the Highway 76 junction. The tornado began to weaken as it moved toward the Cleveland county border, with mainly trees and power poles/lines snapped. The tornado continued into Cleveland County. Monetary damage estimates were not available.","A tornado outbreak occurred over parts of northern and central Oklahoma during the day on the 24th, with violent tornadoes devastating several communities. By the end of the day, one EF-5, two EF-4, and two EF-3 tornadoes destroyed buildings, ripped up trees and power poles, and unfortunately, resulted in 11 deaths. The day began with a strong upper level trough ejecting out of the southwest United States. The trough took on a negative tilt as it approached the southern Plains. A strong jet stream was located at both the middle and upper levels rotating around the upper trough. At the surface, a low pressure strengthened rapidly over northwest Oklahoma, keeping the low-level flow of warm, moist air to flow east of a dry line that had moved into western Oklahoma. Thunderstorms developed by early afternoon over western Oklahoma, and quickly became supercellular as they moved northeast. Strong low-level rotation developed early, with the first tornado occurring over Blaine county, and moved northeast into Major county. Another supercell rapidly gained low-level rotation as it moved from Caddo into Canadian County. This tornado became the strongest of them all as it moved north of El Reno, west of Piedmont, and to south of Guthrie in Logan county. Nine people died as a result of this tornado. Two more powerful supercells developed over Grady county, and they moved northeast into McClain and Cleveland counties. Finally, the final tornado occurred east of Norman into Pottawatomie county. The timing of this outbreak could not have come at a worse time, as rush hour was just unfolding as the tornadoes neared the Oklahoma City metro area.",58
+313004,FRANKLIN CO.,PETER PENDER,05/24/2011,2257,Tornado, ,EF4,1,6,1500000,0,AR,CST-6, ,51969,C,47,TSA,0,0,NWS Storm Survey, ,7.8,2200,3,SSE,0,W,DENNING,35.3182,-93.9044,35.399,-93.8079,"This is the third of six segments of this tornado. The tornado snapped or uprooted a number of large trees as it moved back into Franklin County from Logan County. The damage path widened considerably to about 3/4 of a mile as the tornado moved north of Highway 398 and approached Etna. In and near Etna, the tornado destroyed a number of permanent homes, destroyed mobile homes, destroyed a metal building, destroyed a number of outbuildings, snapped numerous power poles, and snapped or uprooted many large trees. One of the three tornado-related fatalities in Franklin County occurred when a double-wide mobile home was destroyed in Etna. At least six serious injuries occurred in this area and several of those were critical.||Several well-built, wood-framed permanent homes were destroyed in Etna with only a small amount of debris remaining on the foundation. Trees were debarked in this area and the ground was scoured by debris. A well-built, two-story, steel-framed home northeast of Etna on Highway 309 was also destroyed with only a few interior walls remaining on the first floor. Two people survived in the kitchen pantry as the home was destroyed around them. Maximum estimated wind speed in this segment of the tornado based on this damage was about 170 mph.||The tornado continued into Logan County, Arkansas, at 1.25 miles wide.","Severe thunderstorms developed along a dry line over central Oklahoma during the afternoon hours. Very unstable air and strong wind shear east of the dry line supported supercell thunderstorm structures, which persisted as the storms moved into northwestern Arkansas late in the evening. These severe storms produced tornadoes, large hail, and damaging downburst wind across portions of northwestern Arkansas. One of the tornadoes was especially intense, resulting in considerable damage to several towns as well as three fatalities in Franklin County.",59
+353589,TILLMAN CO.,TIPTON ARPT,11/07/2011,1443,Tornado, ,EF4,0,0,0,0,OK,CST-6, ,58317,C,141,OUN,0,0,NWS Storm Survey, ,15,500,7,S,3,NNE,TIPTON,34.357,-99.194,34.542,-99.115,"This violent tornado continued northeast into Tillman county about 9 miles SSW of Tipton. The most severe damage occurred at the Oklahoma State University Agronomy Research Station. The buildings at the site were demolished, with most of the debris thrown into the nearby fields. The trees surrounding the site were debarked and splintered. Other damage was to the Tipton Mesonet site that took a direct hit. The wind speed maxed out at 86.4 mph before the site was demolished by flying debris. The tornado lifted about 3 miles NNE of Tipton.","A powerful storm system moving through the southern Great Plains produced tornadoes, large hail, damaging winds and flooding across parts of Oklahoma and western north Texas on November 7-8, 2011.||The strong storm system generated severe weather including tornadoes, large hail, damaging winds and flooding from the early afternoon of November 7th through the early morning of November 8th. Several supercell thunderstorms developed over southwest Oklahoma during the mid-afternoon hours and moved northeast. One particularly nasty supercell thunderstorm developed over northern Wilbarger county in north Texas. This thunderstorm moved northeast into Tillman county, eventually producing at least eight tornadoes over a five county area. Two of the tornadoes moved near two Oklahoma Mesonet sites, both taking direct hits. The Mesonet site at Tipton measured 86.4 mph before it was destroyed. The Mesonet site near Fort Cobb measured 91.4 mph before it was destroyed. Both sites also recorded significant drops in surface pressure. Other supercells over southwest Oklahoma eventually congealed into a complex of storms and moved east into central Oklahoma. Numerous reports of high winds (92 mph near Clinton, OK) and hail up to golf ball-size were reported. The severe threat transitioned to a heavy rain and high threat after sunset.",60
+359691,SALINE CO.,CARRIERS MILLS,02/29/2012,451,Tornado, ,EF4,8,95,2000000,0,IL,CST-6, ,60247,C,165,PAH,0,0,NWS Storm Survey, ,15.93,325,1,N,1,E,BROOKLYN,37.6945,-88.65,37.771,-88.3751,"The tornado touched down about a mile north of Carrier Mills, then moved east-northeast through Harrisburg. The violent tornado produced a swath of devastation in south and southeast parts of Harrisburg. In Harrisburg, over 200 homes and about 25 businesses were heavily damaged or destroyed. The damage was in residential neighborhoods in the far south and southeast sections of Harrisburg. The commercial strip along U.S. Highway 45 in the south part of the city was directly impacted. A strip mall on the east side of U.S. Route 45 was destroyed. The tornado struck the Harrisburg medical center and surrounding residences on the southeast side of town. At least ten homes or other buildings were levelled, with several home structures displaced from their foundations. The neighborhood with the levelled homes and fatalities was adjacent to the destroyed strip mall. The tornado proceeded across Illinois Route 13 a few miles east of Harrisburg, destroying a farm house and a business. Hundreds of large trees were snapped or uprooted, along with many downed power lines. Peak winds were estimated near 180 mph based on numerous levelled and displaced homes. The average path width was 275 yards. The tornado continued into Gallatin County shortly after crossing Highway 142.","A squall line with embedded sustained supercells crossed southern Illinois. The embedded supercells raced east-northeast at 60 to 70 mph, while the line moved southeast at a slower rate. The storms strengthened as they encountered richer low-level moisture, with surface dew points around 60 degrees spreading rapidly north-northeastward up the Mississippi Valley. Intense low to mid-level wind fields maintained the intensity of tornadic storms despite weak instability due to lack of solar heating. A south-southwesterly low level jet from 60 to 70 knots veered to west-southwest around 75 knots at 500 mb.",61
+359697,GALLATIN CO.,EQUALITY,02/29/2012,504,Tornado, ,EF4,0,13,1000000,0,IL,CST-6, ,60247,C,59,PAH,0,0,NWS Storm Survey, ,10.16,300,4,NW,2,SSW,INMAN,37.771,-88.3751,37.7996,-88.1926,"The tornado crossed into Gallatin County from Saline County in the vicinity of Illinois Highway 142. The tornado moved east-northeast through very sparsely populated farm country before striking Ridgway directly. In Ridgway, the tornado damaged about 140 homes and businesses, causing one critical injury and about a dozen relatively minor injuries. Numerous cars were tossed around, mainly on the east side of Ridgway. A large historic church was completely destroyed. Hundreds of large trees were snapped or uprooted, along with many power lines down. A half dozen grain bins were destroyed. The tornado lifted about 4 miles east-northeast of Ridgway. The average path width was 275 yards. Peak winds were estimated near 180 mph.","A squall line with embedded sustained supercells crossed southern Illinois. The embedded supercells raced east-northeast at 60 to 70 mph, while the line moved southeast at a slower rate. The storms strengthened as they encountered richer low-level moisture, with surface dew points around 60 degrees spreading rapidly north-northeastward up the Mississippi Valley. Intense low to mid-level wind fields maintained the intensity of tornadic storms despite weak instability due to lack of solar heating. A south-southwesterly low level jet from 60 to 70 knots veered to west-southwest around 75 knots at 500 mb.",62
+359896,WASHINGTON CO.,FREDDRICKSBURG,03/02/2012,1450,Tornado, ,EF4,5,0,2000000,0,IN,EST-5, ,60205,C,175,LMK,0,0,NWS Storm Survey, ,17.35,800,1,WNW,3,ENE,DAISY HILL,38.4316,-86.1893,38.5103,-85.8848,"This EF-4 tornado that ultimately stayed on the ground for 49 miles across several counties touched down just south of Fredricksburg.  Several trees were snapped off with estimated EF-1 damage along a path of 30 yards wide along the south fork of the Blue Lick River.  After crossing farmland, the tornado widened and intensified quickly, toppling a high tension metal power structure near the intersection of Homers Chapel and Fredricksburg Roads. Damage at that location was consistent with 130 mph winds.  ||High tension wires were downed and trees snapped along West End Road just north of Shanks Hill Road.  The tornado continued to intensify as it crossed State Route 135 at Dutch Creek Road, ripping large chunks of 3 inch thick asphalt from a section of roadway and depositing large pieces up to 30 yards away, with smaller chunks of pavement found a quarter of a mile downstream.  Just east of State Route 135, tremendous tree damage began. At this point, the tornado widened to around 200 yards. As the tornado crossed Trainer Lane and Route 335 towards Robbs Lane, widespread tree and structural damage indicated EF-2 to EF-3 damage. At this point, the damage path began to widen to one third of a mile. ||After crossing Highway 60 just south of New Pekin, tremendous structural damage was surveyed. A large well-constructed factory building was cleared to its foundation slab with numerous anchoring bolts bent and stripped. Debris from this building was observed up to three quarters of a mile downstream. Large power poles were snapped. Another metal out building on the edge of the circulation had sheeting pulled off, apparently from the force of inbound winds towards the circulation. In this area 5 people were killed in a mobile home. Damage suggested an EF-4 tornado with a width of three to four tenths of a mile and estimated winds of 170 mph. ||The tornado then traveled along the border between Washington and Crawford counties where it caused widespread destruction southeast of Hurst and along East Daisy Hill Road in the county.  Here, a well constructed one story brick home at the top of a ridge was completely destroyed with no wall left standing. Witnesses described the funnel as a black wall. A heavy semi trailer cab was blown from this house and landed near another destroyed brick home. Damage to these homes suggested EF-4 winds of 170 mph. Near the intersection of East Daisy Hill and Williams Knob Roads, a home and two anchored double wide trailers were destroyed. A car was lifted and fell 100 yards away from its original driveway. The width of the damage path along the county line was up to one half mile, although the concentrated damage path was much more narrow. Overall, the twister traveled 17 miles in Washington county, felling thousands of trees in addition to destroying scores of buildings.","A surface Low over Missouri early in the afternoon of March 2nd strengthened to below 990mb as it moved north into Michigan by the evening hours. Around dawn, a warm front moved north of the Ohio River, accompanied by scattered elevated thunderstorms that produced small hail. During the early afternoon, temperatures rose into the lower 70s across southern Indiana. the combination of extreme wind shear and CAPE near 2000 Joules/kg brought several long lived supercells to the state near the Ohio River. These storms produced baseball-sized hail and several tornadoes, including a violent long-tracker, to southern Indiana. The tornadoes across the area were a part of a well forecast regional outbreak that affected the entire Lower Ohio and Tennessee Valleys. Overall, more than 80 tornadoes caused millions of dollars of damage and took several dozen lives. ||For southern Indiana, March 2nd became the worst tornado outbreak since June 2nd, 1990.",63
+359912,CLARK CO.,BLUE LICK,03/02/2012,1509,Tornado, ,EF4,1,0,55000000,0,IN,EST-5, ,60205,C,19,LMK,0,0,NWS Storm Survey, ,16.71,700,4,WNW,3,E,NABB,38.5156,-85.8678,38.606,-85.581,"This is a continuation of the violent long tracked tornado that began just south of Fredricksburg moved into Clark county as an EF-4 with a path width of one-third of a mile.  ||On Dan Gray Road, many well-constructed homes were leveled.  The tornado narrowed to a path width of one-quarter of a mile and decreased in intensity as it crossed Pixley Knob Road. Farther east, the twister destroyed two double-wide modular homes on Speith Road, killing one resident who had moments earlier been videotaping the tornado, and had taken shelter in the interior hallway of the home. Another family residence on the west side of the road was severely damaged, reflecting 150 mph winds.  ||The tornado crossed Interstate 65, trapping several people within damaged cars and semis.  This highway was closed for several hours.  The tornado strengthened just east of exit 19 off the Interstate as it entered a heavily industrialized area.  Buildings containing several businesses were destroyed.  A home was destroyed with estimated EF-4 winds on the east side of North Fraucke Road. Several homes were seriously damaged on the north side of State Highway 160.  The EF-4 tornado then moved through Henryville, severely damaging the south building of the Henryville Junior-Senior High School.  The cafeteria was completely destroyed and six automobiles were piled up along the south side of the school.  Two school buses in the south parking lot were ripped off their chassis, with one moved hundreds of feet east into a commercial business building across North Ferguson Street.  ||Extensive structural damage was surveyed on the east side of Henryville on North Front and Pennsylvania Streets.  A high tension tower and other homes were damaged just west of Pine Drive.  On Brownstown Road, many homes sustained EF-3 damage along the north side of the road.  Several homes were destroyed along Henryville-Otisco Road, with the damage to one reflecting EF-4 winds.  The tornado cycled near the intersect of Blackberry Trail and State Highway 3, with the original vortex narrowing rapidly into a rope-like funnel and ending as an EF-1 just as a new vortex immediately touched down just to the southwest of the original  near Highway 3 and Mahan Road. This new twister damaged a church as an EF-1 and quickly intensified to an EF-3 as it severely damaged several homes on the south side of Marysville. A Civil Air Patrol Flight revealed extensive ground scouring across several fields east of Marysville all the way to the Scott Jefferson County Line. The scouring indicated a multiple vortex tornado and was confirmed by witnesses and photos.  Several homes were severely damaged near and south of the intersection of Nabb-New Washington and Marysville-Nabb Roads.  The tornado had 150 mph winds and a width of one third of a mile at this point. ||The tornado intensified over open country east of the intersection of Kettle Bottom and State Highway 362 before crossing into Scott County as it moved north of Route 362.","A surface Low over Missouri early in the afternoon of March 2nd strengthened to below 990mb as it moved north into Michigan by the evening hours. Around dawn, a warm front moved north of the Ohio River, accompanied by scattered elevated thunderstorms that produced small hail. During the early afternoon, temperatures rose into the lower 70s across southern Indiana. the combination of extreme wind shear and CAPE near 2000 Joules/kg brought several long lived supercells to the state near the Ohio River. These storms produced baseball-sized hail and several tornadoes, including a violent long-tracker, to southern Indiana. The tornadoes across the area were a part of a well forecast regional outbreak that affected the entire Lower Ohio and Tennessee Valleys. Overall, more than 80 tornadoes caused millions of dollars of damage and took several dozen lives. ||For southern Indiana, March 2nd became the worst tornado outbreak since June 2nd, 1990.",64
+359916,SCOTT CO.,NABB,03/02/2012,1525,Tornado, ,EF4,1,0,500000,0,IN,EST-5, ,60205,C,143,LMK,0,0,NWS Storm Survey, ,0.61,500,3,E,3,ENE,NABB,38.6061,-85.5808,38.6094,-85.5702,"After exiting Clark County as an EF-4, this one-third mile wide tornado tracked for only six tenths of a mile across extreme southeastern Scott County before entering Jefferson County between the eastern endpoint of County Road 550 South and State Route 362. ||Despite its limited distance in Scott County, however, the tornado proved to be deadly, taking the life of a 72 year old man who was in his frame home residence on State Route 362 east of Kelly Bottom Road, where two other wood frame homes were also severely damaged and 5 mobile homes completely destroyed. This damage proved consistent with 170 mph winds.","A surface Low over Missouri early in the afternoon of March 2nd strengthened to below 990mb as it moved north into Michigan by the evening hours. Around dawn, a warm front moved north of the Ohio River, accompanied by scattered elevated thunderstorms that produced small hail. During the early afternoon, temperatures rose into the lower 70s across southern Indiana. the combination of extreme wind shear and CAPE near 2000 Joules/kg brought several long lived supercells to the state near the Ohio River. These storms produced baseball-sized hail and several tornadoes, including a violent long-tracker, to southern Indiana. The tornadoes across the area were a part of a well forecast regional outbreak that affected the entire Lower Ohio and Tennessee Valleys. Overall, more than 80 tornadoes caused millions of dollars of damage and took several dozen lives. ||For southern Indiana, March 2nd became the worst tornado outbreak since June 2nd, 1990.",65
+359915,JEFFERSON CO.,CHELSEA,03/02/2012,1526,Tornado, ,EF4,4,0,750000,0,IN,EST-5, ,60205,C,77,LMK,0,0,NWS Storm Survey, ,7.12,500,4,SW,2,ENE,PAYNESVILLE,38.6096,-85.57,38.6346,-85.4421,"The tornado entered Jefferson County as an EF-4 with a damage width of one-third of a mile. Several mobile homes were destroyed along and just north of State Highway 362 near the three-county intersection with Clark and Scott Counties. The tornado severely damaged several frame houses here, extensively damaged many power poles and power lines, and felled many trees.  ||After snapping trees and power poles along County Road 850, the tornado did a tremendous amount of damage around 2 miles south of Chelsea near the intersection of State Highway 62 and Swan Road.  Here, several well built brick homes were destroyed.  The homes had anchor bolts attached to steel plates and a concrete foundation.  One home was lifted and slide 65 yards off its foundation while still remaining essentially intact.  Another home was demolished and thrown several hundred yards downwind.  Three fatalities occurred at this location.  Two vehicles from the garage of this home were tossed for several dozen yards.  A third well-built brick home had its roof lifted and thrown over 300 yards, and an above-ground pool filled with water was missing.  Wind speeds were estimated at around 170 mph with a damage width of one quarter of a mile.  ||Through the rest of Jefferson county, the tornado did extensive damage to forests as it tracked to the north of Paynesville and south of Lee Bottom.  The damage path narrowed to 200 yards before exiting Jefferson County and moving over the Ohio River.","A surface Low over Missouri early in the afternoon of March 2nd strengthened to below 990mb as it moved north into Michigan by the evening hours. Around dawn, a warm front moved north of the Ohio River, accompanied by scattered elevated thunderstorms that produced small hail. During the early afternoon, temperatures rose into the lower 70s across southern Indiana. the combination of extreme wind shear and CAPE near 2000 Joules/kg brought several long lived supercells to the state near the Ohio River. These storms produced baseball-sized hail and several tornadoes, including a violent long-tracker, to southern Indiana. The tornadoes across the area were a part of a well forecast regional outbreak that affected the entire Lower Ohio and Tennessee Valleys. Overall, more than 80 tornadoes caused millions of dollars of damage and took several dozen lives. ||For southern Indiana, March 2nd became the worst tornado outbreak since June 2nd, 1990.",66
+369474,KENTON CO.,BRACHT,03/02/2012,1624,Tornado, ,EF4,4,8,20000000,0,KY,EST-5, ,61698,C,117,ILN,0,0,NWS Storm Survey, ,8.52,880,2,SW,1,SSW,MORNING VIEW,38.796,-84.6092,38.8209,-84.4541,"The tornado touched down in Grant County at 1623 EST, causing low to mid EF3 damage specifically in the Harvesters Subdivision. This damage occurred at the west end of Barley Circle. Most of the damage in the rest of the subdivision was EF1 to EF2. Based on the damage surveyed, the maximum wind speed of this tornado while in Grant County was estimated at 145 miles per hour. After traveling 1.33 miles on the ground in Grant County, the tornado then crossed into Kenton County at 1624 EST. Immediately as the tornado crossed west to east of Interstate 75, it strengthened to EF4 level. Five single family homes were destroyed down to their foundations in this area, with at least two of these homes having strapping or bolting to their foundations. The EF4 damage continued to the north end of Lexington Pike, where 2 homes and multiple outbuildings were completely destroyed. Both homes were brick structures with foundation bolting or strapping. The EF4 winds continued across Route 25 and ended near the Bagby Road area. At least 2 vehicles were carried, with one carried over 1800 feet. Trees were stripped of nearly all branches, with much of the bark also stripped. All 4 fatalities with this tornado occurred within the area of EF4 damage. As the tornado headed further to the east northeast, high end EF3 damage continued through other properties along Bagby Road, to Carlisle, Parker Grove, and Paxton Roads. Numerous double and single wide homes were destroyed, with both brick and siding structures left with collapsed exterior walls and either all or a large percentage of the roof removed. The tornado continued the east northeast path into southeast Kenton County, to the Licking River near Morning View. Damage in the Morning View area was consistent with EF1 to EF2 damage to near the Campbell County line, where the tornado lifted at 1632 EST after traveling 8.52 miles in Kenton County. Based on the damage surveyed, the maximum wind speed from this tornado while in Kenton County was estimated at 175 miles per hour. This storm produced an earlier tornado in southern Indiana. Debris, possibly from that tornado, was later observed falling from the sky across Boone County, Kentucky.","Thunderstorms developed during the afternoon in a high wind shear environment ahead of a strengthening low pressure system. Many of these storms became severe, with large hail, damaging thunderstorm winds, and tornadoes all being the main threats. Isolated flooding also became possible due to the intense rainfall.",67
+366383,ELLSWORTH CO.,KANAPOLIS RES,04/14/2012,1700,Tornado, ,EF4,0,0,0,0,KS,CST-6, ,61250,C,53,ICT,0,0,Amateur Radio, ,6.31,400,9,S,7,SE,KANAPOLIS RES,38.523,-98.008,38.588,-97.926,"Tornado scoured and dug out a section gravel road about 4 to 5 inches deep. Home was swept off foundation and destroyed with small stair case remaining in center. Debris from home was tossed into adjacent tree line to the northeast. Numerous trees around the house were snapped and shredded. Some trees were also debarked from the intense wind speeds. Car was flipped and tossed upside down.  This tornado moved into McPherson County.","A significant severe weather outbreak with several damaging long track tornadoes occurred.  The strongest tornado moved through portions of central Kansas and produced EF-4 damage at one home stead.  Two other tornadoes touched down producing EF-3 damage in south central Kansas.",68
+433413,LAMAR CO.,OAK GROVE,02/10/2013,1703,Tornado, ,EF4,0,8,13500000,0,MS,CST-6, ,71831,C,73,JAN,0,0,NWS Storm Survey, ,7.55,1320,3,W,1,ESE,WARDWELL STATION,31.2802,-89.4665,31.3215,-89.348,"The tornado started along Highway 589, where some limbs and small trees were blown down. It became intense rather quickly, producing significant damage as it moved through the West Lake Serene area. The tornado reached its maximum intensity in the area around and just southwest of Oak Grove High School where maximum winds were estimated at 170 mph, which is EF-4 strength. There was a brick home in a subdivision southwest of the high school, just west of old Highway 11, that was completely leveled with all interior and exterior walls down, and a fair amount of large debris was blown downstream. Additionally, very high end timber damage occurred in this location with a number of trees showing debarking and denuding. Several other homes in this subdivision also sustained EF-2 to EF-3 damage. As the tornado crossed old Highway 11, it produced extensive damage on the campus of Oak Grove High School. The field house adjoining the football stadium was destroyed, the baseball stadium and a large metal building adjoining the stadium were essentially destroyed, and several large steel/concrete light standards were snapped at both the baseball and football stadiums. A vehicle was thrown from the parking lot adjoining the baseball stadium, up a small hill and was deposited near the pitching mound in the middle of the baseball field. The main building of the high school also suffered roof damage.||The tornado then moved northeast into the heavily populated areas of Oak Grove and West Hattiesburg, including areas along Lincoln Road Extension, Weathersby Road, Oak Grove Road, and the area just south of Highway 98 along Clark, Lamar and Foxgate Avenues. Numerous homes were destroyed or suffered major damage, and a few homes showed evidence of high end EF-3 damage. Dozens of power poles were snapped and extensive tree damage occurred. Video evidence and ground survey damage appeared to indicate that the tornado was multi-vortex in nature during its Lamar County portion. Just before crossing Interstate 59, it caused significant roof damage to a number of apartment buildings just west of the interstate. In total in Lamar County, emergency management indicated that 51 homes were destroyed and 170 suffered major damage.||The tornado then moved into Forrest County just to the south of Hardy Street damaging numerous homes with the damage in the EF-2 and EF-3 category. It then crossed Hardy Street impacting the southeast corner of the University of Southern Mississippi campus. Numerous buildings were damaged in this area including several campus buildings and a large church. Numerous power poles were blown down in this area and several metal traffic lights were bent or torn off their bases. Damage in this area was also EF-2 and EF-3.||The tornado continued across Highway 49 impacting multiple neighborhoods. Numerous roofs were blown off houses and many trees fell on houses and vehicles. The tornado crossed North Main Street causing significant damage to the Red Cross building, the Girl Scouts building, and bending large metal poles at the Hattiesburg High School athletic fields. The tornado then moved across east 7th Street causing significant damage to several large brick buildings. Damage in the area between north Main Street and east 7th Avenue was in the high end EF-3 range with maximum winds around 160 mph.||The tornado continued into Petal with the most significant damage occurring to an Ace Hardware store on South Main Street. Numerous homes in the vicinity of the hardware store also had roofs torn off and exterior walls collapsed. This damage was also rated high end EF-3 with maximum winds around 160 mph.||The tornado began to weaken as it crossed the Evelyn Gandy Parkway to the northeast of Petal. Damage in this area was mainly EF-1 and EF-2 and consisted of roof damage and snapped trees. The tornado strengthened one last time as it moved through a neighborhood just off Twin Lakes Road. Numerous well built homes experienced EF-2 damage to the roofs in this neighborhood. The tornado weakened as it approached the Perry County line and dissipated a couple of miles into Perry County. Damage at the end of the track was in the EF-0 to EF-1 range.||In Forrest County, emergency management indicated that 133 homes were destroyed and 207 suffered major damage. There were 63 reported injuries.||This is the second violent tornado to impact Lamar and Forrest Counties in recorded history. The other violent tornado was the infamous Purvis tornado on April 24, 1908 that was on the ground for 155 miles and impacted many counties across Mississippi. In total, 143 people were killed by this tornado, including 60 in Lamar County and 4 in Forrest County.","An approaching cold front, an unusually high amount of wind shear, and sufficient instability resulted in an outbreak of severe thunderstorms across portions of the lower Deep South, including a violent tornado that moved through Hattiesburg. During the morning hours of February 10th, a line of severe thunderstorms moved into the ArkLaMiss, downing trees and powerlines over portions of southeast Arkansas, northeast Louisiana, and central Mississippi. There was also a barn destroyed near Silver City in Humphreys County. The storms continued to push eastward through the early afternoon, then began to slow down as the cold front began to stall. To the south and east of this line of storms, several supercell thunderstorms developed in the more unstable air mass over south Mississippi, with many of the storms exhibiting strong rotation on radar. Shortly after 4 pm, a tornado developed over southwest Marion County near the Pickwick community and tracked across the county into far western Lamar County before lifting. The same storm which produced this tornado continued eastward across northern Lamar County, producing a large tornado which touched down west of Oak Grove and tracked through the very populated West Hattiesburg area. The tornado continued into Forrest County, tracking through the cities of Hattiesburg and Petal before ending in northwestern Perry County. Considerable damage occurred along the path of this storm, and several people were injured. Scattered severe storms continued to affect the Pine Belt area through the remainder of the evening and into the early morning hours of the 11th, before finally moving out of the area.||In addition to severe weather, flash flooding was a major issue in several areas. From the 10th through the early morning hours of the 11th, the heaviest rainfall occurred over parts of southeast Mississippi, where 5 to 7 inches of rain fell and flash flooding was reported in the area. Rainfall amounts of up to 3 1/2 inches occurred in the Jackson metro area, leading to considerable flash flooding. Quick rises occurred on several streams in the city of Jackson.",69
+443090,HOOD CO.,MAMBRINO,05/15/2013,1858,Tornado, ,EF4,6,54,143000000,0,TX,CST-6, ,73336,C,221,FWD,0,0,NWS Storm Survey, ,2.5,400,2,N,2,WSW,ACTON,32.412,-97.754,32.438,-97.7243,"National Weather Service crews surveyed the damage from the Granbury tornado. The tornado first occurred on the west bank of Lake Granbury / Brazos River. The tornado crossed the lake heading east, towards Davis Road. On the east side of the lake, the tornado damaged several power lines and trees, before hitting the American Legion hall on Davis Road. ||The tornado then took much more of a northerly track through the Rancho Brazos subdivision. This subdivision was severely damaged, with 97 of the 110 homes suffering at least minor damage. Four homes suffered EF-4 damage, and ten others had EF-3 damage. The vast majority of the subdivision had evidence of EF-1 or EF-2 damage. Six individuals lost their lives in this subdivision as a direct result of the tornado. All six were in mobile homes at the time. ||Moving north from the Rancho Brazos subdivision, the tornado dissipated approximately one mile to the north-northeast of the area that suffered the most damage.","A tornado and severe weather outbreak occurred on the afternoon and evening hours of May 15th. Nineteen tornadoes occurred, including one EF-4 and one EF-3. Six fatalities occurred in the city of Granbury, TX. These fatalities were the first in the Fort Worth county warning area since 2006. An additional 54 people were injured by the various tornadoes during the evening of May 15th. A number of homes, 171, suffered major damaged or were destroyed. An additional 513 homes suffered minor damage or were somehow affected. ||During the afternoon of May 15th, a vigorous upper level low moved slowly southeast from the panhandle of Texas into the Red River Valley. A dry line strengthened throughout the day, triggering thunderstorms between Bowie and the DFW metroplex. As the upper storm moved slowly east and southeast, several supercell thunderstorms developed, and most of them produced tornadoes.",70
+457695,PAWNEE CO.,BURDETT RUCKER ARPT,05/18/2013,1818,Tornado, ,EF4,0,0,140000,0,KS,CST-6, ,75824,C,145,DDC,0,0,NWS Storm Survey, ,7,1100,4,SE,2,E,BURDETT ROZEL ARPT,38.1429,-99.4706,38.231,-99.4301,"This tornado was well documented by storm chasers, spotters and a research team with portable doppler radar.  The tornado did turn north towards the end of it's life cycle.  Low end EF4 damage was done to a home along US156.  The roof and walls were blown away of this well constructed house.  Several large tanks were carried a long distance.  There were 2 people inside but they escaped injury by taking shelter.  Video shows that sub-vortices within the tornado may have actually had a little stronger wind.  The Doppler on wheels that was observing the tornado had near surface measured wind speeds of 165 to 185 MPH.","High instability was in place as an upper level wind maxima moved out of the base of a deep upper trough in the west.",71
+451506,POTTAWATOMIE CO.,PINK,05/19/2013,1720,Tornado, ,EF4,2,6,0,0,OK,CST-6, ,73821,C,125,OUN,0,0,NWS Storm Survey, ,12.5,1500,4,NNW,4,WSW,AYDELOTTE,35.308,-97.142,35.423,-96.981,"The large tornado moved east-northeast into Pottawatomie County then curving northeast as it approached State Highway 102. The tornado moved through a mobile home park north of Independence Road after crossing State Highway 102. Just northeast of the mobile home park, a permanent home was destroyed with much of the debris blown well to the northeast.  It continued northeast crossing Interstate 40 near the intersection of US-177, then curved north-northeast finally dissipating near Wolverine Road and Coker Road. One fatality occurred in the mobile home park, and another man was killed in his vehicle.","A moist and very unstable airmass was in place over the eastern two thirds of Oklahoma, to the east of a dryline. Additionally, strong wind shear was present as a mid-level jet streak carved into the southern Plains. Several supercells developed along the dryline during the mid and late afternoon hours, producing large hail. Two supercells in central Oklahoma also produced tornadoes, including a few significant, damaging tornadoes.",72
+451537,MCCLAIN CO.,NEWCASTLE,05/20/2013,1356,Tornado, ,EF4,0,5,0,0,OK,CST-6, ,74673,C,87,OUN,0,0,NWS Storm Survey, ,1.85,1280,3,NW,4,N,NEWCASTLE,35.284,-97.628,35.303,-97.605,"The violent Newcastle-Moore tornado was first observed developing about one-half mile south of State Highway 37 in northwest Newcastle to the east of Rockwell Avenue. EF4 damage was observed soon after the tornado crossed State Highway 37. The tornado continued to expand in size as it approached the Canadian River and moved into Cleveland County.||Of the 212 direct injuries documented with this tornado, 5 are estimated to have occurred in McClain County.","A tornado outbreak occurred during the afternoon and evening hours of the 20th. Several tornadoes occurred from central Oklahoma down through south central Oklahoma near the Red River. The strongest tornado touched down near Newcastle and traveled through Moore and south Oklahoma City. This tornado caused catastrophic damage in these areas, with a maximum rating of EF-5. The tornado claimed 24 lives and caused billions of dollars in damage. In addition to the tornadoes, large hail and damaging winds cause damage in many areas.",73
+451572,CLEVELAND CO.,MOORE,05/20/2013,1404,Tornado, ,EF5,24,207,2000000000,0,OK,CST-6, ,74673,C,27,OUN,0,0,NWS Storm Survey, ,12,1900,7,WSW,3,WNW,STANLEY DRAPER LAKE DAM,35.303,-97.605,35.341,-97.3999,"The violent Newcastle-Moore tornado moved into Cleveland County from McClain County as it moved northeast across the Canadian River near Interstate 44. The tornado then turned more east and then east-northeast after crossing Interstate 44. Violent EF4 damage was again observed as it began to move into progressively higher density residential areas approaching May Avenue.||The center of the large tornado path passed near SW 149th Street and Western Avenue. After crossing Western Avenue, numerous buildings were destroyed and horses killed at Orr Family Farm. Two storage tanks estimated to weigh approximately 10 tons were lifted from Orr Family Farm and landed about one-half mile east. Moving east, the tornado destroyed much of Briarwood Elementary School, where the NWS storm survey team initially rated the damage as EF5. However, further evaluation indicated that an EF4 rating was more appropriate at the school. Despite the destruction of this elementary school during school hours, no fatalities occurred at the school. As the tornado continued to move east and east-northeast, it moved through much more densely populated suburban neighborhoods of southwest Oklahoma City and Moore where violent destruction was widespread and a few houses were rated EF5. The width of EF4 and greater damage was up to 250 yards wide as the tornado moved through neighborhoods east of Western Avenue. The first two fatalities occurred in a house in the neighborhood just east of Briarwood Elementary, with another fatality in a house as the tornado approached Santa Fe Avenue. ||After crossing Santa Fe Avenue, the tornado moved through more suburban neighborhoods and toward Plaza Towers Elementary School. Damage to the school was extensive and seven children were killed when a wall collapsed at the school. Nine other people were killed in eight different neighborhood homes within one-quarter mile of Plaza Towers Elementary, most occurring just south of the school.||The tornado turned northeast as it approached Telephone Road, made a loop near the intersection of Telephone Road and 4th Street, then moved southeast crossing the interstate. Three people were killed when a convenience store along Telephone Road was destroyed. Crossing Telephone Road, the tornado inflicted significant damage to the Moore Medical Center, a post office and numerous businesses along Telephone Road and Interstate 35. Although the tornado was more narrow after crossing Interstate 35, it continued to produce EF4 damage in neighborhoods east of the interstate as it curved east and then again east-northeast. One fatality occurred at a business just east of the interstate, and one final fatality occurred in a home between Eastern Avenue and Bryant Avenue. Consistent EF4 damage continued until the tornado passed SE 4th Street just east of Bryant Avenue. Moving east from Bryant, the tornado continued to produce EF2 damage with isolated EF4 damage noted. The density of housing also decreased east of Bryant as the tornado moved east and east-northeast before dissipating east of Air Depot Blvd. between SE 119th Street and SE 134th Street in southeast Oklahoma City.||Overall, over 300 homes experienced EF4/EF5 damage along the tornado path. Of the 212 direct injuries documented from this tornado, 207 are estimated to have occurred in Cleveland County.","A tornado outbreak occurred during the afternoon and evening hours of the 20th. Several tornadoes occurred from central Oklahoma down through south central Oklahoma near the Red River. The strongest tornado touched down near Newcastle and traveled through Moore and south Oklahoma City. This tornado caused catastrophic damage in these areas, with a maximum rating of EF-5. The tornado claimed 24 lives and caused billions of dollars in damage. In addition to the tornadoes, large hail and damaging winds cause damage in many areas.",74
+472670,WAYNE CO.,ALTONA,10/04/2013,1612,Tornado, ,EF4,0,15,0,0,NE,CST-6, ,78590,C,179,OAX,0,0,NWS Storm Survey, ,10.77,2428.8,4,WNW,3,NNE,WAYNE ARPT,42.128,-97.077,42.2643,-96.9559,"This violent tornado started 8 miles southwest of Wayne, Nebraska and flattened corn crops and tore off large limbs of some trees. Gaining strength as it headed northeast, the tornado struct a farmstead about 4.5 miles southwest of Wayne. Here barns and sheds were severely damaged or destroyed. The tornado became very wide at this point, nearly 1.25 miles wide. About 2 miles south of Wayne the tornado severely damaged a farmstead and then cased strong EF-3 damage to two homes along highway 15. The tornado then missed the downtown and residential district of Wayne and severely damaged a softball complex on the southeast side of town. ||The most significant damage occurred in the industrial part area on the east side of Wayne. Numerous metal building structures, some of them quiet large, sustained serious damage or were mangled into rubble. It was here the tornado was rated EF-3 with a couple of small pockets of low-end EF-4 damage. The tornado then crossed highway 35 and impacted the Wayne Municipal Airport. Two hangers were flattened. Some private aircraft were tumbled and ripped up. The automated weather observing station at the airport was also torn up. Continuing northeast, the tornado struck another farmstead and caused EF-2 damage to a home.  Damage continued northeast at it tracked into Dixon County. The damage in the Wayne area was estimated at $50 million.","The same powerful storm system that produced severe weather across eastern Nebraska on October 3rd remain in the area on the 4th. A strong area of low pressure moved from eastern Colorado into southern South Dakota during the day. As this occurred, a dry line was sweeping across central and into eastern Nebraska. A warm front continued to lift north into northeast Nebraska and western Iowa by late afternoon. With unseasonably warm and moist air in the region the atmosphere became strongly unstable. This instability coupled with a strong wind field associated with the powerful storm system and created and environment favorable for significant severe weather. Supercells developed near the intersection of the dry line and warm front over northeast Nebraska during the afternoon and tracked northeast. The supercells were responsible for large hail, damaging winds, and significant tornadoes. Other isolated thunderstorms developed south along the dry line into western Iowa producing very large hail and damaging winds during the evening of the 4th.",75
+476100,WOODBURY CO.,CLIMBING HILL,10/04/2013,1735,Tornado, ,EF4,0,0,2000000,0,IA,CST-6, ,79333,C,193,FSD,0,0,NWS Storm Survey, ,22.66,2600,2,SW,5,E,PIERSON,42.3319,-96.1086,42.5609,-95.7905,"A tornado severely damaged or destroyed about 10 houses, collapsing most walls on a few of the houses, tearing most of the roofs off other houses, and shifting what was left of some houses off their foundations. The tornado caused significant damage to roofs, windows, and siding of additional houses. Numerous farm outbuildings, storage buildings, and a few silos were destroyed or severely damaged. The tornado also destroyed or damaged several pieces of farm equipment, caused significant tree damage, including numerous trunks snapped or uprooted and other trees stripped, and blew down power poles and lines. The tornado then crossed into Cherokee County.","Thunderstorms produced eleven tornadoes, several of them causing damage, which tracked wholly or partly in northwest Iowa during the afternoon and early evening of October 4th. There were also two reports of large hail and one report of non tornadic damaging thunderstorm winds.",76
+483775,TAZEWELL CO.,MARQUETTE HGTS,11/17/2013,1059,Tornado, ,EF4,3,121,910000000,0,IL,CST-6, ,80819,C,179,ILX,0,0,NWS Storm Survey, ,14.16,880,2,E,2,NNE,PEKIN JCT,40.622,-89.5678,40.7482,-89.3549,"A tornado touched down 2.4 miles SE of East Peoria at 10:59 AM CST, then tracked northeastward through parts of East Peoria and Washington before crossing the border into Woodford County at 11:12 AM CST.  One man in Washington was killed by the tornado, one woman from Washington died 11 days later from multiple serious injuries sustained by the tornado, one man died six weeks later from injuries sustained by the tornado, and 121 people were injured.|  |In East Peoria: 20 homes were destroyed, while 75 homes, 7 businesses, and 5 apartment buildings suffered major damage.  Minor damage occurred to 137 homes and 3 businesses.  In addition, nearly 400 vehicles were damaged, thousands of trees and numerous power poles were destroyed.  The estimated damage in East Peoria stands at $110 million.||In Washington: The tornado increased to EF4 intensity and widened to between 1/4 and 1/2 mile wide.  633 homes, 7 businesses, 7 apartment buildings, and 2,500 vehicles were destroyed.  Major damage occurred to 280 homes, 2 businesses, the roof of a school, and several outbuildings.  Minor damage occurred to another 190 homes.  Thousands of trees and power poles were snapped.  Nearly 5,000 people were in the path of this tornado: however, injury and fatality totals were relatively low due to early warning and the fact that many people were either in church or out of town at the time. The tornado moved out of the Washington city limits and across another 2 miles of rural Tazewell County before crossing the border into Woodford County.  Total damage in Washington is estimated at $800 million.","A powerful low pressure system tracked from the central Rockies toward the southern Great Lakes on November 17th. As the system approached central Illinois, unseasonably warm and humid air was pulled northward into the area, resulting in high temperatures soaring into the 70s. This very unstable airmass coupled with strong jet stream level winds aloft created numerous strong to severe thunderstorms. Many of the storms became supercells, producing damaging long-track tornadoes.  A total of 10 tornadoes touched down across central Illinois, including an EF4 tornado that severely impacted the community of Washington in Tazewell County.  Three people were killed and 142 others were injured as the storms tracked through the area.  Total damage was estimated at 1.06 billion dollars across central Illinois.",77
+482450,WASHINGTON CO.,ADDIEVILLE,11/17/2013,1204,Tornado, ,EF4,2,2,0,0,IL,CST-6, ,80439,C,189,LSX,0,0,NWS Storm Survey, ,10.59,200,2,NE,2,N,HOYLETON,38.42,-89.45,38.48,-89.27,"A tornado touchdown on Interstate 64, about 4.4 miles southwest of New Minden, blowing a tractor trailer off the interstate and causing minor injuries to the driver.  The tornado then began moving northeast towards New Minden.  The worst damage was about 2 miles west southwest of New Minden, where a small farm sustained a direct hit.  The outbuildings and barns sustained varying degrees of damage, but the homestead was totally destroyed with only the foundation remaining.  The damage at the homestead was rated EF4, and two fatalities occurred at this location.  Also, a large full size van was rolled over.  Less than a quarter of a mile east of the house, a single wide mobile home was destroyed.  There were 4 people at this location, three of them sought shelter in the creek bed just east of the mobile home while one went back to mobile home to retrieve something.  This person rode out the tornado in the bathtub, but was thrown about 50 feet into a field.  One of his ankles was broken.  He was treated and released from a local hospital.  The tornado then continued to race northeast, hitting the far north side of New Minden north of Illinois Route 177, and producing significant damage to St. Johns Lutheran Church and to several homes just northwest of the church.  Damage to two of the homes was rated EF3.  The tornado continued northeast, producing sporadic damage to just north of Hoyleton. A farm 2 miles west-northwest of Hoyleton sustained significant damage, as did a newly constructed home 2 miles north of Hoyleton.  Damage at these two locations were rated EF2.  The tornado then veered a bit northwest and dissipated.  Overall, the entire tornado path length was 10.59 miles with a max path width of 200 yards. The tornado was rated EF4 with max wind speeds of at least 166 MPH.  There were two fatalities and 2 minor injuries.","Strong cold front moved through the region with plenty of lift, moisture and instability. Numerous severe storms developed and raced east across forecast area.  There were numerous reports of large hail, damaging winds and tornadoes. Also, because of a tight gradient with this system non-thunderstorm winds gusted in excess of 40 mph in a number of locations.",78
+504760,FAULKNER CO.,PALARM,04/27/2014,1825,Tornado, ,EF4,12,167,210000000,0,AR,CST-6, ,83594,C,45,LZK,0,0,NWS Storm Survey, ,24.24,1320,1,SW,5,SE,NAYLOR,34.913,-92.4572,35.1271,-92.1179,"This tornado exited Pulaski County 1.6 miles northeast of Roland, while crossing the Arkansas River, and entered Faulkner County 0.6 mile southwest of Palarm. The tornado reached its maximum intensity of EF4 in Faulkner County. It tracked through the River Plantation subdivision and White City, then struck Mayflower, where residences and businesses were destroyed. The tornado then moved across Interstate 40 at Mayflower, throwing cars, trucks, and road construction equipment off the freeway. Traffic along the interstate was backed up for weeks following the tornado as motorists slowed to view the damage. Next, the tornado crossed a part of Lake Conway and moved across part of Camp Robinson, a National Guard facility, where the Arkansas Game and Fish Commission lost a clubhouse, shop, horse barn, residence, metal carports, shower house, and dog kennels. The tornado then continued on through Saltillo and then caused devastation to homes and businesses in Vilonia. About 400 people had taken shelter in a safe room at the Vilonia high school. ||According to the American Red Cross, in Faulkner County, the tornado destroyed 261 houses and 121 mobile homes; caused major damage to 77 houses, 29 mobile homes, and 5 apartments; caused minor damage to 96 houses, 14 mobile homes, and 4 apartments; and affected 257 houses, 32 mobile homes, and 4 apartments. Hundreds of cars and pickup trucks were mangled along the path of the tornado. ||In Mayflower, a home improvement store was badly damaged, and a vehicle repair shop, millwork company, construction company, electric substation, and church were destroyed. A recreational vehicle dealership and dozens of RVs were also destroyed. The Arkansas Game and Fish Commission eventually removed 627 tons of tornado debris from Lake Conway. In Vilonia, the new intermediate school under construction was destroyed, as were nearly two dozen businesses along Main St. (U.S. 64B), including a dollar store, a strip mall, two auto repair shops, the old city hall, a gas station, a real estate office, an investment firm, an auto parts store, and a fried chicken restaurant. ||There were 12 fatalities in Faulkner County. In the Mayflower area, a 72-year-old woman was killed in a house on Plantation Dr., a 51-year-old man was killed in a house on Fortner Dr., and an 82-year-old man was killed in a house on Dam Rd. The other 9 fatalities were all in the Vilonia area. These included: brothers 7- and 9-years-old in a house on Cody Ln., a 50-year-old woman in a vehicle on U.S. 64, a 52-year-old man and a 53-year-old woman in a house on Cemetery Rd., a 57-year-old man in a house on North St., a 31-year-old man in a house on Aspen Creek Dr., and a 22-year-old man in a house on Clover Ridge Dr. In addition, a woman who was injured in a mobile home on Ponderosa Dr. gave birth to a baby which died immediately. More than 150 people were treated at hospitals. ||The tornado hit Vilonia three years and two days after a tornado had destroyed some of the same structures. The tornado exited Faulkner County 4.6 miles southeast of Naylor and entered White County 2.2 miles west-northwest of El Paso.","A round of showers and thunderstorms occurred during the morning of the 27th. Some of the storms produced hail in central Arkansas. New storms during the afternoon dropped hail in the northern and western parts of the state. The cool outflow from the morning storms left a boundary draped across the middle of the state. This boundary separated cool air to the north and much warmer air to the south. During the evening, as a strong area of low pressure approached, a supercell erupted rapidly along the boundary. Altogether, the supercell produced five separate tornadoes, the first of which was rated EF4 and killed 16 people. It was the deadliest single tornado in Arkansas since 1968. Nearly 200 people were treated at hospitals.||Large amounts of rain fell over the northeastern quarter of the state. For the 24-hour period ending at 7 AM on the 28th, some of the larger totals included 7.60 inches at Batesville Lock and Dam (Independence Co.), 6.10 inches at Calamine (Sharp Co.), 5.34 inches at Evening Shade (Sharp Co.), 5.05 inches at Melbourne (Izard Co.), 4.46 inches at Hardy (Sharp Co.), 4.18 inches at Blanchard Springs (Stone Co.), 3.96 inches at Armstead Mountain (Pope Co.), 3.95 inches at Saddle (Fulton Co.), 3.92 inches at Poughkeepsie (Sharp Co.), 3.91 inches at Greers Ferry Dam (Cleburne Co.), and 3.72 inches at Mountain View (Stone Co.).||President Barack Obama declared a disaster in the following counties:  Faulkner, Pulaski, White, Cleburne, Independence, Jackson, Izard, Sharp, and Fulton.",79
+508158,WINSTON CO.,ZAMA,04/28/2014,1505,Tornado, ,EF4,10,81,115000000,6500000,MS,CST-6, ,84120,C,159,JAN,0,0,NWS Storm Survey, ,25.01,1320,5,ESE,4,SW,BETHEDEN,32.932,-89.3067,33.1893,-89.0028,"This tornado first touched down in northeastern Leake County, where the damage was mostly downed trees. As the tornado approached the 4 corners intersection of Leake, Attala, Neshoba, and Winston Counties, it strengthened and began to impact structures. Several mobile homes, medal buildings and single family homes were damaged or destroyed in this area along Highway 25. The tornado continued northeast impacting rural areas of southwest Winston County. There it intensified and began to produce EF3 and some areas of EF4 damage. Numerous homes were destroyed, trees were debarked and severe damage occurred to several chicken farms. The EF4 damage in this area was a building reduced to a slab and a chicken farm that was completely wiped away.||At this point, the tornado made a turn to a more northerly course and continued to cause EF2 and EF3 damage just south of Louisville. The tornado entered the city of Louisville on the south side along Highway 15 and continued north-northeast through the east side of the city. Widespread EF3 and EF4 damage occurred in this area. Of particular note, several industrial buildings were destroyed and an area of homes and apartments was destroyed, a few of them being completely taken down to the slab.||The tornado continued through the east side of Louisville causing mainly EF3 damage. Of particular note, the Winston Medical Center received heavy damage and became incapable of use. The tornado continued moving north-northeast roughly along McCullough Road causing EF3 and EF4 damage. Numerous homes had their roofs and walls removed and some were reduced to slabs. Near the intersection with Louisville-Brooksville Road, two particularly well built homes were very heavily damaged and received EF4 ratings.||From this point, the tornado began to weaken, causing mainly EF2 and EF3 damage along North Columbus Avenue. As it approached a second intersection with Highway 25, the tornado lifted after traveling on the ground for over 34 miles.","A powerful spring storm system brought a multi-day severe weather outbreak across a large portion of the country during the April 27-30 time frame. This outbreak started across the Central Plains on the 27th and slowly migrated eastward over the following two days. A large tornado outbreak occurred across the Lower MS River & TN River Valleys on the 28th. The event was capped on the 30th with additional severe weather and a historic flash flooding/heavy rain event along the AL, FL gulf coast where rainfall totals peaked between 15-25 inches!||Across the NWS Jackson, MS forecast area, the tornado outbreak on the 28th was the main event. This event was driven by a classic severe weather pattern with a strong fast moving jet stream and a deep surface cyclone over the central plains. These features helped to produce strong wind shear in the atmosphere which in turn combined with rich gulf moisture and setup a volatile atmospheric mix. Multiple supercell thunderstorms developed during the afternoon/evening and produced many instances of damaging wind and large hail along with multiple tornadoes. The most devastating tornado was the EF-4 which tore a path across NE Leake, the corners of Attala/Neshoba counties, and through the heart of Winston County where the city of Louisville was especially hard hit. This tornado was on ground for 34.3 miles and resulted in 10 fatalities and many injuries. Other hard hit counties were Lowndes, Rankin, Hinds, Scott, Newton, Montgomery, Warren and Jones. Each of these counties experienced at least one tornado, some multiple tornadoes. Overall, 21 tornadoes were confirmed across the forecast area. Of these tornadoes, 3 were rated EF-3, 3 rated EF-2, 12 rated EF1 and 2 rated EF-0.",80
+514013,STANTON CO.,STANTON,06/16/2014,1442,Tornado, ,EF4,0,0,2000000,250000,NE,CST-6, ,84971,C,167,OAX,0,0,NWS Storm Survey, ,12.11,400,6,SW,7,N,STANTON,41.893,-97.33,42.0441,-97.2105,"This tornado began to the southwest of the Stanton and increased in intensity and size as it moved to the north northeast, passing to the west of the city of Stanton by about 2 miles. The tornado did the most significant damage to the north of Stanton where two farmsteads were completely destroyed just to the south of Highway 275. Here two vehicles, one car and one truck, were picked up by the tornado and tossed over a quarter of a mile. The tornado also completely destroyed two other homes and outbuildings, as well as debarking trees. The tornado continued northeast of Highway 275 for about 3 miles before roping out.","During the early morning hours of June 16th a warm, humid and unstable airmass rapidly returned to eastern Nebraska and western Iowa. As this air returned to the region, scattered thunderstorms developed during the early morning hours and continued into early afternoon. These thunderstorms were responsible for mainly large hail, some of which was very large. These morning thunderstorms reinforced a warm front across eastern Nebraska during the afternoon. Extreme instability developed along this warm front and allowed for isolated thunderstorm development by mid afternoon, which quickly become severe. A single supercell thunderstorm went on to produce 4 violent tornadoes over the next 2 hours. Other strong and severe thunderstorms moved into northeast Nebraska in the evening and continued into the early morning hours.",81
+514014,STANTON CO.,STANTON,06/16/2014,1500,Tornado, ,EF4,1,20,12000000,250000,NE,CST-6, ,84971,C,167,OAX,0,0,NWS Storm Survey, ,8.05,500,5,E,2,ENE,PILGER,41.9528,-97.1369,42.0297,-97.0193,"This tornado developed about 5.5 miles southwest of the town of Pilger and moved directly northeast directly striking the town. The tornado did violent damage within the town of Pilger.  Nearly 75 percent of the structures in the town received some damage, while structures near the center of the tornado were completely destroyed.  A 5-year-old girl was killed and her mother seriously injured while attempting to take cover from their mobile home to a storm shelter.  The tornado continued to move northeast past the town crossing Highway 275 about 1 mile west of the Cuming County line. The tornado continued northeast exiting Stanton County about 2.25 miles northeast of the city of Pilger into Cuming County.","During the early morning hours of June 16th a warm, humid and unstable airmass rapidly returned to eastern Nebraska and western Iowa. As this air returned to the region, scattered thunderstorms developed during the early morning hours and continued into early afternoon. These thunderstorms were responsible for mainly large hail, some of which was very large. These morning thunderstorms reinforced a warm front across eastern Nebraska during the afternoon. Extreme instability developed along this warm front and allowed for isolated thunderstorm development by mid afternoon, which quickly become severe. A single supercell thunderstorm went on to produce 4 violent tornadoes over the next 2 hours. Other strong and severe thunderstorms moved into northeast Nebraska in the evening and continued into the early morning hours.",82
+514042,CUMING CO.,WISNER,06/16/2014,1517,Tornado, ,EF4,1,0,1000000,250000,NE,CST-6, ,84971,C,39,OAX,0,0,NWS Storm Survey, ,8.6,500,5,W,8,N,WISNER,41.9797,-97.0198,42.091,-96.9449,"As the tornado continued from Stanton County into Cuming county it increased in size and intensity. The tornado crossed the Elkhorn River about 3 miles west of Wisner and then crossed Highway 275 where significant damage was done to a cattle ranch. Over 300 head of cattle were lost here, as well as numerous outbuildings. The tornado continued to the north northeast, running nearly parallel to the Pilger tornado for a time impacting several farmsteads along 4 1/2 Road. As the tornado neared X Road along 4 1/2 Road it directly impacted two farmsteads where violent damage was done including completely destroying two homes down to the foundation, destroying outbuildings, lofting vehicles, and debarking trees.  A 74-year-old Clarkson, Nebraska resident was killed when the vehicle he was driving was flipped by the tornado.  The tornado crossed in front of the Pilger tornado and continued to the north into Wayne County about 7.25 miles north northwest of Wisner, NE.","During the early morning hours of June 16th a warm, humid and unstable airmass rapidly returned to eastern Nebraska and western Iowa. As this air returned to the region, scattered thunderstorms developed during the early morning hours and continued into early afternoon. These thunderstorms were responsible for mainly large hail, some of which was very large. These morning thunderstorms reinforced a warm front across eastern Nebraska during the afternoon. Extreme instability developed along this warm front and allowed for isolated thunderstorm development by mid afternoon, which quickly become severe. A single supercell thunderstorm went on to produce 4 violent tornadoes over the next 2 hours. Other strong and severe thunderstorms moved into northeast Nebraska in the evening and continued into the early morning hours.",83
+514022,WAYNE CO.,ALTONA,06/16/2014,1537,Tornado, ,EF4,0,0,1500000,0,NE,CST-6, ,84971,C,179,OAX,0,0,NWS Storm Survey, ,4.72,500,4,E,8,E,ALTONA,42.0908,-96.931,42.122,-96.8492,"This is a continuation of the Pilger tornado that went through Stanton and Cuming into Wayne County. Once entering the county the tornado produced violent damage at two farmsteads where the houses were completely destroyed down to the foundation. The tornado finally started to narrow and weaken as a new tornado developed to the northeast. As this occurred the tornado narrowed and accelerated to the east northeast to the south of the new tornado before finally dissipating.","During the early morning hours of June 16th a warm, humid and unstable airmass rapidly returned to eastern Nebraska and western Iowa. As this air returned to the region, scattered thunderstorms developed during the early morning hours and continued into early afternoon. These thunderstorms were responsible for mainly large hail, some of which was very large. These morning thunderstorms reinforced a warm front across eastern Nebraska during the afternoon. Extreme instability developed along this warm front and allowed for isolated thunderstorm development by mid afternoon, which quickly become severe. A single supercell thunderstorm went on to produce 4 violent tornadoes over the next 2 hours. Other strong and severe thunderstorms moved into northeast Nebraska in the evening and continued into the early morning hours.",84
+514044,WAYNE CO.,ALTONA,06/16/2014,1540,Tornado, ,EF4,0,0,3000000,0,NE,CST-6, ,84971,C,179,OAX,0,0,NWS Storm Survey, ,9.79,530,7,ENE,2,E,WAKEFIELD,42.127,-96.8686,42.2646,-96.8235,"This tornado developed as the Pilger tornado was beginning to enter the rope stage. The Pilger tornado rotated around the south side of this developing tornado before completely dissipating. As this tornado moved north, along and to the east of State Highway 16 it grew in size and intensity. The tornado impacted numerous farmsteads along its path in eastern Wayne County producing varying degrees of damage, but the tornado was particularly violent in a two mile stretch between 853rd and 855th Roads where 4 houses were completely destroyed down to the foundation. The tornado also destroyed outbuildings, power poles, and debarked trees in these locations as well. The tornado became wrapped in rain as it moved to the east of Wakefield. The tornado entered Dixon County about 2.25 miles east of Wakefield.","During the early morning hours of June 16th a warm, humid and unstable airmass rapidly returned to eastern Nebraska and western Iowa. As this air returned to the region, scattered thunderstorms developed during the early morning hours and continued into early afternoon. These thunderstorms were responsible for mainly large hail, some of which was very large. These morning thunderstorms reinforced a warm front across eastern Nebraska during the afternoon. Extreme instability developed along this warm front and allowed for isolated thunderstorm development by mid afternoon, which quickly become severe. A single supercell thunderstorm went on to produce 4 violent tornadoes over the next 2 hours. Other strong and severe thunderstorms moved into northeast Nebraska in the evening and continued into the early morning hours.",85
+524717,JERAULD CO.,LANE,06/18/2014,1843,Tornado, ,EF4,0,2,300000,0,SD,CST-6, ,86902,C,73,FSD,0,0,NWS Storm Survey, ,11.26,880,2,SSE,2,NW,ALPENA,44.0372,-98.4032,44.1967,-98.4031,"A tornado severely damaged two family farms, including destroying a farmhouse as the family took shelter in their basement. A couple in the house suffered minor injuries.The tornado also damaged trees, power poles, and power lines; and caused an unknown amount of crop damage. The tornado crossed briefly into Beadle County before lifting.","Thunderstorms during the evening of June 18th produced tornadoes in Jerauld County, with one tornado crossing briefly into Beadle County. The tornadoes included one that caused severe damage to Wessington Springs. There was also a report of large hail.",86
+574337,OGLE CO.,CARTHAGE,04/09/2015,1743,Tornado, ,EF4,0,0,10000000,0,IL,CST-6, ,95584,C,141,LOT,0,0,NWS Storm Survey, ,20.94,700,5,ESE,3,E,MONROE CENTER,41.8886,-89.2381,42.0947,-88.9392,"This is the second segment of the Rochelle-Fairdale EF-4 tornado.  At its strongest, peak winds were estimated to be 200 mph which occurred during this segment of the storm.  The tornado entered Ogle County just west of IL-38 and moved northeast where it ripped the roof off of a small barn.  A neighborhood was hit on S Skare Court where damage was consistent with EF-3.  Some of the homes had large sections of the roofs ripped off while some less well constructed homes (nails instead of bolts) had collapsed walls.  The tornado continued northeast and intensified to EF-4 where several well constructed homes along South Richard Road and East Kuehl Court were completely destroyed with the slab swept clean.  Several outbuildings were destroyed along East Hemstock Road and South Center Road.  A residence on East Bethal Road received heavy damage with most of the outer walls collapsing.  The tornado once again intensified to EF-4  near IL-251 and IL-64 where well constructed homes were swept clean off their foundation.  A farmstead just northeast of the aforementioned intersection was also swept clean to the foundation.  A heavy barn was thrown and rolled on East Lindenwood Road.  In total, around 30 homes were damaged or destroyed around Rochelle.  The tornado continued into Dekalb County just north of East Quarry Road.  (Tornado 2b of 7).","Seven tornadoes were confirmed in north central Illinois in the NWS Chicago CWA.  Six of the tornadoes formed from a single supercell. The atmosphere was ripe for severe weather due to highly anomalous moisture and instability for early April across the region.  A strong low pressure system advanced into this favorable air mass. Combined with robust wind shear, this helped to trigger these potent storms.  A long tracked violent tornado destroyed numerous homes and farmsteads along its path across north central Lee, eastern Ogle, northwest Dekalb, and southern Boone counties.  This path included the far northwest side of Rochelle, Interstate-39, and a direct hit in the community of Fairdale where two fatalities occurred.  This was the strongest tornado in the NWS Chicago CWA since the F5 tornado that struck Plainfield, IL on August 28th, 1990.",87
+610234,TATE CO.,TYRO,12/23/2015,1610,Tornado, ,EF4,0,0,5000,0,MS,CST-6, ,102065,C,137,MEG,0,0,NWS Storm Survey, ,2.4,1300,1,NNW,3,SSE,WYATTE,34.5955,-89.7055,34.6131,-89.6691,"The tornado developed over Southeast Tate County. The tornado caused minor roof damage to a house in Tyro before moving into Marshall County.","Strong surface low pressure tracked from the Plains into the Mississippi River Valley while a strong cold front pushed into the Mid-South on December 23, 2015. A very moist and unstable airmass moved into the area as a warm front lifted north through the region during the early morning hours. A potent upper level disturbance help to trigger thunderstorms along and in advance of the approaching cold front. The necessary ingredients were in place for storm to rapidly intensify. Three tornadoes touched down across North Mississippi including an EF-4 that caused severe damage.",88
+610235,MARSHALL CO.,CHULAHOMA,12/23/2015,1612,Tornado, ,EF4,2,30,5000000,0,MS,CST-6, ,102065,C,93,MEG,0,0,NWS Storm Survey, ,25.14,1300,3,SW,5,ENE,HIGDON,34.6131,-89.6691,34.8117,-89.2983,"The tornado tracked into Marshall County from Tate County. As it moved into Marshall County the tornado heavily damaged several homes along Highway 4. The tornado produced damage to a church and surrounding trees southwest of Holly Springs that approached EF-4. The tornado moved across the southeastern edge of Holly Springs causing EF-2 to EF-3 damage. Numerous trees were uprooted or snapped. About 200 homes were damaged in Marshall County. Two fatalities occurred in Marshall County along with at least 30 injuries. The tornado then tracked into Benton County.","Strong surface low pressure tracked from the Plains into the Mississippi River Valley while a strong cold front pushed into the Mid-South on December 23, 2015. A very moist and unstable airmass moved into the area as a warm front lifted north through the region during the early morning hours. A potent upper level disturbance help to trigger thunderstorms along and in advance of the approaching cold front. The necessary ingredients were in place for storm to rapidly intensify. Three tornadoes touched down across North Mississippi including an EF-4 that caused severe damage.",89
+610236,BENTON CO.,ASHLAND,12/23/2015,1637,Tornado, ,EF4,6,1,1960000,0,MS,CST-6, ,102065,C,9,MEG,0,0,NWS Storm Survey, ,18.32,1300,7,W,2,SSE,HOPEWELL,34.8117,-89.2983,34.9428,-89.0174,"The tornado crossed from Marshall County into Benton County near Highway 4 west of Ashland. The tornado appeared to strengthen as it entered Benton County. Several houses west-northwest of Ashland has damage approaching EF-4 with EF-4 damage observed in Northeast Benton County. Six fatalities occurred in Benton County. Eighty-five structures were affected in Benton County. Seventeen homes and fifteen mobile homes were destroyed. Fifteen homes and three mobile homes suffered major damage. Twenty homes and seven mobile homes had minor damage. Many acres of timber were also damaged or destroyed. The tornado then continued into Tippah County.","Strong surface low pressure tracked from the Plains into the Mississippi River Valley while a strong cold front pushed into the Mid-South on December 23, 2015. A very moist and unstable airmass moved into the area as a warm front lifted north through the region during the early morning hours. A potent upper level disturbance help to trigger thunderstorms along and in advance of the approaching cold front. The necessary ingredients were in place for storm to rapidly intensify. Three tornadoes touched down across North Mississippi including an EF-4 that caused severe damage.",90
+610237,TIPPAH CO.,TIPLERSVILLE,12/23/2015,1656,Tornado, ,EF4,1,5,2500000,0,MS,CST-6, ,102065,C,139,MEG,0,0,NWS Storm Survey, ,7.83,1300,7,NW,0,SE,BROWNFIELD,34.9428,-89.0174,34.9958,-88.8952,"The tornado crossed from Benton County Mississippi into Tippah County. The tornado moved across far northwestern Tippah County damaging several homes in the Three Forks Community. One fatality occurred in Tippah County. Over 100 houses were affected and about 45 homes were destroyed. The tornado then crossed the Tennessee state line into Hardeman County.","Strong surface low pressure tracked from the Plains into the Mississippi River Valley while a strong cold front pushed into the Mid-South on December 23, 2015. A very moist and unstable airmass moved into the area as a warm front lifted north through the region during the early morning hours. A potent upper level disturbance help to trigger thunderstorms along and in advance of the approaching cold front. The necessary ingredients were in place for storm to rapidly intensify. Three tornadoes touched down across North Mississippi including an EF-4 that caused severe damage.",91
+610239,HARDEMAN CO.,POOR,12/23/2015,1703,Tornado, ,EF4,0,0,227000,0,TN,CST-6, ,102042,C,69,MEG,0,0,NWS Storm Survey, ,7.09,1300,2,S,2,E,POCAHONTAS,34.9958,-88.8952,35.0471,-88.7866,"The tornado crossed from Tippah County into Hardeman County. As it crossed over the state line it destroyed a large metal agricultural building. A couple of houses and businesses were also damaged. The tornado then moved into McNairy County.","Strong surface low pressure tracked from the Plains into the Mississippi River Valley while a strong cold front pushed into the Mid-South on December 23, 2015. A very moist and unstable airmass moved into the area as a warm front lifted north through the region during the early morning hours. A potent upper level disturbance help to trigger thunderstorms along and in advance of the approaching cold front. The necessary ingredients were in place for storm to intensify to severe limits. There were several reports of large hail, damaging winds and flash flooding across West Tennessee during the late afternoon. A violent long track tornado moved from into parts of Hardeman and McNairy Counties from North Mississippi during the early evening.",92
+611942,MCNAIRY CO.,CHEWALLA,12/23/2015,1711,Tornado, ,EF4,0,0,1230000,0,TN,CST-6, ,102042,C,109,MEG,0,0,NWS Storm Survey, ,14.31,1300,8,WNW,3,SE,SELMER,35.0471,-88.7866,35.1496,-88.5666,"The tornado moved into McNairy County from Hardeman County and began weakening. Around 15 homes were damaged or destroyed south of Selmer. The last observed damage was near Highway 45 on the southeast edge of Selmer.","Strong surface low pressure tracked from the Plains into the Mississippi River Valley while a strong cold front pushed into the Mid-South on December 23, 2015. A very moist and unstable airmass moved into the area as a warm front lifted north through the region during the early morning hours. A potent upper level disturbance help to trigger thunderstorms along and in advance of the approaching cold front. The necessary ingredients were in place for storm to intensify to severe limits. There were several reports of large hail, damaging winds and flash flooding across West Tennessee during the late afternoon. A violent long track tornado moved from into parts of Hardeman and McNairy Counties from North Mississippi during the early evening.",93
+606471,DALLAS CO.,NEW HOPE,12/26/2015,1846,Tornado, ,EF4,10,468,26000000,0,TX,CST-6, ,101364,C,113,FWD,0,0,NWS Storm Survey, ,9.21,550,2,SSE,3,ENE,ROWLETT,32.796,-96.5894,32.915,-96.518,"The Garland and Rowlett tornado began in Sunnyvale, where several mobile homes were destroyed along a wide and long path.  The full tornado length was a little over 13 miles, with nearly ten miles within Dallas County. Nine people lost their lives in vehicles as the tornado crossed Interstate 30 at the President George Bush Turnpike. Another male died after sustaining injuries in a collapsed home in Rowlett. Eight of the 10 died that night, but one died on January 8th from his injuries, and another passed away on January 18th.  The tornado affected nearly 600 homes in Dallas County, destroying nearly 400 of these homes. Twenty-two businesses were affected by this tornado, with one business being completely destroyed.","A potent storm system brought deadly tornadoes and severe weather to North Texas on the 26th followed by waves of heavy rainfall that resulted in significant flooding across parts of North and Central Texas.  Twelve tornadoes were confirmed on the afternoon and evening of the 26th, killing 13 and injuring over 300. The strongest tornado was an EF-4 that struck the Garland and Rowlett areas of Dallas and Rockwall County and where most of the fatalities occurred. Then the waves of heavy rain persisted through the night of the 27th until the upper level low moved past the region. The heaviest rainfall and thus most significant flooding was along and east of Interstate 35 where an average of 3-6+ of rain fell.",94
+633058,GARVIN CO.,HENNEPIN,05/09/2016,1506,Tornado, ,EF4,1,0,1000000,0,OK,CST-6, ,104767,C,49,OUN,0,0,NWS Storm Survey, ,8.9,400,3,N,5,SW,WYNNEWOOD,34.559,-97.357,34.589,-97.21,"A tornado developed 1.25 miles south of the community of Katie, OK, or about 3.4 miles north of Hennepin. The tornado was observed to be very dynamic as it moved east-northeast and east. Initially damage was confined to trees until the tornado crossed county road 1690 where a home was destroyed where only interior walls remained standing. To the east of this house, two mobile homes were damaged on the southern periphery of the tornado path. The tornado moved east-northeast damaging another mobile home, then east removing the roof from a home on Indian Meridian Road.||The tornado varied in movement between northeast and southeast as it approached and crossed county road 1680. A home was destroyed near county road 1680 and Indian Meridian Road where an EF4 rating was applied (DI 2, DOD 9). Further east, a fatality occurred when the tornado destroyed a modular home. After destroying another home, the tornado moved northeast and dissipated near Interstate 35.","With the help of an upper low, storms fired along the dryline in central Oklahoma on the 9th, with some of them becoming severe.",95
+626912,DICKINSON CO.,SOLOMON,05/25/2016,1820,Tornado, ,EF4,0,5,0,0,KS,CST-6, ,104664,C,41,TOP,0,0,NWS Storm Survey, ,21.61,900,5,N,3,ESE,CHAPMAN,38.9917,-97.3713,38.9557,-96.9717,"The long track violent tornado began 1-2 miles NNE of Niles Kansas and destroyed 2 homes in Ottawa county before crossing into Dickinson county north of Solomon.  The tornado tracked 2-3 miles north of the city of Abilene following a meandering path approximately east along 2700 avenue in Dickinson county before veering southeast and crossing interstate 70 approx. 2 miles west of the city of Chapman.  The tornado then moved ESE and then east along a path around 1 mile south of Chapman destroying 1 farmstead and several other homes in the area.  The worst damage was done to a farmstead 1 mile southwest of Chapman along old highway 40 where the home was destroyed and all outbuildings were blown away.  The sub floor of the home was removed from a bolted sill plate and the poured concrete foundation was cracked on the south side exposing the rebar where the strongest forces from the lifting structure occurred as it was being removed and blown away likely occurred.  Much of the brick facade of the home did remain where it fell around the structure however so the area was not swept clean. Winds approaching 200 mph were likely in this area while a woman home at the time took shelter in the basement and was ok with only superficial injuries.  The approximate number of minor injuries was 5 reported to NWS however none required a hospital visit.  Photos of the damage are available off of the NWS damage assessment toolkit website at https://apps.dat.noaa.gov/StormDamage/DamageViewer/ .","One supercell thunderstorm developed over Ottawa county around 5pm on May 25th. That storm went on to produce 4 documented tornadoes including a 26 mile long violent EF4 tornado that was on the ground for around 90 minutes.  Most of the damage was done in Dickinson County Kansas where 20-25 homes were damaged or destroyed. The supercell thunderstorm continued into Morris and Wabaunsee counties where it produced 2 more tornadoes before dissipating that evening.",96
+677516,PERRY CO.,SILVER LAKE,02/28/2017,1951,Tornado, ,EF4,1,12,8000000,0,MO,CST-6, ,113236,C,157,PAH,0,0,NWS Storm Survey, ,17.39,1100,3,N,4,E,BELGIQUE,37.7238,-90.0055,37.8222,-89.7124,"This large and violent tornado touched down about four miles west of Perryville. The tornado quickly became violent, reaching EF-4 intensity and leveling five homes just west of Interstate 55, about 3.5 miles northwest of Perryville. Numerous unoccupied cars from a salvage yard were blown into or over Interstate 55. The lone fatality occurred when a southbound vehicle on Interstate 55 was intercepted by the tornado. The victim's pickup truck was tossed into a field at least 100 yards from the interstate. The coroner reported that the victim was thrown from the vehicle and died at the scene. The passenger in the vehicle was treated for minor injuries at a local hospital. The area of greatest home and property destruction was three miles north of Perryville, in the vicinity of U.S. Highway 61. Maximum wind speeds were estimated near 180 mph in the vicinity of Interstate 55 and also near U.S. Highway 61. The damage path showed multiple vortex characteristics with ground striations and scarring to bare ground. At least 100 homes were damaged or destroyed in Perry County, mostly on the northern outskirts of Perryville. Most persons in the tornado's path took shelter in their basements. All twelve tornado injuries occurred in Perry County, where the tornado was at its strongest. At least one couple was trapped in their basement until rescuers removed debris. As the tornado approached the Mississippi River, multiple ground striations were noted in a farm field, indicative of multiple vortices. The maximum path width was over one-half mile shortly before the tornado crossed the Mississippi River into Randolph County, Illinois.","Isolated supercell thunderstorms developed across southeast Missouri during the evening hours. The storms developed ahead of a cold front in a destabilizing air mass characterized by dew points in the lower to mid 60's. The most intense supercell storm awaited the approach of a mid-level impulse from Oklahoma, which was downstream from the primary shortwave trough over the southern Plains. The supercell produced a violent tornado in Perry County. A southwesterly low-level jet increased substantially during the evening, creating favorable conditions for tornadoes. Outside of the thunderstorm activity, some of the southwest winds aloft mixed down to the surface in the form of isolated gusts from 40 to 45 mph.",97
+683249,VAN ZANDT CO.,BIG ROCK,04/29/2017,1640,Tornado, ,EF4,2,20,700000,200000,TX,CST-6, ,114098,C,467,FWD,0,0,NWS Storm Survey, ,13.6,1760,1,NNW,2,NE,WALLACE,32.357,-95.9549,32.5528,-95.9306,"The Henderson County tornado continued into Van Zandt County. A National Weather Service damage survey crew found the start of tornado number three began in Henderson County, approximately 3 miles due south of Eustace. This tornado eventually moved into Van Zandt County, where the storm produced EF4 damage. In  Henderson County, several homes suffered EF2 damage, along with a considerable amount of tree damage and damage to farm buildings. As the storm moved into Van Zandt County, the tornado  grew to a mile wide at the tornado's maximum width. Over 50 homes were either damaged or destroyed, with a continuous path noted between counties.","A deep low pressure system near the Four corners continued to move east, causing early morning thunderstorms to develop along the Texas Panhandle and into Oklahoma. A cold front was moving southeast across the state and entered our northwestern|counties around sunrise. The strength of the cap was sufficient to hamper any development until mid afternoon. Deep forcing for ascent approached from from the west while remnant boundaries associated with convection over far East Texas and West Louisiana moved in from the east. By 3:30 PM, several parameters came together for the rapid development of severe storms east of Interstate 35/35E. Pre-frontal convection led to the development of supercells, producing numerous tornadoes over a relatively small area. Additional storm development quickly developed along the cold front with several reports of large hail, and eventually producing a brief EF-0 Quasi-Linear Convective System (QLCS) tornado (Tornado #7). ||The survey crew teams determined yesterday that there was a nearly 55 mile damage swath, yet found evidence that there were two tornadoes which caused the damage. One tornado began in western Henderson County and moved into central Van Zandt County. This tornado occluded and dissipated, and a second, long track tornado began nearby. This second tornado was the EF-3 which produced damage on the east side of Canton, Fruitvale, Emory, and finally dissipating near Lake Fork. The first tornado had|a track of approximately 12 miles, while the other had a track of nearly 42 miles. ||It is known that four people lost their lives due to these tornadoes, and 59 people were injured.",98
+813640,LEE CO.,BUPREE,03/03/2019,1403,Tornado, ,EF4,23,90,0,0,AL,CST-6, ,135611,C,81,BMX,0,0,NWS Storm Survey, ,23.55,1600,5,W,1,NW,STONEWALL,32.4571,-85.4362,32.575,-85.057,"National Weather Service meteorologists surveyed damage in far southern Lee County and determined that it was consistent with an EF4 tornado, with maximum sustained winds near 170 mph.||This track is a continuation of a track that began in Macon County. The tornado crossed into Lee County near Lee Road 812 and tracked northeast to County Road 29 where it removed the roof and collapsed several cinder block walls of a church. The tornado continued to intensify as it approached County Road 11, where it peeled sheet metal off of the porch of a home and ripped some sheet metal off of two outdoor storage sheds and continued to uproot numerous pine trees. Debris from structures and their contents were strewn along a tree line to the east of their original location and some evidence of weak ground rowing was observed along the surface tornado path.||The tornado reached its peak intensity just south of the intersection of Lee County Road 36 and Lee County Road 39, where it rolled a manufactured home and emptied its contents nearby on the northern side of the track. Additional damage toward the southern portion of the track included the complete destruction of a house with all debris tossed a short distance from the foundation. The tornado bent the frame of a car around the remnant of a large tree whose upper portion had broken off and totaled three vehicles by severe impacts into the bases of two remaining tree stubs. Farther east on the other side of a small lake, a well-anchored and constructed home was leveled with debris removed from the foundation and anchored bolt screws remaining intact. Toward the northern edge of the tornado, the destruction of two double-wide and a single-wide manufactured home was observed. This was the peak intensity of the tornado due to the combination of damage to the two houses along with extensive severe tree damage including trees snapped at their bases and large trees with expansive root systems uprooted along with some sporadic evidence of ground rowing.||The tornado began to decrease in intensity as it continued east roughly paralleling Lee County Road 39 where two manufactured homes were destroyed with most debris deposited away from the original location and both of the metal frames of the mobile homes could not be located. Another manufactured home was destroyed with its contents deposited in a swath from the site into the remains of a nearby tree line. A car was found in an overturned position against a hardy tree stripped of most limbs with a mattress from a bed wrapped around the mid portion of the tree. A badly mangled metal frame of a manufactured home and debris displaced nearby was all that remained of one residence. Nearby a tractor trailer rig was on its side and shoved around a sturdy tree while a nearby site-built home lost nearly all of its exterior walls with debris remaining on or near the home site. Severe tree destruction continued in this area with trees snapped at their bases and uprooted. To the north of Lee County Road 39, significant debris was deposited in a wooded area where the tornado performed significant timber damage and toppled at least one high-tension power line tower.||After demolishing two double-wide and a single-wide manufactured home the tornado tracked northeast and crossed Lee County Road 51 just north of the intersection with Lee County Road 39. A double-wide manufactured home was moved off of its base and the exterior walls collapsed on a family residence along with significant tree damage.|Some weakening occurred farther east as the tornado crossed Lee County Road 38 where it deposited a large amount of debris into a ragged forested area. The tornado crossed Lee County Road 100 and Lee County Road 166 where it caused damage to trees with some trunks snapped and some trees uprooted.||Tornado damage was observed along Lee County Road 165 and along portions of Lee County Road 40 and Lee County Road 2049. Exterior walls of a family residence were removed and a significant loss of roofing material from a house and a manufactured home were observed. The tornado flipped a manufactured home and deposited its contents nearby along with destroying the roof and walls of a single-wide manufactured home.||The tornado crossed Lee County Road 170 and County Road 175, and then Highway 169 with significant damage to timber along this path. The tornado crossed Lee County Road 245 and Lee County Road 179 with damage to the roof of a house near County Road 239 along with more timber damage. As it approached Smiths Station, the tornado crossed Fullers Lake where it rolled a manufactured home and caused some loss of roofing material to a house. Additional damage occurred along Lee County Road 294 and Lee County Road 298 where a professional building lost some of its roofing materials. Damage also occurred to siding and roofing at several small homes that were not well constructed. As the tornado crossed U.S. Highway 280 it caused some roof damage to a restaurant, damaged a billboard and collapsed a cellular service communications tower. The tornado moved across Lee County Road 318 where some roof damage to homes occurred along with significant timber damage. The tornado moved tracked towards the Chattahoochee River where it caused roof damage to some houses near the river and downed a metal high-tension power line tower. The tornado crossed the Chattahoochee River and continued into Georgia.||There were 23 fatalities and 90 injuries. The American Red Cross estimated 225 homes were destroyed, while another 133 homes sustained major damage.","On the morning of Sunday March 3rd, 2019, an upper-level disturbance moved eastward from the Southern Plains into the southern Gulf Coast States. As favorable upper-level support and deep-layer forcing approached the lower Mississippi River Valley, a surface low pressure developed and moved northeastward into Central Alabama by late morning. Ahead of this surface low, a warm front initially along the Florida Panhandle moved northward allowing for the transport of warm, moist unstable air into southern and southeastern Central Alabama. This frontal boundary eventually became more stationary and stalled out north of the I-85 corridor as the strengthening surface low moved eastward. During this time, a large area of elevated thunderstorms affected portions northern Central Alabama while supercell thunderstorms initiated across the favorable warm sector. As these supercells intensified during the afternoon, parameters became favorable for tornadic thunderstorms in an area along and south of the I-85 corridor.",99
+816403,MONTGOMERY CO.,PYRMONT,05/27/2019,2141,Tornado, ,EF4,0,166,500000000,0,OH,EST-5, ,136052,C,113,ILN,0,1,NWS Storm Survey, ,18.17,1050,2,NNW,1,SSE,EASTVIEW,39.8243,-84.4632,39.758,-84.1121,"The tornado initially touched down just west of Brookville and areas on the south side of Brookville sustained heavy damage, consistent with high-end EF2 wind speeds. Numerous homes suffered significant roof damage and removal, including exterior wall collapse and complete garage destruction. ||The tornado then carved a path east through Trotwood where damage consistent with EF2 wind speeds was widespread and some homes sustained damage consistent with EF3 wind speeds. Structures here again featured roof removal and exterior wall collapse. This was particularly true on the south side of Westbrook Road. A large number of homes and apartment complexes were impacted further east in Trotwood, with most of this damage consistent with high-end EF2 wind speeds.||The highest winds were estimated to have occurred in a corridor from eastern Trotwood (between Shiloh Springs Road and Westbrook Road), then southeast between Shiloh Springs Road and Turner Road, into areas along the Stillwater River/Riverside Drive area. Embedded within this zone was higher-end EF3 damage. Areas near Riverside Drive and the Stillwater River exhibited damage consistent with wind speeds of 170 mph, or lower-end EF4 damage. This damage included well-built apartment buildings that sustained complete roof and exterior wall removal. In addition, significant tree devastation was found along the Stillwater River, east of Riverside Drive, that included numerous trees that were debarked and nubbed down to the trunk.||The tornado continued southeast through Dayton and Northridge, and crossed I-75 into the Old North Dayton Area, where heavy damage continued to homes and businesses. As the tornado entered Riverside, damage began to lessen in intensity, but plenty of damage consistent with EF1 wind speeds was noted. The tornado continued further to the southeast, causing damage in a subdivision north of Burkhardt Road. The roof of an apartment building on Dodge Court was removed. This is the final known damage caused by this tornado.||An 86 year old woman died (indirect) on September 1st, 2019, in part due to injuries suffered when she was trapped in her home during the tornado.","Thunderstorms developed during the evening hours along a warm front lifting slowly north across the region. Many of the thunderstorms produced tornadoes, including a few strong to violent tornadoes.",100
+830798,LEAVENWORTH CO.,LINWOOD,05/28/2019,1732,Tornado, ,EF4,0,0,26000000,0,KS,CST-6, ,138233,C,103,EAX,0,0,NWS Storm Survey, ,12.41,1760,5,WSW,3,S,BASEHOR,38.9689,-95.108,39.0807,-94.927,"This tornado is a continuation of the tornado that formed in Douglas County and crossed the Kansas River into Leavenworth County. As the tornado crossed the Kansas River it became very strong and wide. It produced EF-3 damage to residences along the Kansas River. When the tornado impacted Linwood, Kansas it produced isolated EF-3 and EF-4 damage. Preliminary estimates for damage exceeded 26 million dollars, per the Leavenworth Times ( https://www.leavenworthtimes.com/news/20190531/tornado-damage-exceeds-26-million ). Despite the EF-4 rating and widespread devastation to rural areas near Lawrence and Linwood no serious injuries occurred. This was the strongest tornado to impact the Kansas City metro area since 2003.","In the evening of May 28 a strong tornado formed in Douglas County and grew to a wide EF-4 tornado. This is the same storm that caused the storm chasing group to fly off the road just south of Lawrence, Kansas. Once the tornado crossed into Leavenworth County it impacted mainly rural residences, but also impact the city of Linwood. It was here that isolated EF-3 and EF-4 damage was noted. The tornado continued on to the Bonner Springs area before it dissipated just southwest of Kansas Speedway and I-70.",101
+883016,PUTNAM CO.,ENSOR,03/03/2020,148,Tornado, ,EF4,19,87,100000000,0,TN,CST-6, ,146901,C,141,OHX,0,0,NWS Storm Survey, ,8.39,900,1,W,1,W,COOKEVILLE,36.1715,-85.6628,36.1709,-85.5135,"An historic, violent EF-4 tornado began in western Putnam County northwest of Baxter and tracked eastward for over 8 miles before lifting near downtown Cookeville, damaging or destroying dozens of homes and businesses, killing 19 people, and injuring 88 others. The tornado began 2.5 miles northwest of Baxter along Highway 70 where it caused EF-0 damage to several homes and outbuildings. Scattered trees were blown down as the tornado continued eastward across Gainesboro Highway. The tornado quickly intensified to EF-2 in the Prosperity Pointe subdivision just north of Highway 70 and further strengthened to EF-3 as it crossed Bloomington Road and Clemmons Road in the Double Springs community, severely damaging several homes. As the tornado moved across Charleston Square, Plunk Whitson Road, and North McBloom Chapel Road, it intensified even more and produced a 0.8 mile long by 100 yards wide swath of EF-4 damage. 17 well-constructed, large homes in this area were completely leveled, mostly on Hensley Drive, with many deaths occurring in this area. EF-4 damage continued eastward to Echo Valley Drive, where an apartment complex and 5 more homes were completely destroyed. The tornado weakened to EF-3 as it crossed Highway 70 and Locust Grove Road, where numerous more homes and buildings were damaged or destroyed. A dashcam video of the tornado was taken from an unoccupied vehicle on Willow Brook Drive in this area. Continuing along Highway 70, the tornado weakened further to EF-2 intensity as it crossed County Farm Road and Jackson Street, then down to EF-1 strength along Crescent Drive and Buck Avenue. The tornado rapdily dissipated as it entered the downtown area of Cookeville, quickly lifting on Laurel Avenue just west of Cookeville Regional Medical Center. This was the worst tornado on record to affect Putnam County.","From the late evening hours on March 2 into the early morning hours on March 3, supercell thunderstorms developed and spawned tornadoes across southeast Missouri, southern Kentucky, Tennessee, and central Alabama. One of these supercells formed near the Mississippi River in west Tennessee, then tracked eastward across the entire length of the state just north of the Interstate 40 corridor, spawning 10 tornadoes and dropping large hail bigger than the size of baseballs. Seven of these tornadoes touched down across Middle Tennessee, resulting in widespread damage, 307 injuries and 24 fatalities. An additional fatality and 2 more injuries occurred in Benton County in west Tennessee. These tornadoes were the worst seen in Tennessee since the devastating tornadoes of April 27, 2011 across east Tennessee, as well as the Super Tuesday tornadoes of February 5-6, 2008. Total damage estimates from the Tennessee Emergency Management Agency across Middle Tennessee reached $1.6 billion.",102
+887908,WALTHALL CO.,ENON,04/12/2020,1439,Tornado, ,EF4,2,0,0,0,MS,CST-6, ,147593,C,147,LIX,0,0,NWS Storm Survey, ,6.65,1300,4,ESE,2,E,SARTINSVILLE,31.2763,-90.1732,31.3331,-90.0822,"The tornado touched down near Jefferson Rd just east of the intersection with|Jack Foil Rd. It quickly strengthened as it moved northeastward through the Hope area where it produced damage consistent with 115 mph winds. It also quickly grew in width and was roughly 1200 yd/0.67 mi wide by the time it approached Hwy 27. As it crossed Hwy 27 it continued to cause significant damage along East Sartinville Rd. The tornado was strongest as it approached James Ratcliff Rd. Two homes on this road were leveled, one being reduced to a slab. Consultation with subject matter experts including both engineers and experts in forensic tornado damage  analysis supports raising the maximum intensity to 170 mph based  on the house that was reduced to a slab and a large hard wood tree that was uprooted and tossed several feet from where it stood. The increased wind speed makes the tornado an EF-4 on the Enhanced Fujita scale. The other home that was leveled suffered damage consistent with a high end EF-3. While all walls were collapsed, there was no evidence of bolts that would have held the sill plates to the foundation. Thus, the wind speed for this particular damage is reduced slightly from the expected. The tornado was also widest in this area, reaching a maximum width of around 1300 yards or approximately 0.75 miles. As it continued to move northeastward, it continued snapping every tree near the center of its path. It also caused substantial damage to several small cinder block buildings, tore the roof off of a home and rolled a tied down single-wide manufactured home as it crossed East Sartinville Rd. From there it continued northeastward and tore the entire roof from a brick home just before moving into Lawrence County. It should be noted that from just southwest of James Ratcliff Rd through the remainder of the Walthall Co portion of  the track, nearly every tree in the path of the tornado was snapped or uprooted. The tornado was responsible for two fatalities in Walthall County.","On April 12th 2020, a very potent storm system delivered widespread severe weather across the southeast, as a strong cold front met unstable, moist Gulf air causing severe storms across Mississippi.",103
+902831,JEFFERSON DAVIS CO.,BASSFIELD,04/12/2020,1512,Tornado, ,EF4,4,4,18000000,2500000,MS,CST-6, ,146307,C,65,JAN,0,0,NWS Storm Survey, ,9.99,2640,3,S,7,ESE,TERRELL,31.4641,-89.7579,31.5475,-89.6194,"This violent, deadly tornado traveled 68 miles through parts of five counties including southeastern Jefferson Davis, central Covington, northwestern Jones, southeastern Jasper, and western Clarke counties. Locations impacted by this tornado include Bassfield, the areas between Collins and Seminary, Soso, Moss, Heidelberg, and Pachuta. This tornado is preliminarily rated EF4 with an estimated peak wind of 190 MPH east of Bassfield in southwestern Jefferson Davis County. Additional EF4 damage was noted near Soso in Jones County and at Moss in Jasper County. The maximum path width was 2.25 miles in the vicinity of Hughes Road west of Seminary in western Covington County. At this width, the tornado ranks 3rd widest in the official NOAA United States tornado database behind the El Reno, OK tornado of 2013 (2.6 mi) and the Hallam, NE tornado of 2004 (2.5 mi). This tornado now ranks as the widest on record in the state of Mississippi, surpassing the Yazoo City, MS tornado of 2010 (1.75 mi). Eight lives were lost in this tornado, and there was an undetermined number of additional injuries. Additional details on the damage path and area of most significant damage follow.|| ||The tornado began south of Bassfield along Bassfield Cemetery Road, uprooting trees and resulting in relatively minor structural damage. As it proceeded northeastward, the diameter of the wind field steadily increased and the percentage of snapped trees in the center of the vortex increased considerably as the tornado approached MS Highway 42. At this location, two homes sustained major roof damage. Tornado intensity then began to increase quickly, with EF3 damage as it crossed Hosey Mikell Road, completely demolishing a mobile home and scattering the debris field over 300 yards downwind. Tree damage also ramped up significantly beyond this location, with low end EF4 damage in a narrow swath of nearly complete tree destruction along the center of the tornado vortex and increasing instances of debarking of trees as the tornado moved across Pitts Lane and Reese Road. Outside of this most intense corridor of tornadic winds, EF1 and EF2 damage to trees and structures was occurring over a wider area, up one mile wide. In addition, both ground surveys and aerial photography indicated the presence of multiple vortices at times. Intense damage continued as the tornado crossed the intersection of Graves Key Road and Harper Road, where a cinder block small business building was destroyed, with much of the slab swept clean. Four fatalities occurred at this location. Nearby, a mobile home was completely destroyed, with the undercarriage wrapped around the small set of trees that remained standing downwind. Debarking of some trees was again noted and continued along the tornado path across Claude Booth Road.|| ||The tornado reached its peak intensity as it moved across a field north of Graves Key Road. At this location, the foundation of a wood frame and metal roof cabin was swept clean. A truck parked at this cabin was tossed approximately 300 yards downwind, and trees that remained standing at this site were partially debarked. Though the path of the intense tornado vortex through the field surrounding this cabin was clearly visible, significant scouring was not noted. The tornado continued to remain violent and grow in size, nearly 1.5 miles wide, as it crossed Good Hope Road and continued to track toward the Bouie River. Here, a large swath of extreme tree damage was noted as the whole forest was leveled. An intense core of the tornado was evident by debarking of trees along a well defined center line or sub-vortex feature. Extreme debarking was noted around Willie Fortenberry Road. In this general area, several farmers reported roughly 60 cattle were killed by the tornado. The tornado grew larger as it entered Covington County and peaked in width in the vicinity of Hughes Road. Maximum width was measured at 2.25 miles. The incredible expansive tree damage continued along the path with millions of trees damaged. Several dozen structures were damaged or destroyed between McGowen Circle to US 49. Numerous chicken houses (23-30) were destroyed here as well. A section of Cold Springs Road looked to see another sub- vortex and it was here another area of EF4 damage occurred to a home.|| ||As the tornado crossed US 49, the width decreased to 1.7 miles, but it remained quite strong with mid to upper end EF3 damage noted. Extreme tree damage persisted in large swaths along the path. In addition, a few dozen structures were damaged between US 49 and MS Highway 588. This consisted of varying degrees of damage from EF1 to EF3 levels. The tornado entered northwestern Jones County near the Centerville community where several homes had shingles blown off or parts of the decking exposed. A mobile home along Tommy Pickering Road was thrown and separated from the frame, with the highest winds in the EF2 range. As the storm moved northeast across US 84, trees were uprooted and snapped. Several homes on both sides of the highway had decking exposed or shingles blown off. At least one mobile home was destroyed along US 84. The tornado intensified to an EF3 causing significant damage to multiple homes along Danny Hillburn Road, where large sections of roofing was removed. Between US 84 and MS Highway 29, several mobile homes were completely destroyed and at least one separated from the frame. Several homes had one or more exterior walls collapsed or large sections of the roof removed. The tornado continued to cause widespread destruction as it moved into the town of Soso. Several homes and churches received significant damage. Large swaths of trees were snapped and uprooted along MS Highway 29. Near the center of town, a fire station was heavily damaged when the overhead doors collapsed and portions of the roof were removed. Numerous homes had roofing removed and exposed decking. The worst damage occurred along MS Highway 28 where a convenience store was destroyed and several other cinder block structures were heavily damaged when the storm intensified to low end EF-4. The tornado continued to mow down large swaths of trees and caused major uplift and loss of roofing to numerous homes as it moved northeast toward MS Highway 15. Along Mathews Road numerous mobile homes and several outbuildings were completely destroyed.|| ||The tornado intensified to a low end EF4 as it moved into the Moss community, where winds near 175 mph resulted in widespread devastation. Nearly every structure in the community was damaged with the most significant damage occurring along or near MS Highway 537. About half of the First Baptist Church of Moss was completely leveled. Numerous homes were destroyed or had major roofing loss or uplifted. A small pick-up truck was thrown several hundred yards and completely destroyed. In addition, multiple mobile homes were completely demolished.|| ||As the storm tracked toward I-59 a few miles west of Heidelberg, hundreds of trees were mowed down, outbuildings were destroyed. Several homes and mobile homes had metal roofing peeled back or decking exposed. Large swaths of trees were snapped for several miles including some along I-59 between the Heidelberg and Vossburg exits. Swaths of tree damage continued into the Barnett community. In the town of Pachuta there was scattered tree damage and the metal roofing was peeled off of a church. About two miles north of Pachuta, the damage became sporadic and the tornado lifted in a wooded area along County Road 130.||The total path length was 67.43 miles. The maximum estimated wind speed of both the tornado and in Jefferson Davis County was 190mph.","An outbreak of severe weather occurred on Easter Sunday, 2020. This was a multifaceted event with a few different waves of activity, each of which brought their own unique hazardous weather to the residents of the region. This outbreak had a total of 20 tornadoes across the NWS Jackson service area. Of these, two tornadoes were long tracked and in excess of 60 miles. Additionally, the most intense tornado was historically significant as it was the widest tornado in Mississippi history at 2.25 miles and ranks as the third widest nationally. Unfortunately, fatalities occurred across the region, most of which came from the two long track tornadoes. Total fatalities were 14, which were across several counties and almost 100 people were injured. Of the 20 tornadoes, two were rated as EF4, one was an  EF3, four were EF2, ten were EF1 and there were three EF0.||The first wave of severe storms moved out of northeast Louisiana as a line of thunderstorms or QLCS. The bowing segment of this line was efficient at producing tornadoes as it moved across northeast Louisiana parishes and through central sections of Mississippi before tracking across Alabama. This part of the QLCS produced 13 tornadoes across the service area with the strongest being three EF2s that occurred west of Pioneer LA, northwest of Yazoo City MS, and north of Macon MS.||The next wave was focused around two large supercell storms where each produced long track tornadoes, and were the phenomena that had the greatest impact across south and southeast Mississippi. The first storm produced two EF4 tornadoes, one of which was on the ground for 68 miles before dissipating. This tornado was up to two miles wide in several locations, with the maximum width at 2.25 miles making it the widest tornado in Mississippi history. On the heels of this supercell, another supercell developed and produced a long track EF3 tornado, which was on the ground for 84 miles.||The third and final wave was associated with the southeast surge of the cold front and driven by the strong lift and winds from the core of the upper level low. This wave was a bit unique as there were not as many thunderstorms associated with the line of strong and damaging winds. However, this line of activity produced widespread wind damage across southeast Arkansas, northeast Louisiana and all of the northern half of Mississippi, including the Mississippi Delta where winds of 70 to 90 mph occurred. While many structures sustained some sort of damage, widespread trees and power lines were blown down during the late evening and early morning hours with the final wave.",104
+902837,COVINGTON CO.,WILLIAMSBURG,04/12/2020,1524,Tornado, ,EF4,0,5,25900000,3600000,MS,CST-6, ,146307,C,31,JAN,0,0,NWS Storm Survey, ,15.27,3960,5,S,5,SSE,HOT COFFEE,31.5475,-89.6194,31.6661,-89.4004,"This violent, deadly tornado traveled 68 miles through parts of five counties including southeastern Jefferson Davis, central Covington, northwestern Jones, southeastern Jasper, and western Clarke counties. Locations impacted by this tornado include Bassfield, the areas between Collins and Seminary, Soso, Moss, Heidelberg, and Pachuta. This tornado is preliminarily rated EF4 with an estimated peak wind of 190 MPH east of Bassfield in southwestern Jefferson Davis County. Additional EF4 damage was noted near Soso in Jones County and at Moss in Jasper County. The maximum path width was 2.25 miles in the vicinity of Hughes Road west of Seminary in western Covington County. At this width, the tornado ranks 3rd widest in the official NOAA United States tornado database behind the El Reno, OK tornado of 2013 (2.6 mi) and the Hallam, NE tornado of 2004 (2.5 mi). This tornado now ranks as the widest on record in the state of Mississippi, surpassing the Yazoo City, MS tornado of 2010 (1.75 mi). Eight lives were lost in this tornado, and there was an undetermined number of additional injuries. Additional details on the damage path and area of most significant damage follow.|| ||The tornado began south of Bassfield along Bassfield Cemetery Road, uprooting trees and resulting in relatively minor structural damage. As it proceeded northeastward, the diameter of the wind field steadily increased and the percentage of snapped trees in the center of the vortex increased considerably as the tornado approached MS Highway 42. At this location, two homes sustained major roof damage. Tornado intensity then began to increase quickly, with EF3 damage as it crossed Hosey Mikell Road, completely demolishing a mobile home and scattering the debris field over 300 yards downwind. Tree damage also ramped up significantly beyond this location, with low end EF4 damage in a narrow swath of nearly complete tree destruction along the center of the tornado vortex and increasing instances of debarking of trees as the tornado moved across Pitts Lane and Reese Road. Outside of this most intense corridor of tornadic winds, EF1 and EF2 damage to trees and structures was occurring over a wider area, up one mile wide. In addition, both ground surveys and aerial photography indicated the presence of multiple vortices at times. Intense damage continued as the tornado crossed the intersection of Graves Key Road and Harper Road, where a cinder block small business building was destroyed, with much of the slab swept clean. Four fatalities occurred at this location. Nearby, a mobile home was completely destroyed, with the undercarriage wrapped around the small set of trees that remained standing downwind. Debarking of some trees was again noted and continued along the tornado path across Claude Booth Road.|| ||The tornado reached its peak intensity as it moved across a field north of Graves Key Road. At this location, the foundation of a wood frame and metal roof cabin was swept clean. A truck parked at this cabin was tossed approximately 300 yards downwind, and trees that remained standing at this site were partially debarked. Though the path of the intense tornado vortex through the field surrounding this cabin was clearly visible, significant scouring was not noted. The tornado continued to remain violent and grow in size, nearly 1.5 miles wide, as it crossed Good Hope Road and continued to track toward the Bouie River. Here, a large swath of extreme tree damage was noted as the whole forest was leveled. An intense core of the tornado was evident by debarking of trees along a well defined center line or sub-vortex feature. Extreme debarking was noted around Willie Fortenberry Road. In this general area, several farmers reported roughly 60 cattle were killed by the tornado. The tornado grew larger as it entered Covington County and peaked in width in the vicinity of Hughes Road. Maximum width was measured at 2.25 miles. The incredible expansive tree damage continued along the path with millions of trees damaged. Several dozen structures were damaged or destroyed between McGowen Circle to US 49. Numerous chicken houses (23-30) were destroyed here as well. A section of Cold Springs Road looked to see another sub- vortex and it was here another area of EF4 damage occurred to a home.|| ||As the tornado crossed US 49, the width decreased to 1.7 miles, but it remained quite strong with mid to upper end EF3 damage noted. Extreme tree damage persisted in large swaths along the path. In addition, a few dozen structures were damaged between US 49 and MS Highway 588. This consisted of varying degrees of damage from EF1 to EF3 levels. The tornado entered northwestern Jones County near the Centerville community where several homes had shingles blown off or parts of the decking exposed. A mobile home along Tommy Pickering Road was thrown and separated from the frame, with the highest winds in the EF2 range. As the storm moved northeast across US 84, trees were uprooted and snapped. Several homes on both sides of the highway had decking exposed or shingles blown off. At least one mobile home was destroyed along US 84. The tornado intensified to an EF3 causing significant damage to multiple homes along Danny Hillburn Road, where large sections of roofing was removed. Between US 84 and MS Highway 29, several mobile homes were completely destroyed and at least one separated from the frame. Several homes had one or more exterior walls collapsed or large sections of the roof removed. The tornado continued to cause widespread destruction as it moved into the town of Soso. Several homes and churches received significant damage. Large swaths of trees were snapped and uprooted along MS Highway 29. Near the center of town, a fire station was heavily damaged when the overhead doors collapsed and portions of the roof were removed. Numerous homes had roofing removed and exposed decking. The worst damage occurred along MS Highway 28 where a convenience store was destroyed and several other cinder block structures were heavily damaged when the storm intensified to low end EF-4. The tornado continued to mow down large swaths of trees and caused major uplift and loss of roofing to numerous homes as it moved northeast toward MS Highway 15. Along Mathews Road numerous mobile homes and several outbuildings were completely destroyed.|| ||The tornado intensified to a low end EF4 as it moved into the Moss community, where winds near 175 mph resulted in widespread devastation. Nearly every structure in the community was damaged with the most significant damage occurring along or near MS Highway 537. About half of the First Baptist Church of Moss was completely leveled. Numerous homes were destroyed or had major roofing loss or uplifted. A small pick-up truck was thrown several hundred yards and completely destroyed. In addition, multiple mobile homes were completely demolished.|| ||As the storm tracked toward I-59 a few miles west of Heidelberg, hundreds of trees were mowed down, outbuildings were destroyed. Several homes and mobile homes had metal roofing peeled back or decking exposed. Large swaths of trees were snapped for several miles including some along I-59 between the Heidelberg and Vossburg exits. Swaths of tree damage continued into the Barnett community. In the town of Pachuta there was scattered tree damage and the metal roofing was peeled off of a church. About two miles north of Pachuta, the damage became sporadic and the tornado lifted in a wooded area along County Road 130.||The total path length was 67.43 miles. The maximum estimated wind speed of the tornado was 190mph, while the maximum wind speed in Covington County was 170mph.","An outbreak of severe weather occurred on Easter Sunday, 2020. This was a multifaceted event with a few different waves of activity, each of which brought their own unique hazardous weather to the residents of the region. This outbreak had a total of 20 tornadoes across the NWS Jackson service area. Of these, two tornadoes were long tracked and in excess of 60 miles. Additionally, the most intense tornado was historically significant as it was the widest tornado in Mississippi history at 2.25 miles and ranks as the third widest nationally. Unfortunately, fatalities occurred across the region, most of which came from the two long track tornadoes. Total fatalities were 14, which were across several counties and almost 100 people were injured. Of the 20 tornadoes, two were rated as EF4, one was an  EF3, four were EF2, ten were EF1 and there were three EF0.||The first wave of severe storms moved out of northeast Louisiana as a line of thunderstorms or QLCS. The bowing segment of this line was efficient at producing tornadoes as it moved across northeast Louisiana parishes and through central sections of Mississippi before tracking across Alabama. This part of the QLCS produced 13 tornadoes across the service area with the strongest being three EF2s that occurred west of Pioneer LA, northwest of Yazoo City MS, and north of Macon MS.||The next wave was focused around two large supercell storms where each produced long track tornadoes, and were the phenomena that had the greatest impact across south and southeast Mississippi. The first storm produced two EF4 tornadoes, one of which was on the ground for 68 miles before dissipating. This tornado was up to two miles wide in several locations, with the maximum width at 2.25 miles making it the widest tornado in Mississippi history. On the heels of this supercell, another supercell developed and produced a long track EF3 tornado, which was on the ground for 84 miles.||The third and final wave was associated with the southeast surge of the cold front and driven by the strong lift and winds from the core of the upper level low. This wave was a bit unique as there were not as many thunderstorms associated with the line of strong and damaging winds. However, this line of activity produced widespread wind damage across southeast Arkansas, northeast Louisiana and all of the northern half of Mississippi, including the Mississippi Delta where winds of 70 to 90 mph occurred. While many structures sustained some sort of damage, widespread trees and power lines were blown down during the late evening and early morning hours with the final wave.",105
+902843,JONES CO.,HEBRON,04/12/2020,1541,Tornado, ,EF4,3,80,11800000,3000000,MS,CST-6, ,146307,C,67,JAN,0,1,NWS Storm Survey, ,16.04,3520,3,SSW,5,NNW,HOY,31.6661,-89.4004,31.81,-89.1863,"This violent, deadly tornado traveled 68 miles through parts of five counties including southeastern Jefferson Davis, central Covington, northwestern Jones, southeastern Jasper, and western Clarke counties. Locations impacted by this tornado include Bassfield, the areas between Collins and Seminary, Soso, Moss, Heidelberg, and Pachuta. This tornado is preliminarily rated EF4 with an estimated peak wind of 190 MPH east of Bassfield in southwestern Jefferson Davis County. Additional EF4 damage was noted near Soso in Jones County and at Moss in Jasper County. The maximum path width was 2.25 miles in the vicinity of Hughes Road west of Seminary in western Covington County. At this width, the tornado ranks 3rd widest in the official NOAA United States tornado database behind the El Reno, OK tornado of 2013 (2.6 mi) and the Hallam, NE tornado of 2004 (2.5 mi). This tornado now ranks as the widest on record in the state of Mississippi, surpassing the Yazoo City, MS tornado of 2010 (1.75 mi). Eight lives were lost in this tornado, and there was an undetermined number of additional injuries. Additional details on the damage path and area of most significant damage follow.|| ||The tornado began south of Bassfield along Bassfield Cemetery Road, uprooting trees and resulting in relatively minor structural damage. As it proceeded northeastward, the diameter of the wind field steadily increased and the percentage of snapped trees in the center of the vortex increased considerably as the tornado approached MS Highway 42. At this location, two homes sustained major roof damage. Tornado intensity then began to increase quickly, with EF3 damage as it crossed Hosey Mikell Road, completely demolishing a mobile home and scattering the debris field over 300 yards downwind. Tree damage also ramped up significantly beyond this location, with low end EF4 damage in a narrow swath of nearly complete tree destruction along the center of the tornado vortex and increasing instances of debarking of trees as the tornado moved across Pitts Lane and Reese Road. Outside of this most intense corridor of tornadic winds, EF1 and EF2 damage to trees and structures was occurring over a wider area, up one mile wide. In addition, both ground surveys and aerial photography indicated the presence of multiple vortices at times. Intense damage continued as the tornado crossed the intersection of Graves Key Road and Harper Road, where a cinder block small business building was destroyed, with much of the slab swept clean. Four fatalities occurred at this location. Nearby, a mobile home was completely destroyed, with the undercarriage wrapped around the small set of trees that remained standing downwind. Debarking of some trees was again noted and continued along the tornado path across Claude Booth Road.|| ||The tornado reached its peak intensity as it moved across a field north of Graves Key Road. At this location, the foundation of a wood frame and metal roof cabin was swept clean. A truck parked at this cabin was tossed approximately 300 yards downwind, and trees that remained standing at this site were partially debarked. Though the path of the intense tornado vortex through the field surrounding this cabin was clearly visible, significant scouring was not noted. The tornado continued to remain violent and grow in size, nearly 1.5 miles wide, as it crossed Good Hope Road and continued to track toward the Bouie River. Here, a large swath of extreme tree damage was noted as the whole forest was leveled. An intense core of the tornado was evident by debarking of trees along a well defined center line or sub-vortex feature. Extreme debarking was noted around Willie Fortenberry Road. In this general area, several farmers reported roughly 60 cattle were killed by the tornado. The tornado grew larger as it entered Covington County and peaked in width in the vicinity of Hughes Road. Maximum width was measured at 2.25 miles. The incredible expansive tree damage continued along the path with millions of trees damaged. Several dozen structures were damaged or destroyed between McGowen Circle to US 49. Numerous chicken houses (23-30) were destroyed here as well. A section of Cold Springs Road looked to see another sub- vortex and it was here another area of EF4 damage occurred to a home.|| ||As the tornado crossed US 49, the width decreased to 1.7 miles, but it remained quite strong with mid to upper end EF3 damage noted. Extreme tree damage persisted in large swaths along the path. In addition, a few dozen structures were damaged between US 49 and MS Highway 588. This consisted of varying degrees of damage from EF1 to EF3 levels. The tornado entered northwestern Jones County near the Centerville community where several homes had shingles blown off or parts of the decking exposed. A mobile home along Tommy Pickering Road was thrown and separated from the frame, with the highest winds in the EF2 range. As the storm moved northeast across US 84, trees were uprooted and snapped. Several homes on both sides of the highway had decking exposed or shingles blown off. At least one mobile home was destroyed along US 84. The tornado intensified to an EF3 causing significant damage to multiple homes along Danny Hillburn Road, where large sections of roofing was removed. Between US 84 and MS Highway 29, several mobile homes were completely destroyed and at least one separated from the frame. Several homes had one or more exterior walls collapsed or large sections of the roof removed. The tornado continued to cause widespread destruction as it moved into the town of Soso. Several homes and churches received significant damage. Large swaths of trees were snapped and uprooted along MS Highway 29. Near the center of town, a fire station was heavily damaged when the overhead doors collapsed and portions of the roof were removed. Numerous homes had roofing removed and exposed decking. The worst damage occurred along MS Highway 28 where a convenience store was destroyed and several other cinder block structures were heavily damaged when the storm intensified to low end EF-4. The tornado continued to mow down large swaths of trees and caused major uplift and loss of roofing to numerous homes as it moved northeast toward MS Highway 15. Along Mathews Road numerous mobile homes and several outbuildings were completely destroyed.||The tornado intensified to a low end EF4 as it moved into the Moss community, where winds near 175 mph resulted in widespread devastation. Nearly every structure in the community was damaged with the most significant damage occurring along or near MS Highway 537. About half of the First Baptist Church of Moss was completely leveled. Numerous homes were destroyed or had major roofing loss or uplifted. A small pick-up truck was thrown several hundred yards and completely destroyed. In addition, multiple mobile homes were completely demolished.||As the storm tracked toward I-59 a few miles west of Heidelberg, hundreds of trees were mowed down, outbuildings were destroyed. Several homes and mobile homes had metal roofing peeled back or decking exposed. Large swaths of trees were snapped for several miles including some along I-59 between the Heidelberg and Vossburg exits. Swaths of tree damage continued into the Barnett community. In the town of Pachuta there was scattered tree damage and the metal roofing was peeled off of a church. About two miles north of Pachuta, the damage became sporadic and the tornado lifted in a wooded area along County Road 130.||The total path length was 67.43 miles. The maximum estimated wind speed of the tornado was 190mph, while the maximum wind speed in Jones County was 167mph.","An outbreak of severe weather occurred on Easter Sunday, 2020. This was a multifaceted event with a few different waves of activity, each of which brought their own unique hazardous weather to the residents of the region. This outbreak had a total of 20 tornadoes across the NWS Jackson service area. Of these, two tornadoes were long tracked and in excess of 60 miles. Additionally, the most intense tornado was historically significant as it was the widest tornado in Mississippi history at 2.25 miles and ranks as the third widest nationally. Unfortunately, fatalities occurred across the region, most of which came from the two long track tornadoes. Total fatalities were 14, which were across several counties and almost 100 people were injured. Of the 20 tornadoes, two were rated as EF4, one was an  EF3, four were EF2, ten were EF1 and there were three EF0.||The first wave of severe storms moved out of northeast Louisiana as a line of thunderstorms or QLCS. The bowing segment of this line was efficient at producing tornadoes as it moved across northeast Louisiana parishes and through central sections of Mississippi before tracking across Alabama. This part of the QLCS produced 13 tornadoes across the service area with the strongest being three EF2s that occurred west of Pioneer LA, northwest of Yazoo City MS, and north of Macon MS.||The next wave was focused around two large supercell storms where each produced long track tornadoes, and were the phenomena that had the greatest impact across south and southeast Mississippi. The first storm produced two EF4 tornadoes, one of which was on the ground for 68 miles before dissipating. This tornado was up to two miles wide in several locations, with the maximum width at 2.25 miles making it the widest tornado in Mississippi history. On the heels of this supercell, another supercell developed and produced a long track EF3 tornado, which was on the ground for 84 miles.||The third and final wave was associated with the southeast surge of the cold front and driven by the strong lift and winds from the core of the upper level low. This wave was a bit unique as there were not as many thunderstorms associated with the line of strong and damaging winds. However, this line of activity produced widespread wind damage across southeast Arkansas, northeast Louisiana and all of the northern half of Mississippi, including the Mississippi Delta where winds of 70 to 90 mph occurred. While many structures sustained some sort of damage, widespread trees and power lines were blown down during the late evening and early morning hours with the final wave.",106
+902844,JASPER CO.,MOSS,04/12/2020,1559,Tornado, ,EF4,0,6,5800000,3000000,MS,CST-6, ,146307,C,61,JAN,0,0,NWS Storm Survey, ,22.16,1760,1,SE,5,S,ORANGE,31.81,-89.1863,32.0311,-88.9125,"This violent, deadly tornado traveled 68 miles through parts of five counties including southeastern Jefferson Davis, central Covington, northwestern Jones, southeastern Jasper, and western Clarke counties. Locations impacted by this tornado include Bassfield, the areas between Collins and Seminary, Soso, Moss, Heidelberg, and Pachuta. This tornado is preliminarily rated EF4 with an estimated peak wind of 190 MPH east of Bassfield in southwestern Jefferson Davis County. Additional EF4 damage was noted near Soso in Jones County and at Moss in Jasper County. The maximum path width was 2.25 miles in the vicinity of Hughes Road west of Seminary in western Covington County. At this width, the tornado ranks 3rd widest in the official NOAA United States tornado database behind the El Reno, OK tornado of 2013 (2.6 mi) and the Hallam, NE tornado of 2004 (2.5 mi). This tornado now ranks as the widest on record in the state of Mississippi, surpassing the Yazoo City, MS tornado of 2010 (1.75 mi). Eight lives were lost in this tornado, and there was an undetermined number of additional injuries. Additional details on the damage path and area of most significant damage follow.|||The tornado began south of Bassfield along Bassfield Cemetery Road, uprooting trees and resulting in relatively minor structural damage. As it proceeded northeastward, the diameter of the wind field steadily increased and the percentage of snapped trees in the center of the vortex increased considerably as the tornado approached MS Highway 42. At this location, two homes sustained major roof damage. Tornado intensity then began to increase quickly, with EF3 damage as it crossed Hosey Mikell Road, completely demolishing a mobile home and scattering the debris field over 300 yards downwind. Tree damage also ramped up significantly beyond this location, with low end EF4 damage in a narrow swath of nearly complete tree destruction along the center of the tornado vortex and increasing instances of debarking of trees as the tornado moved across Pitts Lane and Reese Road. Outside of this most intense corridor of tornadic winds, EF1 and EF2 damage to trees and structures was occurring over a wider area, up one mile wide. In addition, both ground surveys and aerial photography indicated the presence of multiple vortices at times. Intense damage continued as the tornado crossed the intersection of Graves Key Road and Harper Road, where a cinder block small business building was destroyed, with much of the slab swept clean. Four fatalities occurred at this location. Nearby, a mobile home was completely destroyed, with the undercarriage wrapped around the small set of trees that remained standing downwind. Debarking of some trees was again noted and continued along the tornado path across Claude Booth Road.||The tornado reached its peak intensity as it moved across a field north of Graves Key Road. At this location, the foundation of a wood frame and metal roof cabin was swept clean. A truck parked at this cabin was tossed approximately 300 yards downwind, and trees that remained standing at this site were partially debarked. Though the path of the intense tornado vortex through the field surrounding this cabin was clearly visible, significant scouring was not noted. The tornado continued to remain violent and grow in size, nearly 1.5 miles wide, as it crossed Good Hope Road and continued to track toward the Bouie River. Here, a large swath of extreme tree damage was noted as the whole forest was leveled. An intense core of the tornado was evident by debarking of trees along a well defined center line or sub-vortex feature. Extreme debarking was noted around Willie Fortenberry Road. In this general area, several farmers reported roughly 60 cattle were killed by the tornado. The tornado grew larger as it entered Covington County and peaked in width in the vicinity of Hughes Road. Maximum width was measured at 2.25 miles. The incredible expansive tree damage continued along the path with millions of trees damaged. Several dozen structures were damaged or destroyed between McGowen Circle to US 49. Numerous chicken houses (23-30) were destroyed here as well. A section of Cold Springs Road looked to see another sub- vortex and it was here another area of EF4 damage occurred to a home.|| ||As the tornado crossed US 49, the width decreased to 1.7 miles, but it remained quite strong with mid to upper end EF3 damage noted. Extreme tree damage persisted in large swaths along the path. In addition, a few dozen structures were damaged between US 49 and MS Highway 588. This consisted of varying degrees of damage from EF1 to EF3 levels. The tornado entered northwestern Jones County near the Centerville community where several homes had shingles blown off or parts of the decking exposed. A mobile home along Tommy Pickering Road was thrown and separated from the frame, with the highest winds in the EF2 range. As the storm moved northeast across US 84, trees were uprooted and snapped. Several homes on both sides of the highway had decking exposed or shingles blown off. At least one mobile home was destroyed along US 84. The tornado intensified to an EF3 causing significant damage to multiple homes along Danny Hillburn Road, where large sections of roofing was removed. Between US 84 and MS Highway 29, several mobile homes were completely destroyed and at least one separated from the frame. Several homes had one or more exterior walls collapsed or large sections of the roof removed. The tornado continued to cause widespread destruction as it moved into the town of Soso. Several homes and churches received significant damage. Large swaths of trees were snapped and uprooted along MS Highway 29. Near the center of town, a fire station was heavily damaged when the overhead doors collapsed and portions of the roof were removed. Numerous homes had roofing removed and exposed decking. The worst damage occurred along MS Highway 28 where a convenience store was destroyed and several other cinder block structures were heavily damaged when the storm intensified to low end EF-4. The tornado continued to mow down large swaths of trees and caused major uplift and loss of roofing to numerous homes as it moved northeast toward MS Highway 15. Along Mathews Road numerous mobile homes and several outbuildings were completely destroyed.||The tornado intensified to a low end EF4 as it moved into the Moss community, where winds near 175 mph resulted in widespread devastation. Nearly every structure in the community was damaged with the most significant damage occurring along or near MS Highway 537. About half of the First Baptist Church of Moss was completely leveled. Numerous homes were destroyed or had major roofing loss or uplifted. A small pick-up truck was thrown several hundred yards and completely destroyed. In addition, multiple mobile homes were completely demolished.||As the storm tracked toward I-59 a few miles west of Heidelberg, hundreds of trees were mowed down, outbuildings were destroyed. Several homes and mobile homes had metal roofing peeled back or decking exposed. Large swaths of trees were snapped for several miles including some along I-59 between the Heidelberg and Vossburg exits. Swaths of tree damage continued into the Barnett community. In the town of Pachuta there was scattered tree damage and the metal roofing was peeled off of a church. About two miles north of Pachuta, the damage became sporadic and the tornado lifted in a wooded area along County Road 130.||The total path length was 67.43 miles. The maximum estimated wind speed of the tornado was 190mph, while the maximum wind speed in Jasper County was 178mph.","An outbreak of severe weather occurred on Easter Sunday, 2020. This was a multifaceted event with a few different waves of activity, each of which brought their own unique hazardous weather to the residents of the region. This outbreak had a total of 20 tornadoes across the NWS Jackson service area. Of these, two tornadoes were long tracked and in excess of 60 miles. Additionally, the most intense tornado was historically significant as it was the widest tornado in Mississippi history at 2.25 miles and ranks as the third widest nationally. Unfortunately, fatalities occurred across the region, most of which came from the two long track tornadoes. Total fatalities were 14, which were across several counties and almost 100 people were injured. Of the 20 tornadoes, two were rated as EF4, one was an  EF3, four were EF2, ten were EF1 and there were three EF0.||The first wave of severe storms moved out of northeast Louisiana as a line of thunderstorms or QLCS. The bowing segment of this line was efficient at producing tornadoes as it moved across northeast Louisiana parishes and through central sections of Mississippi before tracking across Alabama. This part of the QLCS produced 13 tornadoes across the service area with the strongest being three EF2s that occurred west of Pioneer LA, northwest of Yazoo City MS, and north of Macon MS.||The next wave was focused around two large supercell storms where each produced long track tornadoes, and were the phenomena that had the greatest impact across south and southeast Mississippi. The first storm produced two EF4 tornadoes, one of which was on the ground for 68 miles before dissipating. This tornado was up to two miles wide in several locations, with the maximum width at 2.25 miles making it the widest tornado in Mississippi history. On the heels of this supercell, another supercell developed and produced a long track EF3 tornado, which was on the ground for 84 miles.||The third and final wave was associated with the southeast surge of the cold front and driven by the strong lift and winds from the core of the upper level low. This wave was a bit unique as there were not as many thunderstorms associated with the line of strong and damaging winds. However, this line of activity produced widespread wind damage across southeast Arkansas, northeast Louisiana and all of the northern half of Mississippi, including the Mississippi Delta where winds of 70 to 90 mph occurred. While many structures sustained some sort of damage, widespread trees and power lines were blown down during the late evening and early morning hours with the final wave.",107
+889068,HAMPTON CO.,ESTILL MUNI ARPT,04/13/2020,510,Tornado, ,EF4,5,60,0,0,SC,EST-5, ,147485,C,49,CHS,0,0,NWS Storm Survey, ,23.73,1300,3,WSW,5,NE,FECHTIG,32.7045,-81.2899,32.829,-80.9092,"A National Weather Service Storm Survey Team confirmed an EF-4 tornado with an estimated maximum wind speed of 175 mph in central Hampton County. ||The tornado began just north of Collie Road, approximately 3 miles west-northwest of Scotia, South Carolina, snapping and uprooting trees and causing damage to the Federal Correctional Institution of Estill along its northeast track. The tornado then continued northeast, crossing over Highway 321 near the intersection with County Road S-25-35 before gaining strength and causing substantial damage. Beyond this point, the unusually long track and wide tornado damaged and destroyed many residences, including mobile and single family homes along its entire path. A few automobiles were also tossed/rolled 50 to 75 yards from their original locations. In addition, the tornado reached a maximum width of about 0.75 mile, causing extensive damage to thousands of trees and numerous power lines. At times, the damage pattern suggested that the tornado may have consisted of multiple vortices, which can occur in stronger tornadoes.||The most significant structural damage occurred just south of Estill, South Carolina and across Nixville, South Carolina, where at least six residences were destroyed. After crossing Highway 321 and continuing a northeast track, the tornado began producing EF-2 to EF-3 damage to residences along Sprayfield Road to Lena Expressway. The tornado then continued northeast where it completely destroyed a mobile home near the intersection of Highway 3 and Highway 601, tragically claiming the lives of 2 adult males. Continuing on a northeast track, the tornado heavily damaged homes near the intersection of Turner Expressway and Brandy Lane, including completely destroying a mobile home that tragically claimed the lives of 2 adult females and 1 adult male. The tornado then reached peak EF-4 intensity along Lento Road where the roof and all exterior/interior walls of a two story home were removed and dispersed across the yard. The tornado then began a weakening trend while tracking further northeast, eventually crossing Highway 278, Yemassee Highway and ending approximately 1 mile beyond the intersection of Old Salkehatchie Highway and Archie Road before the Hampton/Colleton County line. ||Overall, the tornado path stretched approximately 24 miles, claiming the lives of 5 individuals in the hardest hit areas just south of Estill, South Carolina and across Nixville, South Carolina. Additionally, 60 people sustained injuries associated with the tornado tracking through this hardest hit area, including a few individuals that were thrown 30 to 50 yards from mobile homes and individuals that were in homes that received EF-3 to EF-4 damage.","A severe quasi-linear convective system (QLCS) moved through southeast South Carolina during the early morning hours of April 13, 2020 ahead of an approaching cold front. The environment ahead of the QLCS was unusually unstable for this time of day and year, with gulf moisture spreading upper 60 F to near 70 F dewpoints into a warm sector across the Southeast United States and mid level lapse rates around 7 C/km helping produce mixed layer convective available potential energy (MLCAPE) as high as 2000 J/kg across Southeast South Carolina. Within the warm sector, very strong vertical shear associated with a 50 knot plus low and mid-level jet, effective bulk shear around 70 knots, effective storm relative helicity in the 400-600 m2/s2 range, and VAD wind profiles displaying large, curved low-level hodographs were supportive of well organized convection and potentially embedded supercell thunderstorms in a QLCS capable of producing a prolonged path of damaging winds and strong long-track tornadoes. As the QLCS swept through Southeast South Carolina, a few supercell thunderstorms became exceptionally strong while partially breaking away from the main line of thunderstorms, producing widespread wind damage and strong long-track tornadoes. ||A total of 13 confirmed tornadoes occurred across Southeast South Carolina, including a long track EF-4 tornado in Hampton County that took the lives of 5 people and injured 60 others along an approximately 24 mile path. The EF-4 tornado was the first to have occurred across Southeast South Carolina and the last to have occurred in the entire state of South Carolina since November 17, 1995, almost 25 years prior. This particular tornado was associated with a storm that produced a destructive path of straight-line wind damage and series of long track and intermittent tornadoes for over 150 miles, beginning in Screven County, Georgia, then continuing northeast across Hampton County, Colleton County, Dorchester County, and Berkeley County, South Carolina before leaving the area and eventually shifting offshore along the South Carolina coast. Two other storms were responsible for the remaining tornadoes across the area, most of which occurred from a single storm occurring across Edisto Island, Seabrook Island and Kiawah Island. Outside the EF-4 tornado in Hampton County, straight-line winds near a passing tornado claimed the life of one individual and injured one in Colleton County, while another tornado caused 6 injuries across Berkeley County.",108
+899721,MARION CO.,ST PAUL,04/19/2020,1813,Tornado, ,EF4,1,0,400000,0,MS,CST-6, ,146303,C,91,JAN,0,0,NWS Storm Survey, ,16.34,2275,5,W,4,E,PINEBUR,31.075,-89.9209,31.1348,-89.6537,"This violent tornado began over southeastern Walthall County in a field just west of Reagan Road and moved east northeastward along MS Highway 48, producing significant tree damage and minor damage to a few homes. It crossed into Marion County near the intersection of MS Highway 48 and Mt Bethel Road. The tornado then began to move more northeastward as it moved into southwestern Marion County, uprooting and snapping several softwood trees, causing minor roof damage to a home, and destroying an outdoor small shed along New Hope Road. It also snapped several trees and peeled the tin roof of a barn along A Pittman, Marks and Davis Roads. The tornado intensified relatively quickly once it moved northeast, snapping the majority of trees close to the ground in a wooded area east of New Hope Road. The basis for the low-end EF4 rating was a home on Johnson Road that was completely destroyed with its debris pushed to a corner of the foundation leaving residual vinyl flooring and a few of its anchor bolts bent. Furthermore, across the street from the aforementioned home, in a field a few of the snapped trees sustained patchy debarking. A higher rating was not assigned because the contents of the home were not spread a significant distance from the foundation and debris remained over a part of the slab. Nonetheless, significant damage to the home and nearby trees occurred. In addition, multiple wooden power poles were snapped, several other homes had significant roof damage and multiple mobile homes were completely destroyed, resulting in one fatality. Continual uprooting and snapping of trees was observed at Hurricane Creek Road, in addition to minor roof damage to a shed and a one-story home. When the tornado crossed Hurricane Creek Church Road, it caused significant roof damage to the Hurricane Creek Baptist Church and the nearby pastor's home. Behind the pastor's home was a large 40-foot shed that sat partially on cinder blocks and partially on a slab that was bolted down. This shed was completely destroyed as it was blown a few feet away. Several headstones in a cemetery were knocked over at this location as well. Additional roof damage to multiple homes and the uprooting and snapping of numerous trees along Hurricane Creek Road to the intersection of MS Highway 35. When the tornado reached MS Highway 35, it snapped multiple wooden power-poles and continued snapping trees. It continued east- northeast to Old MS Highway 35 causing numerous snapping of hardwood trees and the removal of a portion of a one-story home roof. The tornado continued moving east-northeast across the Pearl River bottom, when it reached MS Highway 43, multiple wooden power-poles were snapped, some minor roof damage occurred to some one-story homes and hardwood trees were snapped. Just east of MS Highway 43 along Joe Magee Road, a brick home sustained significant damage as the roof was completely destroyed and a few exterior walls were collapsed. A swath of snapped softwood trees was noted along Abrams Road thus producing EF2 damage.||Once the tornado reached MS Highway 13 and surrounding streets such as Pine Burr Road and Firetower Road near the Marion and Lamar county borders, a slight decline in strength was noted, though its path remained wide. Although, it was still snapping large tree limbs and snapping and uprooting some softwood trees, several of which fell onto wooden power poles and caused them to fall. The tornado maintained its east northeastward track, knocking thousands of trees down along with numerous power lines and poles down across the western portions of Lamar County. This tree damage was consistent with high end EF1 winds peaking between 100-110 mph. Around a dozen homes were damaged starting from Luther Saucier Rd to Purvis to Columbia Road, including one old mobile home that was completely destroyed. As the tornado continued to track east northeastward to the north of Purvis. It crossed Purvis Oloh Road, MS Highway 589 along with US 11. Hundreds of trees were damaged along with many power lines down. Some minor damage occurred to some homes. The tornado was slightly weaker here with winds between 90- 100mph. The tornado crossed I-59 into Forrest County along Ford and Elks Lodge Road in the Dixie community. Hundreds of trees were damaged along with many power lines down. Sheds and several homes had minor damage and one mobile home had the roof blown off. The tornado then crossed US 49 a couple miles north of Southgate Road. The tornado proceeded into Camp Shelby. At Camp Shelby, there were widespread snapped and uprooted trees. Multiple structures across the north half, in and around Lee Avenue to Glenn Walker Lake, had varying degrees of minor to moderate roof damage from the tornado or fallen trees. The park and camper area on the north end of the lake was impacted. One person was injured here as a large tree fell on a truck. The tornado then crossed over US 98 just west of the Perry County line. It continued into Perry County along the Leaf River bottom, snapping and uprooting trees. It continued to track just south of Old River Road before dissipating along Old River Road three miles northwest of New Augusta. Total path length was 53.76 miles.","A very unstable airmass was in place across the region as a frontal boundary was stalled across the central portions of the ArkLaMiss region. Severe thunderstorms moved across central and southern portions of the area during the afternoon and evening hours of the 19th. A supercell thunderstorm developed and moved across portions of the Pine Belt and brought a violent tornado across the region, for the second time in as many weeks.",109
+898306,GRANT CO.,ASHBY,07/08/2020,1608,Tornado, ,EF4,0,0,100000,5000,MN,CST-6, ,148227,C,51,FGF,0,0,NWS Storm Survey, ,2.36,650,6,W,4,W,ASHBY,46.09,-95.94,46.11,-95.9,"This tornado began in Grant County, but after about two miles, it crossed into Otter Tail County, where it ended about 5 miles east of Dalton. The total track through both counties was about 9 miles. Peak winds were estimated at 170 mph, based on available damage indicators. At least 10 farmsteads were impacted, with three homes, one pole shed, and one machine shed destroyed.","A lone weak cell appeared on radar at 430 pm CDT over northern Grant County, Minnesota. Numerous storm chasers had congregated in this area, hoping to see a good storm to chase. By 5 pm, the cell had blossomed into a strong thunderstorm. Weather spotters, law enforcement, and storm chasers then reported a funnel coming down toward the ground slightly after 505 pm. A tornado warning was issued at 508 pm (until 6 pm) for portions of south central Otter Tail and northeast Grant counties. This tornado tracked about 9 miles through the warned area, before dissipating. At its peak strength, it was rated as an EF-4 tornado. Another rotation was noted a little later, leading to a second tornado warning at 635 pm (until 7 pm), this time for southwest Wadena and southeast Otter Tail counties.",110
+898307,OTTER TAIL CO.,DALTON,07/08/2020,1615,Tornado, ,EF4,1,2,1500000,250000,MN,CST-6, ,148227,C,111,FGF,0,0,NWS Storm Survey, ,6.5,650,4,S,5,E,DALTON,46.11,-95.9,46.17,-95.7955,"This tornado began in Grant County, but after about two miles, it crossed into Otter Tail County, where it ended about 5 miles east of Dalton. The total track through both counties was about 9 miles. Peak winds were estimated at 170 mph, based on available damage indicators. At least 10 farmsteads were impacted, with three homes, one pole shed, and one machine shed destroyed.","A lone weak cell appeared on radar at 430 pm CDT over northern Grant County, Minnesota. Numerous storm chasers had congregated in this area, hoping to see a good storm to chase. By 5 pm, the cell had blossomed into a strong thunderstorm. Weather spotters, law enforcement, and storm chasers then reported a funnel coming down toward the ground slightly after 505 pm. A tornado warning was issued at 508 pm (until 6 pm) for portions of south central Otter Tail and northeast Grant counties. This tornado tracked about 9 miles through the warned area, before dissipating. At its peak strength, it was rated as an EF-4 tornado. Another rotation was noted a little later, leading to a second tornado warning at 635 pm (until 7 pm), this time for southwest Wadena and southeast Otter Tail counties.",111

From 61d398938c92bcec772e91b9b7ae6570ef6889a2 Mon Sep 17 00:00:00 2001
From: Simon Angel <simonangel@Simons-MacBook-Pro.local>
Date: Sat, 27 Feb 2021 13:06:52 -0500
Subject: [PATCH 04/38] THis is a test, ok?

---
 NaturalDisasterProject/Datasets/testFile | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 NaturalDisasterProject/Datasets/testFile

diff --git a/NaturalDisasterProject/Datasets/testFile b/NaturalDisasterProject/Datasets/testFile
new file mode 100644
index 00000000..efb7a7cd
--- /dev/null
+++ b/NaturalDisasterProject/Datasets/testFile
@@ -0,0 +1 @@
+this is a test. 
\ No newline at end of file

From dd99838c372d6a5712117d74097772244fcea457 Mon Sep 17 00:00:00 2001
From: varocarras <varocarras@gmail.com>
Date: Sat, 27 Feb 2021 13:29:53 -0500
Subject: [PATCH 05/38] Update README.md

---
 NaturalDisasterProject/README.md | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/NaturalDisasterProject/README.md b/NaturalDisasterProject/README.md
index ec8dcca1..dfd008da 100644
--- a/NaturalDisasterProject/README.md
+++ b/NaturalDisasterProject/README.md
@@ -1,3 +1,4 @@
+#Alvaro
 # CS 506 - Final Project Repository
 
 All final projects for CS506.
@@ -64,5 +65,3 @@ This is a draft of your final report that has been reviewed by your client. It i
 ### Final Project Deliverable
 
 This should be an enhancement of deliverable 4.
-
-

From 136c02627d309ab85a1a1bfdc0cd1a813cbc2d7e Mon Sep 17 00:00:00 2001
From: varocarras <varocarras@gmail.com>
Date: Sat, 27 Feb 2021 13:34:04 -0500
Subject: [PATCH 06/38] Update README.md

---
 NaturalDisasterProject/README.md | 1 -
 1 file changed, 1 deletion(-)

diff --git a/NaturalDisasterProject/README.md b/NaturalDisasterProject/README.md
index dfd008da..f020892e 100644
--- a/NaturalDisasterProject/README.md
+++ b/NaturalDisasterProject/README.md
@@ -1,4 +1,3 @@
-#Alvaro
 # CS 506 - Final Project Repository
 
 All final projects for CS506.

From 64268562181c3d5e20cde0332331c92e787669a6 Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Sat, 27 Feb 2021 15:06:37 -0500
Subject: [PATCH 07/38] HeatMap/Transform Data

Transform weather data into heat map and choropleth map
---
 .../Deliverable_1/choropleth_weather.html     |  76 ++++
 .../Deliverable_1/heatmap_weather.html        |  76 ++++
 .../weather_data_transforming.ipynb           | 394 ++++++++++++++++++
 .../weather_data_transforming.py              | 103 +++++
 4 files changed, 649 insertions(+)
 create mode 100644 NaturalDisasterProject/Deliverable_1/choropleth_weather.html
 create mode 100644 NaturalDisasterProject/Deliverable_1/heatmap_weather.html
 create mode 100644 NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
 create mode 100644 NaturalDisasterProject/Deliverable_1/weather_data_transforming.py

diff --git a/NaturalDisasterProject/Deliverable_1/choropleth_weather.html b/NaturalDisasterProject/Deliverable_1/choropleth_weather.html
new file mode 100644
index 00000000..f5a44f0c
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/choropleth_weather.html
@@ -0,0 +1,76 @@
+<!DOCTYPE html>
+<head>    
+    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
+    
+        <script>
+            L_NO_TOUCH = false;
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+    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
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+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>
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+            <div class="folium-map" id="map_caa5ac6661f14f718f208d08c1c906fb" ></div>
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+<script>    
+    
+            var map_caa5ac6661f14f718f208d08c1c906fb = L.map(
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+                {
+                    center: [32.7003, -90.6783],
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+                [[32.7003, -90.6783], [32.9456, -90.1539], [34.2203, -85.9602], [35.1808, -97.4273], [35.377, -97.305], [45.45, -99.71], [41.5512, -83.538], [46.11, -95.425], [47.54, -97.3], [47.68, -97.32], [46.41, -95.18], [46.43, -95.15], [43.5755, -93.6404], [43.404, -95.8605], [46.11, -96.63], [46.13, -96.563], [31.7947, -92.808], [42.7293, -94.8557], [38.7364, -90.4863], [32.7992, -89.1088], [34.0757, -87.0097], [32.9017, -88.9145], [32.9262, -88.8719], [34.1043, -88.1479], [34.3054, -86.6549], [34.3528, -86.5813], [34.3109, -87.7858], [34.0455, -88.445], [34.4368, -87.5307], [34.0891, -88.36], [34.6208, -85.9814], [34.662, -87.0705], [34.82, -85.6314], [33.6448, -87.4238], [34.8017, -86.7855], [33.0606, -87.8315], [33.8668, -86.995], [34.7948, -85.909], [33.3512, -87.1975], [32.0712, -89.3201], [34.3907, -85.9784], [32.1439, -88.9154], [33.6839, -86.5234], [33.8291, -86.0526], [35.5324, -84.0504], [35.5459, -84.0274], [35.34, -85.42], [35.3969, -85.3253], [34.8744, -85.1785], [34.9868, -85.0485], [35.0371, -84.9875], [32.7545, -85.8826], [35.5535, -85.1077], [37.056, -94.5701], [35.444, -98.287], [35.008, -97.961], [34.939, -97.67], [35.189, -97.67], [35.3182, -93.9044], [34.357, -99.194], [37.6945, -88.65], [37.771, -88.3751], [38.4316, -86.1893], [38.5156, -85.8678], [38.6061, -85.5808], [38.6096, -85.57], [38.796, -84.6092], [38.523, -98.008], [31.2802, -89.4665], [32.412, -97.754], [38.1429, -99.4706], [35.308, -97.142], [35.284, -97.628], [35.303, -97.605], [42.128, -97.077], [42.3319, -96.1086], [40.622, -89.5678], [38.42, -89.45], [34.913, -92.4572], [32.932, -89.3067], [41.893, -97.33], [41.9528, -97.1369], [41.9797, -97.0198], [42.0908, -96.931], [42.127, -96.8686], [44.0372, -98.4032], [41.8886, -89.2381], [34.5955, -89.7055], [34.6131, -89.6691], [34.8117, -89.2983], [34.9428, -89.0174], [34.9958, -88.8952], [35.0471, -88.7866], [32.796, -96.5894], [34.559, -97.357], [38.9917, -97.3713], [37.7238, -90.0055], [32.357, -95.9549], [32.4571, -85.4362], [39.8243, -84.4632], [38.9689, -95.108], [36.1715, -85.6628], [31.2763, -90.1732], [31.4641, -89.7579], [31.5475, -89.6194], [31.6661, -89.4004], [31.81, -89.1863], [32.7045, -81.2899], [31.075, -89.9209], [46.09, -95.94], [46.11, -95.9]],
+                {"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
+            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+        
+</script>
\ No newline at end of file
diff --git a/NaturalDisasterProject/Deliverable_1/heatmap_weather.html b/NaturalDisasterProject/Deliverable_1/heatmap_weather.html
new file mode 100644
index 00000000..f5a44f0c
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/heatmap_weather.html
@@ -0,0 +1,76 @@
+<!DOCTYPE html>
+<head>    
+    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
+    
+        <script>
+            L_NO_TOUCH = false;
+            L_DISABLE_3D = false;
+        </script>
+    
+    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
+    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
+    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.js"></script>
+    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
+    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
+    
+            <meta name="viewport" content="width=device-width,
+                initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
+            <style>
+                #map_caa5ac6661f14f718f208d08c1c906fb {
+                    position: relative;
+                    width: 100.0%;
+                    height: 100.0%;
+                    left: 0.0%;
+                    top: 0.0%;
+                }
+            </style>
+        
+    <script src="https://cdn.jsdelivr.net/gh/python-visualization/folium@master/folium/templates/leaflet_heat.min.js"></script>
+</head>
+<body>    
+    
+            <div class="folium-map" id="map_caa5ac6661f14f718f208d08c1c906fb" ></div>
+        
+</body>
+<script>    
+    
+            var map_caa5ac6661f14f718f208d08c1c906fb = L.map(
+                "map_caa5ac6661f14f718f208d08c1c906fb",
+                {
+                    center: [32.7003, -90.6783],
+                    crs: L.CRS.EPSG3857,
+                    zoom: 10,
+                    zoomControl: true,
+                    preferCanvas: false,
+                }
+            );
+
+            
+
+        
+    
+            var tile_layer_631210ae6ca6470abb864414d414b0af = L.tileLayer(
+                "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
+                {"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
+            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+        
+    
+            var heat_map_3be44ae715354bd3b151cf3c61afd564 = L.heatLayer(
+                [[32.7003, -90.6783], [32.9456, -90.1539], [34.2203, -85.9602], [35.1808, -97.4273], [35.377, -97.305], [45.45, -99.71], [41.5512, -83.538], [46.11, -95.425], [47.54, -97.3], [47.68, -97.32], [46.41, -95.18], [46.43, -95.15], [43.5755, -93.6404], [43.404, -95.8605], [46.11, -96.63], [46.13, -96.563], [31.7947, -92.808], [42.7293, -94.8557], [38.7364, -90.4863], [32.7992, -89.1088], [34.0757, -87.0097], [32.9017, -88.9145], [32.9262, -88.8719], [34.1043, -88.1479], [34.3054, -86.6549], [34.3528, -86.5813], [34.3109, -87.7858], [34.0455, -88.445], [34.4368, -87.5307], [34.0891, -88.36], [34.6208, -85.9814], [34.662, -87.0705], [34.82, -85.6314], [33.6448, -87.4238], [34.8017, -86.7855], [33.0606, -87.8315], [33.8668, -86.995], [34.7948, -85.909], [33.3512, -87.1975], [32.0712, -89.3201], [34.3907, -85.9784], [32.1439, -88.9154], [33.6839, -86.5234], [33.8291, -86.0526], [35.5324, -84.0504], [35.5459, -84.0274], [35.34, -85.42], [35.3969, -85.3253], [34.8744, -85.1785], [34.9868, -85.0485], [35.0371, -84.9875], [32.7545, -85.8826], [35.5535, -85.1077], [37.056, -94.5701], [35.444, -98.287], [35.008, -97.961], [34.939, -97.67], [35.189, -97.67], [35.3182, -93.9044], [34.357, -99.194], [37.6945, -88.65], [37.771, -88.3751], [38.4316, -86.1893], [38.5156, -85.8678], [38.6061, -85.5808], [38.6096, -85.57], [38.796, -84.6092], [38.523, -98.008], [31.2802, -89.4665], [32.412, -97.754], [38.1429, -99.4706], [35.308, -97.142], [35.284, -97.628], [35.303, -97.605], [42.128, -97.077], [42.3319, -96.1086], [40.622, -89.5678], [38.42, -89.45], [34.913, -92.4572], [32.932, -89.3067], [41.893, -97.33], [41.9528, -97.1369], [41.9797, -97.0198], [42.0908, -96.931], [42.127, -96.8686], [44.0372, -98.4032], [41.8886, -89.2381], [34.5955, -89.7055], [34.6131, -89.6691], [34.8117, -89.2983], [34.9428, -89.0174], [34.9958, -88.8952], [35.0471, -88.7866], [32.796, -96.5894], [34.559, -97.357], [38.9917, -97.3713], [37.7238, -90.0055], [32.357, -95.9549], [32.4571, -85.4362], [39.8243, -84.4632], [38.9689, -95.108], [36.1715, -85.6628], [31.2763, -90.1732], [31.4641, -89.7579], [31.5475, -89.6194], [31.6661, -89.4004], [31.81, -89.1863], [32.7045, -81.2899], [31.075, -89.9209], [46.09, -95.94], [46.11, -95.9]],
+                {"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
+            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+        
+    
+            var heat_map_b66a17aeb5714612b5e5eb5d33e771a5 = L.heatLayer(
+                [[32.7003, -90.6783], [32.9456, -90.1539], [34.2203, -85.9602], [35.1808, -97.4273], [35.377, -97.305], [45.45, -99.71], [41.5512, -83.538], [46.11, -95.425], [47.54, -97.3], [47.68, -97.32], [46.41, -95.18], [46.43, -95.15], [43.5755, -93.6404], [43.404, -95.8605], [46.11, -96.63], [46.13, -96.563], [31.7947, -92.808], [42.7293, -94.8557], [38.7364, -90.4863], [32.7992, -89.1088], [34.0757, -87.0097], [32.9017, -88.9145], [32.9262, -88.8719], [34.1043, -88.1479], [34.3054, -86.6549], [34.3528, -86.5813], [34.3109, -87.7858], [34.0455, -88.445], [34.4368, -87.5307], [34.0891, -88.36], [34.6208, -85.9814], [34.662, -87.0705], [34.82, -85.6314], [33.6448, -87.4238], [34.8017, -86.7855], [33.0606, -87.8315], [33.8668, -86.995], [34.7948, -85.909], [33.3512, -87.1975], [32.0712, -89.3201], [34.3907, -85.9784], [32.1439, -88.9154], [33.6839, -86.5234], [33.8291, -86.0526], [35.5324, -84.0504], [35.5459, -84.0274], [35.34, -85.42], [35.3969, -85.3253], [34.8744, -85.1785], [34.9868, -85.0485], [35.0371, -84.9875], [32.7545, -85.8826], [35.5535, -85.1077], [37.056, -94.5701], [35.444, -98.287], [35.008, -97.961], [34.939, -97.67], [35.189, -97.67], [35.3182, -93.9044], [34.357, -99.194], [37.6945, -88.65], [37.771, -88.3751], [38.4316, -86.1893], [38.5156, -85.8678], [38.6061, -85.5808], [38.6096, -85.57], [38.796, -84.6092], [38.523, -98.008], [31.2802, -89.4665], [32.412, -97.754], [38.1429, -99.4706], [35.308, -97.142], [35.284, -97.628], [35.303, -97.605], [42.128, -97.077], [42.3319, -96.1086], [40.622, -89.5678], [38.42, -89.45], [34.913, -92.4572], [32.932, -89.3067], [41.893, -97.33], [41.9528, -97.1369], [41.9797, -97.0198], [42.0908, -96.931], [42.127, -96.8686], [44.0372, -98.4032], [41.8886, -89.2381], [34.5955, -89.7055], [34.6131, -89.6691], [34.8117, -89.2983], [34.9428, -89.0174], [34.9958, -88.8952], [35.0471, -88.7866], [32.796, -96.5894], [34.559, -97.357], [38.9917, -97.3713], [37.7238, -90.0055], [32.357, -95.9549], [32.4571, -85.4362], [39.8243, -84.4632], [38.9689, -95.108], [36.1715, -85.6628], [31.2763, -90.1732], [31.4641, -89.7579], [31.5475, -89.6194], [31.6661, -89.4004], [31.81, -89.1863], [32.7045, -81.2899], [31.075, -89.9209], [46.09, -95.94], [46.11, -95.9]],
+                {"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
+            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+        
+</script>
\ No newline at end of file
diff --git a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
new file mode 100644
index 00000000..d85ff351
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
@@ -0,0 +1,394 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "beneficial-storm",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import folium\n",
+    "from folium.plugins import HeatMap\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import os\n",
+    "current_directory = os.getcwd()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "bigger-standing",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "location=[32.7003, -90.6783]\n",
+    "weather_data = pd.read_csv('/Users/abdullaahrobins/Documents/GitHub/CS506Spring2021Repository/NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv')\n",
+    "folium.Map(location=location, zoom_start=3)\n",
+    "heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]\n",
+    "heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])\n",
+    "# HeatMap(data=weather_data.groupby(['BEGIN_LAT', 'BEGIN_LON']).mean().reset_index().values.tolist(), radius=8, max_zoom=4).add_to(base_map)\n",
+    "# base_map.save('tornado_heat_map.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "prospective-career",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 111 entries, 0 to 110\n",
+      "Data columns (total 37 columns):\n",
+      " #   Column               Non-Null Count  Dtype  \n",
+      "---  ------               --------------  -----  \n",
+      " 0   EVENT_ID             111 non-null    int64  \n",
+      " 1   CZ_NAME_STR          111 non-null    object \n",
+      " 2   BEGIN_LOCATION       111 non-null    object \n",
+      " 3   BEGIN_DATE           111 non-null    object \n",
+      " 4   BEGIN_TIME           111 non-null    int64  \n",
+      " 5   EVENT_TYPE           111 non-null    object \n",
+      " 6   MAGNITUDE            111 non-null    object \n",
+      " 7   TOR_F_SCALE          111 non-null    object \n",
+      " 8   DEATHS_DIRECT        111 non-null    int64  \n",
+      " 9   INJURIES_DIRECT      111 non-null    int64  \n",
+      " 10  DAMAGE_PROPERTY_NUM  111 non-null    int64  \n",
+      " 11  DAMAGE_CROPS_NUM     111 non-null    int64  \n",
+      " 12  STATE_ABBR           111 non-null    object \n",
+      " 13  CZ_TIMEZONE          111 non-null    object \n",
+      " 14  MAGNITUDE_TYPE       111 non-null    object \n",
+      " 15  EPISODE_ID           111 non-null    int64  \n",
+      " 16  CZ_TYPE              111 non-null    object \n",
+      " 17  CZ_FIPS              111 non-null    int64  \n",
+      " 18  WFO                  111 non-null    object \n",
+      " 19  INJURIES_INDIRECT    111 non-null    int64  \n",
+      " 20  DEATHS_INDIRECT      111 non-null    int64  \n",
+      " 21  SOURCE               111 non-null    object \n",
+      " 22  FLOOD_CAUSE          111 non-null    object \n",
+      " 23  TOR_LENGTH           111 non-null    float64\n",
+      " 24  TOR_WIDTH            111 non-null    float64\n",
+      " 25  BEGIN_RANGE          111 non-null    int64  \n",
+      " 26  BEGIN_AZIMUTH        111 non-null    object \n",
+      " 27  END_RANGE            111 non-null    int64  \n",
+      " 28  END_AZIMUTH          111 non-null    object \n",
+      " 29  END_LOCATION         111 non-null    object \n",
+      " 30  BEGIN_LAT            111 non-null    float64\n",
+      " 31  BEGIN_LON            111 non-null    float64\n",
+      " 32  END_LAT              111 non-null    float64\n",
+      " 33  END_LON              111 non-null    float64\n",
+      " 34  EVENT_NARRATIVE      111 non-null    object \n",
+      " 35  EPISODE_NARRATIVE    111 non-null    object \n",
+      " 36  ABSOLUTE_ROWNUMBER   111 non-null    int64  \n",
+      "dtypes: float64(6), int64(13), object(18)\n",
+      "memory usage: 32.2+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "info = weather_data.info()\n",
+    "state_occ = weather_data['STATE_ABBR'].value_counts()\n",
+    "df = weather_data['STATE_ABBR'].value_counts().rename_axis('states').reset_index(name='counts')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "administrative-score",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 20 entries, 0 to 19\n",
+      "Data columns (total 2 columns):\n",
+      " #   Column  Non-Null Count  Dtype \n",
+      "---  ------  --------------  ----- \n",
+      " 0   states  20 non-null     object\n",
+      " 1   counts  20 non-null     int64 \n",
+      "dtypes: int64(1), object(1)\n",
+      "memory usage: 448.0+ bytes\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "owned-superior",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<folium.map.LayerControl at 0x1284f8050>"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "url = (\n",
+    "    \"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data\"\n",
+    ")\n",
+    "state_geo = f\"{url}/us-states.json\"\n",
+    "\n",
+    "m = folium.Map(location=location, zoom_start=3)\n",
+    "\n",
+    "folium.Choropleth(\n",
+    "    geo_data=state_geo,\n",
+    "    name=\"choropleth\",\n",
+    "    data=df,\n",
+    "    columns=[\"states\", \"counts\"],\n",
+    "    key_on=\"feature.id\",\n",
+    "    fill_color=\"YlGn\",\n",
+    "    fill_opacity=0.7,\n",
+    "    line_opacity=0.2,\n",
+    "    legend_name=\"Tornado Occurrances\",\n",
+    ").add_to(m)\n",
+    "\n",
+    "folium.LayerControl().add_to(m)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "manufactured-dictionary",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "</div>"
+      ],
+      "text/plain": [
+       "     BEGIN_LAT  BEGIN_LON\n",
+       "0      32.7003   -90.6783\n",
+       "1      32.9456   -90.1539\n",
+       "2      34.2203   -85.9602\n",
+       "3      35.1808   -97.4273\n",
+       "4      35.3770   -97.3050\n",
+       "..         ...        ...\n",
+       "106    31.8100   -89.1863\n",
+       "107    32.7045   -81.2899\n",
+       "108    31.0750   -89.9209\n",
+       "109    46.0900   -95.9400\n",
+       "110    46.1100   -95.9000\n",
+       "\n",
+       "[111 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "heat_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "revised-peace",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<folium.plugins.heat_map.HeatMap at 0x129c52b10>"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "heat_data = [[row['BEGIN_LAT'],row['BEGIN_LON']] for index, row in heat_df.iterrows()]\n",
+    "HeatMap(heat_data).add_to(base_map)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "operating-consideration",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" 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onload=\"this.contentDocument.open();this.contentDocument.write(    decodeURIComponent(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x127108ed0>"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "base_map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "respected-marketplace",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "base_map.save('heatmap_weather.html')\n",
+    "base_map.save('choropleth_weather.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "impossible-friday",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py
new file mode 100644
index 00000000..aa85ce8e
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py
@@ -0,0 +1,103 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[25]:
+
+
+import folium
+from folium.plugins import HeatMap
+import numpy as np
+import pandas as pd
+import os
+current_directory = os.getcwd()
+
+
+# In[26]:
+
+
+
+location=[32.7003, -90.6783]
+weather_data = pd.read_csv('/Users/abdullaahrobins/Documents/GitHub/CS506Spring2021Repository/NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv')
+folium.Map(location=location, zoom_start=3)
+heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]
+heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])
+# HeatMap(data=weather_data.groupby(['BEGIN_LAT', 'BEGIN_LON']).mean().reset_index().values.tolist(), radius=8, max_zoom=4).add_to(base_map)
+# base_map.save('tornado_heat_map.html')
+
+
+# In[27]:
+
+
+info = weather_data.info()
+state_occ = weather_data['STATE_ABBR'].value_counts()
+df = weather_data['STATE_ABBR'].value_counts().rename_axis('states').reset_index(name='counts')
+
+
+# In[28]:
+
+
+df.info()
+
+
+# In[29]:
+
+
+url = (
+    "https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
+)
+state_geo = f"{url}/us-states.json"
+
+m = folium.Map(location=location, zoom_start=3)
+
+folium.Choropleth(
+    geo_data=state_geo,
+    name="choropleth",
+    data=df,
+    columns=["states", "counts"],
+    key_on="feature.id",
+    fill_color="YlGn",
+    fill_opacity=0.7,
+    line_opacity=0.2,
+    legend_name="Tornado Occurrances",
+).add_to(m)
+
+folium.LayerControl().add_to(m)
+
+
+# In[30]:
+
+
+m
+
+
+# In[31]:
+
+
+heat_df
+
+
+# In[32]:
+
+
+heat_data = [[row['BEGIN_LAT'],row['BEGIN_LON']] for index, row in heat_df.iterrows()]
+HeatMap(heat_data).add_to(base_map)
+
+
+# In[33]:
+
+
+base_map
+
+
+# In[34]:
+
+
+base_map.save('heatmap_weather.html')
+base_map.save('choropleth_weather.html')
+
+
+# In[ ]:
+
+
+
+

From 3b66eec18ae915f36a5908747c1a38173b895c4f Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Sat, 27 Feb 2021 15:35:37 -0500
Subject: [PATCH 08/38] Fixed Chloropleth Map

---
 .../Deliverable_1/choropleth_weather.html     | 126 +++++++++++++++---
 .../weather_data_transforming.py              |   6 +-
 2 files changed, 112 insertions(+), 20 deletions(-)

diff --git a/NaturalDisasterProject/Deliverable_1/choropleth_weather.html b/NaturalDisasterProject/Deliverable_1/choropleth_weather.html
index f5a44f0c..00bdbce8 100644
--- a/NaturalDisasterProject/Deliverable_1/choropleth_weather.html
+++ b/NaturalDisasterProject/Deliverable_1/choropleth_weather.html
@@ -23,7 +23,7 @@
             <meta name="viewport" content="width=device-width,
                 initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
             <style>
-                #map_caa5ac6661f14f718f208d08c1c906fb {
+                #map_2a83db2240664c2bbc43a9df4a85b26f {
                     position: relative;
                     width: 100.0%;
                     height: 100.0%;
@@ -32,21 +32,21 @@
                 }
             </style>
         
-    <script src="https://cdn.jsdelivr.net/gh/python-visualization/folium@master/folium/templates/leaflet_heat.min.js"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js"></script>
 </head>
 <body>    
     
-            <div class="folium-map" id="map_caa5ac6661f14f718f208d08c1c906fb" ></div>
+            <div class="folium-map" id="map_2a83db2240664c2bbc43a9df4a85b26f" ></div>
         
 </body>
 <script>    
     
-            var map_caa5ac6661f14f718f208d08c1c906fb = L.map(
-                "map_caa5ac6661f14f718f208d08c1c906fb",
+            var map_2a83db2240664c2bbc43a9df4a85b26f = L.map(
+                "map_2a83db2240664c2bbc43a9df4a85b26f",
                 {
                     center: [32.7003, -90.6783],
                     crs: L.CRS.EPSG3857,
-                    zoom: 10,
+                    zoom: 3,
                     zoomControl: true,
                     preferCanvas: false,
                 }
@@ -56,21 +56,115 @@
 
         
     
-            var tile_layer_631210ae6ca6470abb864414d414b0af = L.tileLayer(
+            var tile_layer_16fe225c3a68442288f45e8692f4f701 = L.tileLayer(
                 "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
                 {"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
-            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+            ).addTo(map_2a83db2240664c2bbc43a9df4a85b26f);
         
     
-            var heat_map_3be44ae715354bd3b151cf3c61afd564 = L.heatLayer(
-                [[32.7003, -90.6783], [32.9456, -90.1539], [34.2203, -85.9602], [35.1808, -97.4273], [35.377, -97.305], [45.45, -99.71], [41.5512, -83.538], [46.11, -95.425], [47.54, -97.3], [47.68, -97.32], [46.41, -95.18], [46.43, -95.15], [43.5755, -93.6404], [43.404, -95.8605], [46.11, -96.63], [46.13, -96.563], [31.7947, -92.808], [42.7293, -94.8557], [38.7364, -90.4863], [32.7992, -89.1088], [34.0757, -87.0097], [32.9017, -88.9145], [32.9262, -88.8719], [34.1043, -88.1479], [34.3054, -86.6549], [34.3528, -86.5813], [34.3109, -87.7858], [34.0455, -88.445], [34.4368, -87.5307], [34.0891, -88.36], [34.6208, -85.9814], [34.662, -87.0705], [34.82, -85.6314], [33.6448, -87.4238], [34.8017, -86.7855], [33.0606, -87.8315], [33.8668, -86.995], [34.7948, -85.909], [33.3512, -87.1975], [32.0712, -89.3201], [34.3907, -85.9784], [32.1439, -88.9154], [33.6839, -86.5234], [33.8291, -86.0526], [35.5324, -84.0504], [35.5459, -84.0274], [35.34, -85.42], [35.3969, -85.3253], [34.8744, -85.1785], [34.9868, -85.0485], [35.0371, -84.9875], [32.7545, -85.8826], [35.5535, -85.1077], [37.056, -94.5701], [35.444, -98.287], [35.008, -97.961], [34.939, -97.67], [35.189, -97.67], [35.3182, -93.9044], [34.357, -99.194], [37.6945, -88.65], [37.771, -88.3751], [38.4316, -86.1893], [38.5156, -85.8678], [38.6061, -85.5808], [38.6096, -85.57], [38.796, -84.6092], [38.523, -98.008], [31.2802, -89.4665], [32.412, -97.754], [38.1429, -99.4706], [35.308, -97.142], [35.284, -97.628], [35.303, -97.605], [42.128, -97.077], [42.3319, -96.1086], [40.622, -89.5678], [38.42, -89.45], [34.913, -92.4572], [32.932, -89.3067], [41.893, -97.33], [41.9528, -97.1369], [41.9797, -97.0198], [42.0908, -96.931], [42.127, -96.8686], [44.0372, -98.4032], [41.8886, -89.2381], [34.5955, -89.7055], [34.6131, -89.6691], [34.8117, -89.2983], [34.9428, -89.0174], [34.9958, -88.8952], [35.0471, -88.7866], [32.796, -96.5894], [34.559, -97.357], [38.9917, -97.3713], [37.7238, -90.0055], [32.357, -95.9549], [32.4571, -85.4362], [39.8243, -84.4632], [38.9689, -95.108], [36.1715, -85.6628], [31.2763, -90.1732], [31.4641, -89.7579], [31.5475, -89.6194], [31.6661, -89.4004], [31.81, -89.1863], [32.7045, -81.2899], [31.075, -89.9209], [46.09, -95.94], [46.11, -95.9]],
-                {"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
-            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+            var choropleth_e76e441a47b64fdbac62cc38fca3fde8 = L.featureGroup(
+                {}
+            ).addTo(map_2a83db2240664c2bbc43a9df4a85b26f);
         
     
-            var heat_map_b66a17aeb5714612b5e5eb5d33e771a5 = L.heatLayer(
-                [[32.7003, -90.6783], [32.9456, -90.1539], [34.2203, -85.9602], [35.1808, -97.4273], [35.377, -97.305], [45.45, -99.71], [41.5512, -83.538], [46.11, -95.425], [47.54, -97.3], [47.68, -97.32], [46.41, -95.18], [46.43, -95.15], [43.5755, -93.6404], [43.404, -95.8605], [46.11, -96.63], [46.13, -96.563], [31.7947, -92.808], [42.7293, -94.8557], [38.7364, -90.4863], [32.7992, -89.1088], [34.0757, -87.0097], [32.9017, -88.9145], [32.9262, -88.8719], [34.1043, -88.1479], [34.3054, -86.6549], [34.3528, -86.5813], [34.3109, -87.7858], [34.0455, -88.445], [34.4368, -87.5307], [34.0891, -88.36], [34.6208, -85.9814], [34.662, -87.0705], [34.82, -85.6314], [33.6448, -87.4238], [34.8017, -86.7855], [33.0606, -87.8315], [33.8668, -86.995], [34.7948, -85.909], [33.3512, -87.1975], [32.0712, -89.3201], [34.3907, -85.9784], [32.1439, -88.9154], [33.6839, -86.5234], [33.8291, -86.0526], [35.5324, -84.0504], [35.5459, -84.0274], [35.34, -85.42], [35.3969, -85.3253], [34.8744, -85.1785], [34.9868, -85.0485], [35.0371, -84.9875], [32.7545, -85.8826], [35.5535, -85.1077], [37.056, -94.5701], [35.444, -98.287], [35.008, -97.961], [34.939, -97.67], [35.189, -97.67], [35.3182, -93.9044], [34.357, -99.194], [37.6945, -88.65], [37.771, -88.3751], [38.4316, -86.1893], [38.5156, -85.8678], [38.6061, -85.5808], [38.6096, -85.57], [38.796, -84.6092], [38.523, -98.008], [31.2802, -89.4665], [32.412, -97.754], [38.1429, -99.4706], [35.308, -97.142], [35.284, -97.628], [35.303, -97.605], [42.128, -97.077], [42.3319, -96.1086], [40.622, -89.5678], [38.42, -89.45], [34.913, -92.4572], [32.932, -89.3067], [41.893, -97.33], [41.9528, -97.1369], [41.9797, -97.0198], [42.0908, -96.931], [42.127, -96.8686], [44.0372, -98.4032], [41.8886, -89.2381], [34.5955, -89.7055], [34.6131, -89.6691], [34.8117, -89.2983], [34.9428, -89.0174], [34.9958, -88.8952], [35.0471, -88.7866], [32.796, -96.5894], [34.559, -97.357], [38.9917, -97.3713], [37.7238, -90.0055], [32.357, -95.9549], [32.4571, -85.4362], [39.8243, -84.4632], [38.9689, -95.108], [36.1715, -85.6628], [31.2763, -90.1732], [31.4641, -89.7579], [31.5475, -89.6194], [31.6661, -89.4004], [31.81, -89.1863], [32.7045, -81.2899], [31.075, -89.9209], [46.09, -95.94], [46.11, -95.9]],
-                {"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
-            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+        function geo_json_01e31973e4c446fba564f5e1c84f5a71_styler(feature) {
+            switch(feature.id) {
+                case "AL": case "MS": 
+                    return {"color": "black", "fillColor": "#006837", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                case "AR": case "GA": case "IN": case "IA": case "KS": case "KY": case "LA": case "MO": case "ND": case "OH": case "SC": case "SD": case "TX": 
+                    return {"color": "black", "fillColor": "#ffffcc", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                case "IL": case "MN": case "NE": 
+                    return {"color": "black", "fillColor": "#d9f0a3", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                case "OK": 
+                    return {"color": "black", "fillColor": "#78c679", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                case "TN": 
+                    return {"color": "black", "fillColor": "#addd8e", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                default:
+                    return {"color": "black", "fillColor": "black", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+            }
+        }
+
+        function geo_json_01e31973e4c446fba564f5e1c84f5a71_onEachFeature(feature, layer) {
+            layer.on({
+            });
+        };
+        var geo_json_01e31973e4c446fba564f5e1c84f5a71 = L.geoJson(null, {
+                onEachFeature: geo_json_01e31973e4c446fba564f5e1c84f5a71_onEachFeature,
+            
+                style: geo_json_01e31973e4c446fba564f5e1c84f5a71_styler,
+        });
+
+        function geo_json_01e31973e4c446fba564f5e1c84f5a71_add (data) {
+            geo_json_01e31973e4c446fba564f5e1c84f5a71
+                .addData(data)
+                .addTo(choropleth_e76e441a47b64fdbac62cc38fca3fde8);
+        }
+            geo_json_01e31973e4c446fba564f5e1c84f5a71_add({"features": [{"geometry": {"coordinates": [[[-87.359296, 35.00118], [-85.606675, 34.984749], [-85.431413, 34.124869], [-85.184951, 32.859696], [-85.069935, 32.580372], [-84.960397, 32.421541], [-85.004212, 32.322956], [-84.889196, 32.262709], [-85.058981, 32.13674], [-85.053504, 32.01077], [-85.141136, 31.840985], [-85.042551, 31.539753], [-85.113751, 31.27686], [-85.004212, 31.003013], [-85.497137, 30.997536], [-87.600282, 30.997536], [-87.633143, 30.86609], [-87.408589, 30.674397], [-87.446927, 30.510088], [-87.37025, 30.427934], [-87.518128, 30.280057], [-87.655051, 30.247195], [-87.90699, 30.411504], [-87.934375, 30.657966], [-88.011052, 30.685351], [-88.10416, 30.499135], [-88.137022, 30.318396], [-88.394438, 30.367688], [-88.471115, 31.895754], [-88.241084, 33.796253], [-88.098683, 34.891641], [-88.202745, 34.995703], [-87.359296, 35.00118]]], "type": "Polygon"}, "id": "AL", "properties": {"name": "Alabama"}, "type": "Feature"}, {"geometry": {"coordinates": [[[[-131.602021, 55.117982], [-131.569159, 55.28229], [-131.355558, 55.183705], [-131.38842, 55.01392], [-131.645836, 55.035827], [-131.602021, 55.117982]]], [[[-131.832052, 55.42469], [-131.645836, 55.304197], [-131.749898, 55.128935], [-131.832052, 55.189182], [-131.832052, 55.42469]]], [[[-132.976733, 56.437924], [-132.735747, 56.459832], [-132.631685, 56.421493], [-132.664547, 56.273616], [-132.878148, 56.240754], [-133.069841, 56.333862], [-132.976733, 56.437924]]], [[[-133.595627, 56.350293], [-133.162949, 56.317431], [-133.05341, 56.125739], [-132.620732, 55.912138], [-132.472854, 55.780691], [-132.4619, 55.671152], [-132.357838, 55.649245], [-132.341408, 55.506844], [-132.166146, 55.364444], [-132.144238, 55.238474], [-132.029222, 55.276813], [-131.97993, 55.178228], [-131.958022, 54.789365], [-132.029222, 54.701734], [-132.308546, 54.718165], [-132.385223, 54.915335], [-132.483808, 54.898904], [-132.686455, 55.046781], [-132.746701, 54.997489], [-132.916486, 55.046781], [-132.889102, 54.898904], [-132.73027, 54.937242], [-132.626209, 54.882473], [-132.675501, 54.679826], [-132.867194, 54.701734], [-133.157472, 54.95915], [-133.239626, 55.090597], [-133.223195, 55.22752], [-133.453227, 55.216566], [-133.453227, 55.320628], [-133.277964, 55.331582], [-133.102702, 55.42469], [-133.17938, 55.588998], [-133.387503, 55.62186], [-133.420365, 55.884753], [-133.497042, 56.0162], [-133.639442, 55.923092], [-133.694212, 56.070969], [-133.546335, 56.142169], [-133.666827, 56.311955], [-133.595627, 56.350293]]], [[[-133.738027, 55.556137], [-133.546335, 55.490413], [-133.414888, 55.572568], [-133.283441, 55.534229], [-133.420365, 55.386352], [-133.633966, 55.430167], [-133.738027, 55.556137]]], [[[-133.907813, 56.930849], [-134.050213, 57.029434], [-133.885905, 57.095157], [-133.343688, 57.002049], [-133.102702, 57.007526], [-132.932917, 56.82131], [-132.620732, 56.667956], [-132.653593, 56.55294], [-132.817901, 56.492694], [-133.042456, 56.520078], [-133.201287, 56.448878], [-133.420365, 56.492694], [-133.66135, 56.448878], [-133.710643, 56.684386], [-133.688735, 56.837741], [-133.869474, 56.843218], [-133.907813, 56.930849]]], [[[-134.115936, 56.48174], [-134.25286, 56.558417], [-134.400737, 56.722725], [-134.417168, 56.848695], [-134.296675, 56.908941], [-134.170706, 56.848695], [-134.143321, 56.952757], [-133.748981, 56.772017], [-133.710643, 56.596755], [-133.847566, 56.574848], [-133.935197, 56.377678], [-133.836612, 56.322908], [-133.957105, 56.092877], [-134.110459, 56.142169], [-134.132367, 55.999769], [-134.230952, 56.070969], [-134.291198, 56.350293], [-134.115936, 56.48174]]], [[[-134.636246, 56.28457], [-134.669107, 56.169554], [-134.806031, 56.235277], [-135.178463, 56.67891], [-135.413971, 56.810356], [-135.331817, 56.914418], [-135.424925, 57.166357], [-135.687818, 57.369004], [-135.419448, 57.566174], [-135.298955, 57.48402], [-135.063447, 57.418296], [-134.849846, 57.407343], [-134.844369, 57.248511], [-134.636246, 56.728202], [-134.636246, 56.28457]]], [[[-134.712923, 58.223407], [-134.373353, 58.14673], [-134.176183, 58.157683], [-134.187137, 58.081006], [-133.902336, 57.807159], [-134.099505, 57.850975], [-134.148798, 57.757867], [-133.935197, 57.615466], [-133.869474, 57.363527], [-134.083075, 57.297804], [-134.154275, 57.210173], [-134.499322, 57.029434], [-134.603384, 57.034911], [-134.6472, 57.226604], [-134.575999, 57.341619], [-134.608861, 57.511404], [-134.729354, 57.719528], [-134.707446, 57.829067], [-134.784123, 58.097437], [-134.91557, 58.212453], [-134.953908, 58.409623], [-134.712923, 58.223407]]], [[[-135.857603, 57.330665], [-135.715203, 57.330665], [-135.567326, 57.149926], [-135.633049, 57.023957], [-135.857603, 56.996572], [-135.824742, 57.193742], [-135.857603, 57.330665]]], [[[-136.279328, 58.206976], [-135.978096, 58.201499], [-135.780926, 58.28913], [-135.496125, 58.168637], [-135.64948, 58.037191], [-135.59471, 57.987898], [-135.45231, 58.135776], [-135.107263, 58.086483], [-134.91557, 57.976944], [-135.025108, 57.779775], [-134.937477, 57.763344], [-134.822462, 57.500451], [-135.085355, 57.462112], [-135.572802, 57.675713], [-135.556372, 57.456635], [-135.709726, 57.369004], [-135.890465, 57.407343], [-136.000004, 57.544266], [-136.208128, 57.637374], [-136.366959, 57.829067], [-136.569606, 57.916698], [-136.558652, 58.075529], [-136.421728, 58.130299], [-136.377913, 58.267222], [-136.279328, 58.206976]]], [[[-147.079854, 60.200582], [-147.501579, 59.948643], [-147.53444, 59.850058], [-147.874011, 59.784335], [-147.80281, 59.937689], [-147.435855, 60.09652], [-147.205824, 60.271782], [-147.079854, 60.200582]]], [[[-147.561825, 60.578491], [-147.616594, 60.370367], [-147.758995, 60.156767], [-147.956165, 60.227967], [-147.791856, 60.474429], [-147.561825, 60.578491]]], [[[-147.786379, 70.245291], [-147.682318, 70.201475], [-147.162008, 70.15766], [-146.888161, 70.185044], [-146.510252, 70.185044], 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+
+        
+    
+    var color_map_8376637c08dc4769aeb73310c2c85533 = {};
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+    
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+    
+
+    color_map_8376637c08dc4769aeb73310c2c85533.x = d3.scale.linear()
+              .domain([1.0, 21.0])
+              .range([0, 400]);
+
+    color_map_8376637c08dc4769aeb73310c2c85533.legend = L.control({position: 'topright'});
+    color_map_8376637c08dc4769aeb73310c2c85533.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};
+    color_map_8376637c08dc4769aeb73310c2c85533.legend.addTo(map_2a83db2240664c2bbc43a9df4a85b26f);
+
+    color_map_8376637c08dc4769aeb73310c2c85533.xAxis = d3.svg.axis()
+        .scale(color_map_8376637c08dc4769aeb73310c2c85533.x)
+        .orient("top")
+        .tickSize(1)
+        .tickValues([1.0, 4.333333333333334, 7.666666666666667, 11.0, 14.333333333333334, 17.666666666666668, 21.0]);
+
+    color_map_8376637c08dc4769aeb73310c2c85533.svg = d3.select(".legend.leaflet-control").append("svg")
+        .attr("id", 'legend')
+        .attr("width", 450)
+        .attr("height", 40);
+
+    color_map_8376637c08dc4769aeb73310c2c85533.g = color_map_8376637c08dc4769aeb73310c2c85533.svg.append("g")
+        .attr("class", "key")
+        .attr("transform", "translate(25,16)");
+
+    color_map_8376637c08dc4769aeb73310c2c85533.g.selectAll("rect")
+        .data(color_map_8376637c08dc4769aeb73310c2c85533.color.range().map(function(d, i) {
+          return {
+            x0: i ? color_map_8376637c08dc4769aeb73310c2c85533.x(color_map_8376637c08dc4769aeb73310c2c85533.color.domain()[i - 1]) : color_map_8376637c08dc4769aeb73310c2c85533.x.range()[0],
+            x1: i < color_map_8376637c08dc4769aeb73310c2c85533.color.domain().length ? color_map_8376637c08dc4769aeb73310c2c85533.x(color_map_8376637c08dc4769aeb73310c2c85533.color.domain()[i]) : color_map_8376637c08dc4769aeb73310c2c85533.x.range()[1],
+            z: d
+          };
+        }))
+      .enter().append("rect")
+        .attr("height", 10)
+        .attr("x", function(d) { return d.x0; })
+        .attr("width", function(d) { return d.x1 - d.x0; })
+        .style("fill", function(d) { return d.z; });
+
+    color_map_8376637c08dc4769aeb73310c2c85533.g.call(color_map_8376637c08dc4769aeb73310c2c85533.xAxis).append("text")
+        .attr("class", "caption")
+        .attr("y", 21)
+        .text('Tornado Occurrances');
+    
+            var layer_control_2a01fcaf92d4409095a30965f51a7b9e = {
+                base_layers : {
+                    "openstreetmap" : tile_layer_16fe225c3a68442288f45e8692f4f701,
+                },
+                overlays :  {
+                    "choropleth" : choropleth_e76e441a47b64fdbac62cc38fca3fde8,
+                },
+            };
+            L.control.layers(
+                layer_control_2a01fcaf92d4409095a30965f51a7b9e.base_layers,
+                layer_control_2a01fcaf92d4409095a30965f51a7b9e.overlays,
+                {"autoZIndex": true, "collapsed": true, "position": "topright"}
+            ).addTo(map_2a83db2240664c2bbc43a9df4a85b26f);
         
 </script>
\ No newline at end of file
diff --git a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py
index aa85ce8e..3e35a554 100644
--- a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py
+++ b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py
@@ -18,11 +18,9 @@
 
 location=[32.7003, -90.6783]
 weather_data = pd.read_csv('/Users/abdullaahrobins/Documents/GitHub/CS506Spring2021Repository/NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv')
-folium.Map(location=location, zoom_start=3)
+base_map = folium.Map(location=location, zoom_start=3)
 heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]
 heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])
-# HeatMap(data=weather_data.groupby(['BEGIN_LAT', 'BEGIN_LON']).mean().reset_index().values.tolist(), radius=8, max_zoom=4).add_to(base_map)
-# base_map.save('tornado_heat_map.html')
 
 
 # In[27]:
@@ -93,7 +91,7 @@
 
 
 base_map.save('heatmap_weather.html')
-base_map.save('choropleth_weather.html')
+m.save('choropleth_weather.html')
 
 
 # In[ ]:

From d3dc2fba379387e02ed1a62c80607a3c616b9e1b Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Sat, 27 Feb 2021 15:36:39 -0500
Subject: [PATCH 09/38] HeatMap/Transform Data (#4)

* HeatMap/Transform Data

Transform weather data into heat map and choropleth map

* Fixed Chloropleth Map
---
 .../Deliverable_1/choropleth_weather.html     | 170 ++++++++
 .../Deliverable_1/heatmap_weather.html        |  76 ++++
 .../weather_data_transforming.ipynb           | 394 ++++++++++++++++++
 .../weather_data_transforming.py              | 101 +++++
 4 files changed, 741 insertions(+)
 create mode 100644 NaturalDisasterProject/Deliverable_1/choropleth_weather.html
 create mode 100644 NaturalDisasterProject/Deliverable_1/heatmap_weather.html
 create mode 100644 NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
 create mode 100644 NaturalDisasterProject/Deliverable_1/weather_data_transforming.py

diff --git a/NaturalDisasterProject/Deliverable_1/choropleth_weather.html b/NaturalDisasterProject/Deliverable_1/choropleth_weather.html
new file mode 100644
index 00000000..00bdbce8
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/choropleth_weather.html
@@ -0,0 +1,170 @@
+<!DOCTYPE html>
+<head>    
+    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
+    
+        <script>
+            L_NO_TOUCH = false;
+            L_DISABLE_3D = false;
+        </script>
+    
+    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
+    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
+    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.js"></script>
+    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
+    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
+    
+            <meta name="viewport" content="width=device-width,
+                initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
+            <style>
+                #map_2a83db2240664c2bbc43a9df4a85b26f {
+                    position: relative;
+                    width: 100.0%;
+                    height: 100.0%;
+                    left: 0.0%;
+                    top: 0.0%;
+                }
+            </style>
+        
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js"></script>
+</head>
+<body>    
+    
+            <div class="folium-map" id="map_2a83db2240664c2bbc43a9df4a85b26f" ></div>
+        
+</body>
+<script>    
+    
+            var map_2a83db2240664c2bbc43a9df4a85b26f = L.map(
+                "map_2a83db2240664c2bbc43a9df4a85b26f",
+                {
+                    center: [32.7003, -90.6783],
+                    crs: L.CRS.EPSG3857,
+                    zoom: 3,
+                    zoomControl: true,
+                    preferCanvas: false,
+                }
+            );
+
+            
+
+        
+    
+            var tile_layer_16fe225c3a68442288f45e8692f4f701 = L.tileLayer(
+                "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
+                {"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
+            ).addTo(map_2a83db2240664c2bbc43a9df4a85b26f);
+        
+    
+            var choropleth_e76e441a47b64fdbac62cc38fca3fde8 = L.featureGroup(
+                {}
+            ).addTo(map_2a83db2240664c2bbc43a9df4a85b26f);
+        
+    
+        function geo_json_01e31973e4c446fba564f5e1c84f5a71_styler(feature) {
+            switch(feature.id) {
+                case "AL": case "MS": 
+                    return {"color": "black", "fillColor": "#006837", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                case "AR": case "GA": case "IN": case "IA": case "KS": case "KY": case "LA": case "MO": case "ND": case "OH": case "SC": case "SD": case "TX": 
+                    return {"color": "black", "fillColor": "#ffffcc", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                case "IL": case "MN": case "NE": 
+                    return {"color": "black", "fillColor": "#d9f0a3", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                case "OK": 
+                    return {"color": "black", "fillColor": "#78c679", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                case "TN": 
+                    return {"color": "black", "fillColor": "#addd8e", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+                default:
+                    return {"color": "black", "fillColor": "black", "fillOpacity": 0.7, "opacity": 0.2, "weight": 1};
+            }
+        }
+
+        function geo_json_01e31973e4c446fba564f5e1c84f5a71_onEachFeature(feature, layer) {
+            layer.on({
+            });
+        };
+        var geo_json_01e31973e4c446fba564f5e1c84f5a71 = L.geoJson(null, {
+                onEachFeature: geo_json_01e31973e4c446fba564f5e1c84f5a71_onEachFeature,
+            
+                style: geo_json_01e31973e4c446fba564f5e1c84f5a71_styler,
+        });
+
+        function geo_json_01e31973e4c446fba564f5e1c84f5a71_add (data) {
+            geo_json_01e31973e4c446fba564f5e1c84f5a71
+                .addData(data)
+                .addTo(choropleth_e76e441a47b64fdbac62cc38fca3fde8);
+        }
+            geo_json_01e31973e4c446fba564f5e1c84f5a71_add({"features": [{"geometry": {"coordinates": [[[-87.359296, 35.00118], [-85.606675, 34.984749], [-85.431413, 34.124869], [-85.184951, 32.859696], [-85.069935, 32.580372], [-84.960397, 32.421541], [-85.004212, 32.322956], [-84.889196, 32.262709], [-85.058981, 32.13674], [-85.053504, 32.01077], [-85.141136, 31.840985], [-85.042551, 31.539753], [-85.113751, 31.27686], [-85.004212, 31.003013], [-85.497137, 30.997536], [-87.600282, 30.997536], [-87.633143, 30.86609], [-87.408589, 30.674397], [-87.446927, 30.510088], [-87.37025, 30.427934], [-87.518128, 30.280057], [-87.655051, 30.247195], [-87.90699, 30.411504], [-87.934375, 30.657966], [-88.011052, 30.685351], [-88.10416, 30.499135], [-88.137022, 30.318396], [-88.394438, 30.367688], [-88.471115, 31.895754], [-88.241084, 33.796253], [-88.098683, 34.891641], [-88.202745, 34.995703], [-87.359296, 35.00118]]], "type": "Polygon"}, "id": "AL", "properties": {"name": "Alabama"}, "type": "Feature"}, {"geometry": {"coordinates": [[[[-131.602021, 55.117982], [-131.569159, 55.28229], [-131.355558, 55.183705], [-131.38842, 55.01392], [-131.645836, 55.035827], [-131.602021, 55.117982]]], [[[-131.832052, 55.42469], [-131.645836, 55.304197], [-131.749898, 55.128935], [-131.832052, 55.189182], [-131.832052, 55.42469]]], [[[-132.976733, 56.437924], [-132.735747, 56.459832], [-132.631685, 56.421493], [-132.664547, 56.273616], [-132.878148, 56.240754], [-133.069841, 56.333862], [-132.976733, 56.437924]]], [[[-133.595627, 56.350293], [-133.162949, 56.317431], [-133.05341, 56.125739], [-132.620732, 55.912138], [-132.472854, 55.780691], [-132.4619, 55.671152], [-132.357838, 55.649245], [-132.341408, 55.506844], [-132.166146, 55.364444], [-132.144238, 55.238474], [-132.029222, 55.276813], [-131.97993, 55.178228], [-131.958022, 54.789365], [-132.029222, 54.701734], [-132.308546, 54.718165], [-132.385223, 54.915335], [-132.483808, 54.898904], [-132.686455, 55.046781], [-132.746701, 54.997489], [-132.916486, 55.046781], [-132.889102, 54.898904], [-132.73027, 54.937242], [-132.626209, 54.882473], [-132.675501, 54.679826], [-132.867194, 54.701734], [-133.157472, 54.95915], [-133.239626, 55.090597], [-133.223195, 55.22752], [-133.453227, 55.216566], [-133.453227, 55.320628], [-133.277964, 55.331582], [-133.102702, 55.42469], [-133.17938, 55.588998], [-133.387503, 55.62186], [-133.420365, 55.884753], [-133.497042, 56.0162], [-133.639442, 55.923092], [-133.694212, 56.070969], [-133.546335, 56.142169], [-133.666827, 56.311955], [-133.595627, 56.350293]]], [[[-133.738027, 55.556137], [-133.546335, 55.490413], [-133.414888, 55.572568], [-133.283441, 55.534229], [-133.420365, 55.386352], [-133.633966, 55.430167], [-133.738027, 55.556137]]], [[[-133.907813, 56.930849], [-134.050213, 57.029434], [-133.885905, 57.095157], [-133.343688, 57.002049], [-133.102702, 57.007526], [-132.932917, 56.82131], [-132.620732, 56.667956], [-132.653593, 56.55294], [-132.817901, 56.492694], 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[-134.844369, 57.248511], [-134.636246, 56.728202], [-134.636246, 56.28457]]], [[[-134.712923, 58.223407], [-134.373353, 58.14673], [-134.176183, 58.157683], [-134.187137, 58.081006], [-133.902336, 57.807159], [-134.099505, 57.850975], [-134.148798, 57.757867], [-133.935197, 57.615466], [-133.869474, 57.363527], [-134.083075, 57.297804], [-134.154275, 57.210173], [-134.499322, 57.029434], [-134.603384, 57.034911], [-134.6472, 57.226604], [-134.575999, 57.341619], [-134.608861, 57.511404], [-134.729354, 57.719528], [-134.707446, 57.829067], [-134.784123, 58.097437], [-134.91557, 58.212453], [-134.953908, 58.409623], [-134.712923, 58.223407]]], [[[-135.857603, 57.330665], [-135.715203, 57.330665], [-135.567326, 57.149926], [-135.633049, 57.023957], [-135.857603, 56.996572], [-135.824742, 57.193742], [-135.857603, 57.330665]]], [[[-136.279328, 58.206976], [-135.978096, 58.201499], [-135.780926, 58.28913], [-135.496125, 58.168637], [-135.64948, 58.037191], [-135.59471, 57.987898], 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+
+        
+    
+    var color_map_8376637c08dc4769aeb73310c2c85533 = {};
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+    
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+    
+
+    color_map_8376637c08dc4769aeb73310c2c85533.x = d3.scale.linear()
+              .domain([1.0, 21.0])
+              .range([0, 400]);
+
+    color_map_8376637c08dc4769aeb73310c2c85533.legend = L.control({position: 'topright'});
+    color_map_8376637c08dc4769aeb73310c2c85533.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};
+    color_map_8376637c08dc4769aeb73310c2c85533.legend.addTo(map_2a83db2240664c2bbc43a9df4a85b26f);
+
+    color_map_8376637c08dc4769aeb73310c2c85533.xAxis = d3.svg.axis()
+        .scale(color_map_8376637c08dc4769aeb73310c2c85533.x)
+        .orient("top")
+        .tickSize(1)
+        .tickValues([1.0, 4.333333333333334, 7.666666666666667, 11.0, 14.333333333333334, 17.666666666666668, 21.0]);
+
+    color_map_8376637c08dc4769aeb73310c2c85533.svg = d3.select(".legend.leaflet-control").append("svg")
+        .attr("id", 'legend')
+        .attr("width", 450)
+        .attr("height", 40);
+
+    color_map_8376637c08dc4769aeb73310c2c85533.g = color_map_8376637c08dc4769aeb73310c2c85533.svg.append("g")
+        .attr("class", "key")
+        .attr("transform", "translate(25,16)");
+
+    color_map_8376637c08dc4769aeb73310c2c85533.g.selectAll("rect")
+        .data(color_map_8376637c08dc4769aeb73310c2c85533.color.range().map(function(d, i) {
+          return {
+            x0: i ? color_map_8376637c08dc4769aeb73310c2c85533.x(color_map_8376637c08dc4769aeb73310c2c85533.color.domain()[i - 1]) : color_map_8376637c08dc4769aeb73310c2c85533.x.range()[0],
+            x1: i < color_map_8376637c08dc4769aeb73310c2c85533.color.domain().length ? color_map_8376637c08dc4769aeb73310c2c85533.x(color_map_8376637c08dc4769aeb73310c2c85533.color.domain()[i]) : color_map_8376637c08dc4769aeb73310c2c85533.x.range()[1],
+            z: d
+          };
+        }))
+      .enter().append("rect")
+        .attr("height", 10)
+        .attr("x", function(d) { return d.x0; })
+        .attr("width", function(d) { return d.x1 - d.x0; })
+        .style("fill", function(d) { return d.z; });
+
+    color_map_8376637c08dc4769aeb73310c2c85533.g.call(color_map_8376637c08dc4769aeb73310c2c85533.xAxis).append("text")
+        .attr("class", "caption")
+        .attr("y", 21)
+        .text('Tornado Occurrances');
+    
+            var layer_control_2a01fcaf92d4409095a30965f51a7b9e = {
+                base_layers : {
+                    "openstreetmap" : tile_layer_16fe225c3a68442288f45e8692f4f701,
+                },
+                overlays :  {
+                    "choropleth" : choropleth_e76e441a47b64fdbac62cc38fca3fde8,
+                },
+            };
+            L.control.layers(
+                layer_control_2a01fcaf92d4409095a30965f51a7b9e.base_layers,
+                layer_control_2a01fcaf92d4409095a30965f51a7b9e.overlays,
+                {"autoZIndex": true, "collapsed": true, "position": "topright"}
+            ).addTo(map_2a83db2240664c2bbc43a9df4a85b26f);
+        
+</script>
\ No newline at end of file
diff --git a/NaturalDisasterProject/Deliverable_1/heatmap_weather.html b/NaturalDisasterProject/Deliverable_1/heatmap_weather.html
new file mode 100644
index 00000000..f5a44f0c
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/heatmap_weather.html
@@ -0,0 +1,76 @@
+<!DOCTYPE html>
+<head>    
+    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
+    
+        <script>
+            L_NO_TOUCH = false;
+            L_DISABLE_3D = false;
+        </script>
+    
+    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
+    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
+    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.js"></script>
+    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
+    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
+    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
+    
+            <meta name="viewport" content="width=device-width,
+                initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
+            <style>
+                #map_caa5ac6661f14f718f208d08c1c906fb {
+                    position: relative;
+                    width: 100.0%;
+                    height: 100.0%;
+                    left: 0.0%;
+                    top: 0.0%;
+                }
+            </style>
+        
+    <script src="https://cdn.jsdelivr.net/gh/python-visualization/folium@master/folium/templates/leaflet_heat.min.js"></script>
+</head>
+<body>    
+    
+            <div class="folium-map" id="map_caa5ac6661f14f718f208d08c1c906fb" ></div>
+        
+</body>
+<script>    
+    
+            var map_caa5ac6661f14f718f208d08c1c906fb = L.map(
+                "map_caa5ac6661f14f718f208d08c1c906fb",
+                {
+                    center: [32.7003, -90.6783],
+                    crs: L.CRS.EPSG3857,
+                    zoom: 10,
+                    zoomControl: true,
+                    preferCanvas: false,
+                }
+            );
+
+            
+
+        
+    
+            var tile_layer_631210ae6ca6470abb864414d414b0af = L.tileLayer(
+                "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
+                {"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
+            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+        
+    
+            var heat_map_3be44ae715354bd3b151cf3c61afd564 = L.heatLayer(
+                [[32.7003, -90.6783], [32.9456, -90.1539], [34.2203, -85.9602], [35.1808, -97.4273], [35.377, -97.305], [45.45, -99.71], [41.5512, -83.538], [46.11, -95.425], [47.54, -97.3], [47.68, -97.32], [46.41, -95.18], [46.43, -95.15], [43.5755, -93.6404], [43.404, -95.8605], [46.11, -96.63], [46.13, -96.563], [31.7947, -92.808], [42.7293, -94.8557], [38.7364, -90.4863], [32.7992, -89.1088], [34.0757, -87.0097], [32.9017, -88.9145], [32.9262, -88.8719], [34.1043, -88.1479], [34.3054, -86.6549], [34.3528, -86.5813], [34.3109, -87.7858], [34.0455, -88.445], [34.4368, -87.5307], [34.0891, -88.36], [34.6208, -85.9814], [34.662, -87.0705], [34.82, -85.6314], [33.6448, -87.4238], [34.8017, -86.7855], [33.0606, -87.8315], [33.8668, -86.995], [34.7948, -85.909], [33.3512, -87.1975], [32.0712, -89.3201], [34.3907, -85.9784], [32.1439, -88.9154], [33.6839, -86.5234], [33.8291, -86.0526], [35.5324, -84.0504], [35.5459, -84.0274], [35.34, -85.42], [35.3969, -85.3253], [34.8744, -85.1785], [34.9868, -85.0485], [35.0371, -84.9875], [32.7545, -85.8826], [35.5535, -85.1077], [37.056, -94.5701], [35.444, -98.287], [35.008, -97.961], [34.939, -97.67], [35.189, -97.67], [35.3182, -93.9044], [34.357, -99.194], [37.6945, -88.65], [37.771, -88.3751], [38.4316, -86.1893], [38.5156, -85.8678], [38.6061, -85.5808], [38.6096, -85.57], [38.796, -84.6092], [38.523, -98.008], [31.2802, -89.4665], [32.412, -97.754], [38.1429, -99.4706], [35.308, -97.142], [35.284, -97.628], [35.303, -97.605], [42.128, -97.077], [42.3319, -96.1086], [40.622, -89.5678], [38.42, -89.45], [34.913, -92.4572], [32.932, -89.3067], [41.893, -97.33], [41.9528, -97.1369], [41.9797, -97.0198], [42.0908, -96.931], [42.127, -96.8686], [44.0372, -98.4032], [41.8886, -89.2381], [34.5955, -89.7055], [34.6131, -89.6691], [34.8117, -89.2983], [34.9428, -89.0174], [34.9958, -88.8952], [35.0471, -88.7866], [32.796, -96.5894], [34.559, -97.357], [38.9917, -97.3713], [37.7238, -90.0055], [32.357, -95.9549], [32.4571, -85.4362], [39.8243, -84.4632], [38.9689, -95.108], [36.1715, -85.6628], [31.2763, -90.1732], [31.4641, -89.7579], [31.5475, -89.6194], [31.6661, -89.4004], [31.81, -89.1863], [32.7045, -81.2899], [31.075, -89.9209], [46.09, -95.94], [46.11, -95.9]],
+                {"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
+            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+        
+    
+            var heat_map_b66a17aeb5714612b5e5eb5d33e771a5 = L.heatLayer(
+                [[32.7003, -90.6783], [32.9456, -90.1539], [34.2203, -85.9602], [35.1808, -97.4273], [35.377, -97.305], [45.45, -99.71], [41.5512, -83.538], [46.11, -95.425], [47.54, -97.3], [47.68, -97.32], [46.41, -95.18], [46.43, -95.15], [43.5755, -93.6404], [43.404, -95.8605], [46.11, -96.63], [46.13, -96.563], [31.7947, -92.808], [42.7293, -94.8557], [38.7364, -90.4863], [32.7992, -89.1088], [34.0757, -87.0097], [32.9017, -88.9145], [32.9262, -88.8719], [34.1043, -88.1479], [34.3054, -86.6549], [34.3528, -86.5813], [34.3109, -87.7858], [34.0455, -88.445], [34.4368, -87.5307], [34.0891, -88.36], [34.6208, -85.9814], [34.662, -87.0705], [34.82, -85.6314], [33.6448, -87.4238], [34.8017, -86.7855], [33.0606, -87.8315], [33.8668, -86.995], [34.7948, -85.909], [33.3512, -87.1975], [32.0712, -89.3201], [34.3907, -85.9784], [32.1439, -88.9154], [33.6839, -86.5234], [33.8291, -86.0526], [35.5324, -84.0504], [35.5459, -84.0274], [35.34, -85.42], [35.3969, -85.3253], [34.8744, -85.1785], [34.9868, -85.0485], [35.0371, -84.9875], [32.7545, -85.8826], [35.5535, -85.1077], [37.056, -94.5701], [35.444, -98.287], [35.008, -97.961], [34.939, -97.67], [35.189, -97.67], [35.3182, -93.9044], [34.357, -99.194], [37.6945, -88.65], [37.771, -88.3751], [38.4316, -86.1893], [38.5156, -85.8678], [38.6061, -85.5808], [38.6096, -85.57], [38.796, -84.6092], [38.523, -98.008], [31.2802, -89.4665], [32.412, -97.754], [38.1429, -99.4706], [35.308, -97.142], [35.284, -97.628], [35.303, -97.605], [42.128, -97.077], [42.3319, -96.1086], [40.622, -89.5678], [38.42, -89.45], [34.913, -92.4572], [32.932, -89.3067], [41.893, -97.33], [41.9528, -97.1369], [41.9797, -97.0198], [42.0908, -96.931], [42.127, -96.8686], [44.0372, -98.4032], [41.8886, -89.2381], [34.5955, -89.7055], [34.6131, -89.6691], [34.8117, -89.2983], [34.9428, -89.0174], [34.9958, -88.8952], [35.0471, -88.7866], [32.796, -96.5894], [34.559, -97.357], [38.9917, -97.3713], [37.7238, -90.0055], [32.357, -95.9549], [32.4571, -85.4362], [39.8243, -84.4632], [38.9689, -95.108], [36.1715, -85.6628], [31.2763, -90.1732], [31.4641, -89.7579], [31.5475, -89.6194], [31.6661, -89.4004], [31.81, -89.1863], [32.7045, -81.2899], [31.075, -89.9209], [46.09, -95.94], [46.11, -95.9]],
+                {"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
+            ).addTo(map_caa5ac6661f14f718f208d08c1c906fb);
+        
+</script>
\ No newline at end of file
diff --git a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
new file mode 100644
index 00000000..d85ff351
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
@@ -0,0 +1,394 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "beneficial-storm",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import folium\n",
+    "from folium.plugins import HeatMap\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import os\n",
+    "current_directory = os.getcwd()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "bigger-standing",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "location=[32.7003, -90.6783]\n",
+    "weather_data = pd.read_csv('/Users/abdullaahrobins/Documents/GitHub/CS506Spring2021Repository/NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv')\n",
+    "folium.Map(location=location, zoom_start=3)\n",
+    "heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]\n",
+    "heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])\n",
+    "# HeatMap(data=weather_data.groupby(['BEGIN_LAT', 'BEGIN_LON']).mean().reset_index().values.tolist(), radius=8, max_zoom=4).add_to(base_map)\n",
+    "# base_map.save('tornado_heat_map.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "prospective-career",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 111 entries, 0 to 110\n",
+      "Data columns (total 37 columns):\n",
+      " #   Column               Non-Null Count  Dtype  \n",
+      "---  ------               --------------  -----  \n",
+      " 0   EVENT_ID             111 non-null    int64  \n",
+      " 1   CZ_NAME_STR          111 non-null    object \n",
+      " 2   BEGIN_LOCATION       111 non-null    object \n",
+      " 3   BEGIN_DATE           111 non-null    object \n",
+      " 4   BEGIN_TIME           111 non-null    int64  \n",
+      " 5   EVENT_TYPE           111 non-null    object \n",
+      " 6   MAGNITUDE            111 non-null    object \n",
+      " 7   TOR_F_SCALE          111 non-null    object \n",
+      " 8   DEATHS_DIRECT        111 non-null    int64  \n",
+      " 9   INJURIES_DIRECT      111 non-null    int64  \n",
+      " 10  DAMAGE_PROPERTY_NUM  111 non-null    int64  \n",
+      " 11  DAMAGE_CROPS_NUM     111 non-null    int64  \n",
+      " 12  STATE_ABBR           111 non-null    object \n",
+      " 13  CZ_TIMEZONE          111 non-null    object \n",
+      " 14  MAGNITUDE_TYPE       111 non-null    object \n",
+      " 15  EPISODE_ID           111 non-null    int64  \n",
+      " 16  CZ_TYPE              111 non-null    object \n",
+      " 17  CZ_FIPS              111 non-null    int64  \n",
+      " 18  WFO                  111 non-null    object \n",
+      " 19  INJURIES_INDIRECT    111 non-null    int64  \n",
+      " 20  DEATHS_INDIRECT      111 non-null    int64  \n",
+      " 21  SOURCE               111 non-null    object \n",
+      " 22  FLOOD_CAUSE          111 non-null    object \n",
+      " 23  TOR_LENGTH           111 non-null    float64\n",
+      " 24  TOR_WIDTH            111 non-null    float64\n",
+      " 25  BEGIN_RANGE          111 non-null    int64  \n",
+      " 26  BEGIN_AZIMUTH        111 non-null    object \n",
+      " 27  END_RANGE            111 non-null    int64  \n",
+      " 28  END_AZIMUTH          111 non-null    object \n",
+      " 29  END_LOCATION         111 non-null    object \n",
+      " 30  BEGIN_LAT            111 non-null    float64\n",
+      " 31  BEGIN_LON            111 non-null    float64\n",
+      " 32  END_LAT              111 non-null    float64\n",
+      " 33  END_LON              111 non-null    float64\n",
+      " 34  EVENT_NARRATIVE      111 non-null    object \n",
+      " 35  EPISODE_NARRATIVE    111 non-null    object \n",
+      " 36  ABSOLUTE_ROWNUMBER   111 non-null    int64  \n",
+      "dtypes: float64(6), int64(13), object(18)\n",
+      "memory usage: 32.2+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "info = weather_data.info()\n",
+    "state_occ = weather_data['STATE_ABBR'].value_counts()\n",
+    "df = weather_data['STATE_ABBR'].value_counts().rename_axis('states').reset_index(name='counts')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "administrative-score",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 20 entries, 0 to 19\n",
+      "Data columns (total 2 columns):\n",
+      " #   Column  Non-Null Count  Dtype \n",
+      "---  ------  --------------  ----- \n",
+      " 0   states  20 non-null     object\n",
+      " 1   counts  20 non-null     int64 \n",
+      "dtypes: int64(1), object(1)\n",
+      "memory usage: 448.0+ bytes\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "owned-superior",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<folium.map.LayerControl at 0x1284f8050>"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "url = (\n",
+    "    \"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data\"\n",
+    ")\n",
+    "state_geo = f\"{url}/us-states.json\"\n",
+    "\n",
+    "m = folium.Map(location=location, zoom_start=3)\n",
+    "\n",
+    "folium.Choropleth(\n",
+    "    geo_data=state_geo,\n",
+    "    name=\"choropleth\",\n",
+    "    data=df,\n",
+    "    columns=[\"states\", \"counts\"],\n",
+    "    key_on=\"feature.id\",\n",
+    "    fill_color=\"YlGn\",\n",
+    "    fill_opacity=0.7,\n",
+    "    line_opacity=0.2,\n",
+    "    legend_name=\"Tornado Occurrances\",\n",
+    ").add_to(m)\n",
+    "\n",
+    "folium.LayerControl().add_to(m)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "manufactured-dictionary",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" 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+       "</div>"
+      ],
+      "text/plain": [
+       "     BEGIN_LAT  BEGIN_LON\n",
+       "0      32.7003   -90.6783\n",
+       "1      32.9456   -90.1539\n",
+       "2      34.2203   -85.9602\n",
+       "3      35.1808   -97.4273\n",
+       "4      35.3770   -97.3050\n",
+       "..         ...        ...\n",
+       "106    31.8100   -89.1863\n",
+       "107    32.7045   -81.2899\n",
+       "108    31.0750   -89.9209\n",
+       "109    46.0900   -95.9400\n",
+       "110    46.1100   -95.9000\n",
+       "\n",
+       "[111 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "heat_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "revised-peace",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<folium.plugins.heat_map.HeatMap at 0x129c52b10>"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "heat_data = [[row['BEGIN_LAT'],row['BEGIN_LON']] for index, row in heat_df.iterrows()]\n",
+    "HeatMap(heat_data).add_to(base_map)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "operating-consideration",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" 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onload=\"this.contentDocument.open();this.contentDocument.write(    decodeURIComponent(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x127108ed0>"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "base_map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "respected-marketplace",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "base_map.save('heatmap_weather.html')\n",
+    "base_map.save('choropleth_weather.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "impossible-friday",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py
new file mode 100644
index 00000000..3e35a554
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.py
@@ -0,0 +1,101 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[25]:
+
+
+import folium
+from folium.plugins import HeatMap
+import numpy as np
+import pandas as pd
+import os
+current_directory = os.getcwd()
+
+
+# In[26]:
+
+
+
+location=[32.7003, -90.6783]
+weather_data = pd.read_csv('/Users/abdullaahrobins/Documents/GitHub/CS506Spring2021Repository/NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv')
+base_map = folium.Map(location=location, zoom_start=3)
+heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]
+heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])
+
+
+# In[27]:
+
+
+info = weather_data.info()
+state_occ = weather_data['STATE_ABBR'].value_counts()
+df = weather_data['STATE_ABBR'].value_counts().rename_axis('states').reset_index(name='counts')
+
+
+# In[28]:
+
+
+df.info()
+
+
+# In[29]:
+
+
+url = (
+    "https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
+)
+state_geo = f"{url}/us-states.json"
+
+m = folium.Map(location=location, zoom_start=3)
+
+folium.Choropleth(
+    geo_data=state_geo,
+    name="choropleth",
+    data=df,
+    columns=["states", "counts"],
+    key_on="feature.id",
+    fill_color="YlGn",
+    fill_opacity=0.7,
+    line_opacity=0.2,
+    legend_name="Tornado Occurrances",
+).add_to(m)
+
+folium.LayerControl().add_to(m)
+
+
+# In[30]:
+
+
+m
+
+
+# In[31]:
+
+
+heat_df
+
+
+# In[32]:
+
+
+heat_data = [[row['BEGIN_LAT'],row['BEGIN_LON']] for index, row in heat_df.iterrows()]
+HeatMap(heat_data).add_to(base_map)
+
+
+# In[33]:
+
+
+base_map
+
+
+# In[34]:
+
+
+base_map.save('heatmap_weather.html')
+m.save('choropleth_weather.html')
+
+
+# In[ ]:
+
+
+
+

From 23a5e4409e676d45323b2e9320237dbd854f7c19 Mon Sep 17 00:00:00 2001
From: varocarras <varocarras@gmail.com>
Date: Sat, 27 Feb 2021 17:22:11 -0500
Subject: [PATCH 10/38] Added simplified list of Tornado locations

Created by Abdullah
---
 NaturalDisasterProject/.DS_Store              | Bin 6148 -> 6148 bytes
 .../Datasets/export_dataframe.csv             | 112 ++++++++++++++++++
 2 files changed, 112 insertions(+)
 create mode 100644 NaturalDisasterProject/Datasets/export_dataframe.csv

diff --git a/NaturalDisasterProject/.DS_Store b/NaturalDisasterProject/.DS_Store
index 7058c63ac89d8cec35d8378d42d0a5fbfd12a965..62719c1a271db678176dccd82918767df0ad3dff 100644
GIT binary patch
delta 317
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zP7ZNZLtD>;+{&uzn%cUV3}C>>2%#DHp)`z|HCdT;cOox?3qvYH4nrnG8IUewNMuL?
z@=_V%84Nvh@{^Nt@{@oX1Q-|?e*$T}|6l+%0*}t5^5O!hPOzKPspe*&&3Npce4h3G
JW_FIh`~Zr(MP2{^

delta 95
zcmZoMXfc@J&&atkU^g=(=j1|Gk;w`y){Ms|JF+#Xi&a-!7?|iNnAhqkRGXU{09lsi
wwY8ia;;M$Wo(Z{?Rn;}Mb<-!mVv}c_0oH5Dx_q)Z`-P1Sk&K(!IsWnk05YT<ga7~l

diff --git a/NaturalDisasterProject/Datasets/export_dataframe.csv b/NaturalDisasterProject/Datasets/export_dataframe.csv
new file mode 100644
index 00000000..013ac25c
--- /dev/null
+++ b/NaturalDisasterProject/Datasets/export_dataframe.csv
@@ -0,0 +1,112 @@
+BEGIN_LOCATION,STATE_ABBR,BEGIN_DATE
+ENOLA,MS,04/24/2010
+ZEIGLERVILLE,MS,04/24/2010
+RODENTOWN,AL,04/24/2010
+NORMAN,OK,05/10/2010
+(TIK)TINKER AFB,OK,05/10/2010
+BOWDLE,SD,05/22/2010
+MOLINE,OH,06/05/2010
+URBANK,MN,06/17/2010
+PORTLAND JCT,ND,06/17/2010
+HOLMES,ND,06/17/2010
+BLUFFTON,MN,06/17/2010
+WADENA,MN,06/17/2010
+MANSFIELD,MN,06/17/2010
+SIBLEY,IA,06/25/2010
+TYLER,ND,08/07/2010
+DORAN,MN,08/07/2010
+ATLANTA,LA,11/29/2010
+VARINA,IA,04/09/2011
+VIGUS,MO,04/22/2011
+LONGINO,MS,04/27/2011
+CRANE HILL,AL,04/27/2011
+PRINCE CHAPEL,MS,04/27/2011
+FEARNS SPGS,MS,04/27/2011
+BARNESVILLE,AL,04/27/2011
+GUM POND,AL,04/27/2011
+RUTH,AL,04/27/2011
+NIX,AL,04/27/2011
+SMITHVILLE,MS,04/27/2011
+MT HOPE,AL,04/27/2011
+NEW SALEM,MS,04/27/2011
+HODGE,AL,04/27/2011
+LAWNGATE,AL,04/27/2011
+IDER,AL,04/27/2011
+MARIETTA,AL,04/27/2011
+CLUTTSVILLE,AL,04/27/2011
+RALPH,AL,04/27/2011
+ARKADELPHIA,AL,04/27/2011
+FACKLER,AL,04/27/2011
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+SANIE,AL,04/27/2011
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+MORGAN SPGS,TN,04/27/2011
+CENTRAL CITY,MO,05/22/2011
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+CRINER,OK,05/24/2011
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+CARRIERS MILLS,IL,02/29/2012
+EQUALITY,IL,02/29/2012
+FREDDRICKSBURG,IN,03/02/2012
+BLUE LICK,IN,03/02/2012
+NABB,IN,03/02/2012
+CHELSEA,IN,03/02/2012
+BRACHT,KY,03/02/2012
+KANAPOLIS RES,KS,04/14/2012
+OAK GROVE,MS,02/10/2013
+MAMBRINO,TX,05/15/2013
+BURDETT RUCKER ARPT,KS,05/18/2013
+PINK,OK,05/19/2013
+NEWCASTLE,OK,05/20/2013
+MOORE,OK,05/20/2013
+ALTONA,NE,10/04/2013
+CLIMBING HILL,IA,10/04/2013
+MARQUETTE HGTS,IL,11/17/2013
+ADDIEVILLE,IL,11/17/2013
+PALARM,AR,04/27/2014
+ZAMA,MS,04/28/2014
+STANTON,NE,06/16/2014
+STANTON,NE,06/16/2014
+WISNER,NE,06/16/2014
+ALTONA,NE,06/16/2014
+ALTONA,NE,06/16/2014
+LANE,SD,06/18/2014
+CARTHAGE,IL,04/09/2015
+TYRO,MS,12/23/2015
+CHULAHOMA,MS,12/23/2015
+ASHLAND,MS,12/23/2015
+TIPLERSVILLE,MS,12/23/2015
+POOR,TN,12/23/2015
+CHEWALLA,TN,12/23/2015
+NEW HOPE,TX,12/26/2015
+HENNEPIN,OK,05/09/2016
+SOLOMON,KS,05/25/2016
+SILVER LAKE,MO,02/28/2017
+BIG ROCK,TX,04/29/2017
+BUPREE,AL,03/03/2019
+PYRMONT,OH,05/27/2019
+LINWOOD,KS,05/28/2019
+ENSOR,TN,03/03/2020
+ENON,MS,04/12/2020
+BASSFIELD,MS,04/12/2020
+WILLIAMSBURG,MS,04/12/2020
+HEBRON,MS,04/12/2020
+MOSS,MS,04/12/2020
+ESTILL MUNI ARPT,SC,04/13/2020
+ST PAUL,MS,04/19/2020
+ASHBY,MN,07/08/2020
+DALTON,MN,07/08/2020

From 3f75295743611c23b3683f1b841d666129d27fd8 Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Sun, 28 Feb 2021 00:02:06 -0500
Subject: [PATCH 11/38] Python script to get weather data from API

gathered data from API & stored in dataframe & csv
---
 .../Deliverable_1/historical_data.csv         | 2851 ++++++++
 .../Deliverable_1/historical_data2.csv        | 3421 +++++++++
 .../Deliverable_1/historical_data_fin.csv     | 6271 +++++++++++++++++
 .../Deliverable_1/weather_data.py             |    0
 .../weather_data_transforming.ipynb           | 1047 ++-
 5 files changed, 13429 insertions(+), 161 deletions(-)
 create mode 100644 NaturalDisasterProject/Deliverable_1/historical_data.csv
 create mode 100644 NaturalDisasterProject/Deliverable_1/historical_data2.csv
 create mode 100644 NaturalDisasterProject/Deliverable_1/historical_data_fin.csv
 create mode 100644 NaturalDisasterProject/Deliverable_1/weather_data.py

diff --git a/NaturalDisasterProject/Deliverable_1/historical_data.csv b/NaturalDisasterProject/Deliverable_1/historical_data.csv
new file mode 100644
index 00000000..e287a872
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/historical_data.csv
@@ -0,0 +1,2851 @@
+datetime,temperature (degC),wind_speed (m/s),surface_solar_radiation (W/m^2),relative_humidity (0-1),surface_pressure (Pa),total_precipitation (mm of water equivalent),latitude,longitude
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diff --git a/NaturalDisasterProject/Deliverable_1/historical_data2.csv b/NaturalDisasterProject/Deliverable_1/historical_data2.csv
new file mode 100644
index 00000000..37004de0
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/historical_data2.csv
@@ -0,0 +1,3421 @@
+datetime,temperature (degC),wind_speed (m/s),surface_solar_radiation (W/m^2),relative_humidity (0-1),surface_pressure (Pa),total_precipitation (mm of water equivalent),latitude,longitude
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diff --git a/NaturalDisasterProject/Deliverable_1/historical_data_fin.csv b/NaturalDisasterProject/Deliverable_1/historical_data_fin.csv
new file mode 100644
index 00000000..4b2cc969
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/historical_data_fin.csv
@@ -0,0 +1,6271 @@
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diff --git a/NaturalDisasterProject/Deliverable_1/weather_data.py b/NaturalDisasterProject/Deliverable_1/weather_data.py
new file mode 100644
index 00000000..e69de29b
diff --git a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
index d85ff351..ec14c01e 100644
--- a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
+++ b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 30,
    "id": "beneficial-storm",
    "metadata": {},
    "outputs": [],
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 31,
    "id": "bigger-standing",
    "metadata": {},
    "outputs": [],
@@ -26,171 +26,121 @@
     "\n",
     "location=[32.7003, -90.6783]\n",
     "weather_data = pd.read_csv('/Users/abdullaahrobins/Documents/GitHub/CS506Spring2021Repository/NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv')\n",
-    "folium.Map(location=location, zoom_start=3)\n",
-    "heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]\n",
-    "heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])\n",
+    "# folium.Map(location=location, zoom_start=3)\n",
+    "# heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]\n",
+    "# heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])\n",
     "# HeatMap(data=weather_data.groupby(['BEGIN_LAT', 'BEGIN_LON']).mean().reset_index().values.tolist(), radius=8, max_zoom=4).add_to(base_map)\n",
     "# base_map.save('tornado_heat_map.html')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 4,
    "id": "prospective-career",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 111 entries, 0 to 110\n",
-      "Data columns (total 37 columns):\n",
-      " #   Column               Non-Null Count  Dtype  \n",
-      "---  ------               --------------  -----  \n",
-      " 0   EVENT_ID             111 non-null    int64  \n",
-      " 1   CZ_NAME_STR          111 non-null    object \n",
-      " 2   BEGIN_LOCATION       111 non-null    object \n",
-      " 3   BEGIN_DATE           111 non-null    object \n",
-      " 4   BEGIN_TIME           111 non-null    int64  \n",
-      " 5   EVENT_TYPE           111 non-null    object \n",
-      " 6   MAGNITUDE            111 non-null    object \n",
-      " 7   TOR_F_SCALE          111 non-null    object \n",
-      " 8   DEATHS_DIRECT        111 non-null    int64  \n",
-      " 9   INJURIES_DIRECT      111 non-null    int64  \n",
-      " 10  DAMAGE_PROPERTY_NUM  111 non-null    int64  \n",
-      " 11  DAMAGE_CROPS_NUM     111 non-null    int64  \n",
-      " 12  STATE_ABBR           111 non-null    object \n",
-      " 13  CZ_TIMEZONE          111 non-null    object \n",
-      " 14  MAGNITUDE_TYPE       111 non-null    object \n",
-      " 15  EPISODE_ID           111 non-null    int64  \n",
-      " 16  CZ_TYPE              111 non-null    object \n",
-      " 17  CZ_FIPS              111 non-null    int64  \n",
-      " 18  WFO                  111 non-null    object \n",
-      " 19  INJURIES_INDIRECT    111 non-null    int64  \n",
-      " 20  DEATHS_INDIRECT      111 non-null    int64  \n",
-      " 21  SOURCE               111 non-null    object \n",
-      " 22  FLOOD_CAUSE          111 non-null    object \n",
-      " 23  TOR_LENGTH           111 non-null    float64\n",
-      " 24  TOR_WIDTH            111 non-null    float64\n",
-      " 25  BEGIN_RANGE          111 non-null    int64  \n",
-      " 26  BEGIN_AZIMUTH        111 non-null    object \n",
-      " 27  END_RANGE            111 non-null    int64  \n",
-      " 28  END_AZIMUTH          111 non-null    object \n",
-      " 29  END_LOCATION         111 non-null    object \n",
-      " 30  BEGIN_LAT            111 non-null    float64\n",
-      " 31  BEGIN_LON            111 non-null    float64\n",
-      " 32  END_LAT              111 non-null    float64\n",
-      " 33  END_LON              111 non-null    float64\n",
-      " 34  EVENT_NARRATIVE      111 non-null    object \n",
-      " 35  EPISODE_NARRATIVE    111 non-null    object \n",
-      " 36  ABSOLUTE_ROWNUMBER   111 non-null    int64  \n",
-      "dtypes: float64(6), int64(13), object(18)\n",
-      "memory usage: 32.2+ KB\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "info = weather_data.info()\n",
-    "state_occ = weather_data['STATE_ABBR'].value_counts()\n",
-    "df = weather_data['STATE_ABBR'].value_counts().rename_axis('states').reset_index(name='counts')"
+    "# info = weather_data.info()\n",
+    "# state_occ = weather_data['STATE_ABBR'].value_counts()\n",
+    "# df = weather_data['STATE_ABBR'].value_counts().rename_axis('states').reset_index(name='counts')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 5,
    "id": "administrative-score",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 20 entries, 0 to 19\n",
-      "Data columns (total 2 columns):\n",
-      " #   Column  Non-Null Count  Dtype \n",
-      "---  ------  --------------  ----- \n",
-      " 0   states  20 non-null     object\n",
-      " 1   counts  20 non-null     int64 \n",
-      "dtypes: int64(1), object(1)\n",
-      "memory usage: 448.0+ bytes\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "df.info()"
+    "# df.info()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 6,
    "id": "owned-superior",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<folium.map.LayerControl at 0x1284f8050>"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "url = (\n",
-    "    \"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data\"\n",
-    ")\n",
-    "state_geo = f\"{url}/us-states.json\"\n",
+    "# url = (\n",
+    "#     \"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data\"\n",
+    "# )\n",
+    "# state_geo = f\"{url}/us-states.json\"\n",
     "\n",
-    "m = folium.Map(location=location, zoom_start=3)\n",
+    "# m = folium.Map(location=location, zoom_start=3)\n",
     "\n",
-    "folium.Choropleth(\n",
-    "    geo_data=state_geo,\n",
-    "    name=\"choropleth\",\n",
-    "    data=df,\n",
-    "    columns=[\"states\", \"counts\"],\n",
-    "    key_on=\"feature.id\",\n",
-    "    fill_color=\"YlGn\",\n",
-    "    fill_opacity=0.7,\n",
-    "    line_opacity=0.2,\n",
-    "    legend_name=\"Tornado Occurrances\",\n",
-    ").add_to(m)\n",
+    "# folium.Choropleth(\n",
+    "#     geo_data=state_geo,\n",
+    "#     name=\"choropleth\",\n",
+    "#     data=df,\n",
+    "#     columns=[\"states\", \"counts\"],\n",
+    "#     key_on=\"feature.id\",\n",
+    "#     fill_color=\"YlGn\",\n",
+    "#     fill_opacity=0.7,\n",
+    "#     line_opacity=0.2,\n",
+    "#     legend_name=\"Tornado Occurrances\",\n",
+    "# ).add_to(m)\n",
     "\n",
-    "folium.LayerControl().add_to(m)"
+    "# folium.LayerControl().add_to(m)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 7,
    "id": "manufactured-dictionary",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" 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onload=\"this.contentDocument.open();this.contentDocument.write(    decodeURIComponent(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
-      ],
-      "text/plain": [
-       "<folium.folium.Map at 0x129c1ad50>"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "m"
+    "# m"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 8,
    "id": "passive-density",
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# heat_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "revised-peace",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# heat_data = [[row['BEGIN_LAT'],row['BEGIN_LON']] for index, row in heat_df.iterrows()]\n",
+    "# HeatMap(heat_data).add_to(base_map)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "operating-consideration",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# base_map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "respected-marketplace",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# base_map.save('heatmap_weather.html')\n",
+    "# base_map.save('choropleth_weather.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "impossible-friday",
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -213,158 +163,933 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>EVENT_ID</th>\n",
+       "      <th>CZ_NAME_STR</th>\n",
+       "      <th>BEGIN_LOCATION</th>\n",
+       "      <th>BEGIN_DATE</th>\n",
+       "      <th>BEGIN_TIME</th>\n",
+       "      <th>EVENT_TYPE</th>\n",
+       "      <th>MAGNITUDE</th>\n",
+       "      <th>TOR_F_SCALE</th>\n",
+       "      <th>DEATHS_DIRECT</th>\n",
+       "      <th>INJURIES_DIRECT</th>\n",
+       "      <th>...</th>\n",
+       "      <th>END_RANGE</th>\n",
+       "      <th>END_AZIMUTH</th>\n",
+       "      <th>END_LOCATION</th>\n",
        "      <th>BEGIN_LAT</th>\n",
        "      <th>BEGIN_LON</th>\n",
+       "      <th>END_LAT</th>\n",
+       "      <th>END_LON</th>\n",
+       "      <th>EVENT_NARRATIVE</th>\n",
+       "      <th>EPISODE_NARRATIVE</th>\n",
+       "      <th>ABSOLUTE_ROWNUMBER</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
+       "      <td>224551</td>\n",
+       "      <td>YAZOO CO.</td>\n",
+       "      <td>ENOLA</td>\n",
+       "      <td>04/24/2010</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>53</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3</td>\n",
+       "      <td>NNW</td>\n",
+       "      <td>FORDYKE</td>\n",
        "      <td>32.7003</td>\n",
        "      <td>-90.6783</td>\n",
+       "      <td>32.9456</td>\n",
+       "      <td>-90.1539</td>\n",
+       "      <td>The tornado moved out of extreme southeast Sha...</td>\n",
+       "      <td>During the midday hours of April 24th, an inte...</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
+       "      <td>224552</td>\n",
+       "      <td>HOLMES CO.</td>\n",
+       "      <td>ZEIGLERVILLE</td>\n",
+       "      <td>04/24/2010</td>\n",
+       "      <td>1133</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>40</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3</td>\n",
+       "      <td>E</td>\n",
+       "      <td>DURANT</td>\n",
        "      <td>32.9456</td>\n",
        "      <td>-90.1539</td>\n",
+       "      <td>33.0802</td>\n",
+       "      <td>-89.8241</td>\n",
+       "      <td>The tornado continued northeast into rural sou...</td>\n",
+       "      <td>During the midday hours of April 24th, an inte...</td>\n",
+       "      <td>2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
+       "      <td>220277</td>\n",
+       "      <td>DEKALB CO.</td>\n",
+       "      <td>RODENTOWN</td>\n",
+       "      <td>04/24/2010</td>\n",
+       "      <td>2301</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>ESE</td>\n",
+       "      <td>DOG TOWN</td>\n",
        "      <td>34.2203</td>\n",
        "      <td>-85.9602</td>\n",
+       "      <td>34.3439</td>\n",
+       "      <td>-85.7105</td>\n",
+       "      <td>A long track tornado began it's 16.6 mile path...</td>\n",
+       "      <td>Four damaging tornadoes tore tracks through no...</td>\n",
+       "      <td>3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
+       "      <td>231948</td>\n",
+       "      <td>CLEVELAND CO.</td>\n",
+       "      <td>NORMAN</td>\n",
+       "      <td>05/10/2010</td>\n",
+       "      <td>1632</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>32</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5</td>\n",
+       "      <td>ENE</td>\n",
+       "      <td>LAKE THUNDERBIRD DAM</td>\n",
        "      <td>35.1808</td>\n",
        "      <td>-97.4273</td>\n",
+       "      <td>35.2490</td>\n",
+       "      <td>-97.1420</td>\n",
+       "      <td>This tornado is labeled #J1, and moved into Po...</td>\n",
+       "      <td>A significant outbreak of severe thunderstorms...</td>\n",
+       "      <td>4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
+       "      <td>231939</td>\n",
+       "      <td>OKLAHOMA CO.</td>\n",
+       "      <td>(TIK)TINKER AFB</td>\n",
+       "      <td>05/10/2010</td>\n",
+       "      <td>1635</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>29</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>SSE</td>\n",
+       "      <td>HARRAH</td>\n",
        "      <td>35.3770</td>\n",
        "      <td>-97.3050</td>\n",
+       "      <td>35.4700</td>\n",
+       "      <td>-97.1550</td>\n",
+       "      <td>This tornado is a continuation of the tornado ...</td>\n",
+       "      <td>A significant outbreak of severe thunderstorms...</td>\n",
+       "      <td>5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>106</th>\n",
+       "      <td>902844</td>\n",
+       "      <td>JASPER CO.</td>\n",
+       "      <td>MOSS</td>\n",
+       "      <td>04/12/2020</td>\n",
+       "      <td>1559</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5</td>\n",
+       "      <td>S</td>\n",
+       "      <td>ORANGE</td>\n",
        "      <td>31.8100</td>\n",
        "      <td>-89.1863</td>\n",
+       "      <td>32.0311</td>\n",
+       "      <td>-88.9125</td>\n",
+       "      <td>This violent, deadly tornado traveled 68 miles...</td>\n",
+       "      <td>An outbreak of severe weather occurred on East...</td>\n",
+       "      <td>107</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>107</th>\n",
+       "      <td>889068</td>\n",
+       "      <td>HAMPTON CO.</td>\n",
+       "      <td>ESTILL MUNI ARPT</td>\n",
+       "      <td>04/13/2020</td>\n",
+       "      <td>510</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>5</td>\n",
+       "      <td>60</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5</td>\n",
+       "      <td>NE</td>\n",
+       "      <td>FECHTIG</td>\n",
        "      <td>32.7045</td>\n",
        "      <td>-81.2899</td>\n",
+       "      <td>32.8290</td>\n",
+       "      <td>-80.9092</td>\n",
+       "      <td>A National Weather Service Storm Survey Team c...</td>\n",
+       "      <td>A severe quasi-linear convective system (QLCS)...</td>\n",
+       "      <td>108</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>108</th>\n",
+       "      <td>899721</td>\n",
+       "      <td>MARION CO.</td>\n",
+       "      <td>ST PAUL</td>\n",
+       "      <td>04/19/2020</td>\n",
+       "      <td>1813</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4</td>\n",
+       "      <td>E</td>\n",
+       "      <td>PINEBUR</td>\n",
        "      <td>31.0750</td>\n",
        "      <td>-89.9209</td>\n",
+       "      <td>31.1348</td>\n",
+       "      <td>-89.6537</td>\n",
+       "      <td>This violent tornado began over southeastern W...</td>\n",
+       "      <td>A very unstable airmass was in place across th...</td>\n",
+       "      <td>109</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>109</th>\n",
+       "      <td>898306</td>\n",
+       "      <td>GRANT CO.</td>\n",
+       "      <td>ASHBY</td>\n",
+       "      <td>07/08/2020</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4</td>\n",
+       "      <td>W</td>\n",
+       "      <td>ASHBY</td>\n",
        "      <td>46.0900</td>\n",
        "      <td>-95.9400</td>\n",
+       "      <td>46.1100</td>\n",
+       "      <td>-95.9000</td>\n",
+       "      <td>This tornado began in Grant County, but after ...</td>\n",
+       "      <td>A lone weak cell appeared on radar at 430 pm C...</td>\n",
+       "      <td>110</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>110</th>\n",
+       "      <td>898307</td>\n",
+       "      <td>OTTER TAIL CO.</td>\n",
+       "      <td>DALTON</td>\n",
+       "      <td>07/08/2020</td>\n",
+       "      <td>1615</td>\n",
+       "      <td>Tornado</td>\n",
+       "      <td></td>\n",
+       "      <td>EF4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5</td>\n",
+       "      <td>E</td>\n",
+       "      <td>DALTON</td>\n",
        "      <td>46.1100</td>\n",
        "      <td>-95.9000</td>\n",
+       "      <td>46.1700</td>\n",
+       "      <td>-95.7955</td>\n",
+       "      <td>This tornado began in Grant County, but after ...</td>\n",
+       "      <td>A lone weak cell appeared on radar at 430 pm C...</td>\n",
+       "      <td>111</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>111 rows × 2 columns</p>\n",
+       "<p>111 rows × 37 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "     BEGIN_LAT  BEGIN_LON\n",
-       "0      32.7003   -90.6783\n",
-       "1      32.9456   -90.1539\n",
-       "2      34.2203   -85.9602\n",
-       "3      35.1808   -97.4273\n",
-       "4      35.3770   -97.3050\n",
-       "..         ...        ...\n",
-       "106    31.8100   -89.1863\n",
-       "107    32.7045   -81.2899\n",
-       "108    31.0750   -89.9209\n",
-       "109    46.0900   -95.9400\n",
-       "110    46.1100   -95.9000\n",
+       "     EVENT_ID     CZ_NAME_STR    BEGIN_LOCATION  BEGIN_DATE  BEGIN_TIME  \\\n",
+       "0      224551       YAZOO CO.             ENOLA  04/24/2010        1053   \n",
+       "1      224552      HOLMES CO.      ZEIGLERVILLE  04/24/2010        1133   \n",
+       "2      220277      DEKALB CO.         RODENTOWN  04/24/2010        2301   \n",
+       "3      231948   CLEVELAND CO.            NORMAN  05/10/2010        1632   \n",
+       "4      231939    OKLAHOMA CO.   (TIK)TINKER AFB  05/10/2010        1635   \n",
+       "..        ...             ...               ...         ...         ...   \n",
+       "106    902844      JASPER CO.              MOSS  04/12/2020        1559   \n",
+       "107    889068     HAMPTON CO.  ESTILL MUNI ARPT  04/13/2020         510   \n",
+       "108    899721      MARION CO.           ST PAUL  04/19/2020        1813   \n",
+       "109    898306       GRANT CO.             ASHBY  07/08/2020        1608   \n",
+       "110    898307  OTTER TAIL CO.            DALTON  07/08/2020        1615   \n",
+       "\n",
+       "    EVENT_TYPE MAGNITUDE TOR_F_SCALE  DEATHS_DIRECT  INJURIES_DIRECT  ...  \\\n",
+       "0      Tornado                   EF4              4               53  ...   \n",
+       "1      Tornado                   EF4              1               40  ...   \n",
+       "2      Tornado                   EF4              0                5  ...   \n",
+       "3      Tornado                   EF4              1               32  ...   \n",
+       "4      Tornado                   EF4              2               29  ...   \n",
+       "..         ...       ...         ...            ...              ...  ...   \n",
+       "106    Tornado                   EF4              0                6  ...   \n",
+       "107    Tornado                   EF4              5               60  ...   \n",
+       "108    Tornado                   EF4              1                0  ...   \n",
+       "109    Tornado                   EF4              0                0  ...   \n",
+       "110    Tornado                   EF4              1                2  ...   \n",
+       "\n",
+       "     END_RANGE  END_AZIMUTH          END_LOCATION BEGIN_LAT BEGIN_LON  \\\n",
+       "0            3          NNW               FORDYKE   32.7003  -90.6783   \n",
+       "1            3            E                DURANT   32.9456  -90.1539   \n",
+       "2            1          ESE              DOG TOWN   34.2203  -85.9602   \n",
+       "3            5          ENE  LAKE THUNDERBIRD DAM   35.1808  -97.4273   \n",
+       "4            1          SSE                HARRAH   35.3770  -97.3050   \n",
+       "..         ...          ...                   ...       ...       ...   \n",
+       "106          5            S                ORANGE   31.8100  -89.1863   \n",
+       "107          5           NE               FECHTIG   32.7045  -81.2899   \n",
+       "108          4            E               PINEBUR   31.0750  -89.9209   \n",
+       "109          4            W                 ASHBY   46.0900  -95.9400   \n",
+       "110          5            E                DALTON   46.1100  -95.9000   \n",
+       "\n",
+       "     END_LAT  END_LON                                    EVENT_NARRATIVE  \\\n",
+       "0    32.9456 -90.1539  The tornado moved out of extreme southeast Sha...   \n",
+       "1    33.0802 -89.8241  The tornado continued northeast into rural sou...   \n",
+       "2    34.3439 -85.7105  A long track tornado began it's 16.6 mile path...   \n",
+       "3    35.2490 -97.1420  This tornado is labeled #J1, and moved into Po...   \n",
+       "4    35.4700 -97.1550  This tornado is a continuation of the tornado ...   \n",
+       "..       ...      ...                                                ...   \n",
+       "106  32.0311 -88.9125  This violent, deadly tornado traveled 68 miles...   \n",
+       "107  32.8290 -80.9092  A National Weather Service Storm Survey Team c...   \n",
+       "108  31.1348 -89.6537  This violent tornado began over southeastern W...   \n",
+       "109  46.1100 -95.9000  This tornado began in Grant County, but after ...   \n",
+       "110  46.1700 -95.7955  This tornado began in Grant County, but after ...   \n",
+       "\n",
+       "                                     EPISODE_NARRATIVE  ABSOLUTE_ROWNUMBER  \n",
+       "0    During the midday hours of April 24th, an inte...                   1  \n",
+       "1    During the midday hours of April 24th, an inte...                   2  \n",
+       "2    Four damaging tornadoes tore tracks through no...                   3  \n",
+       "3    A significant outbreak of severe thunderstorms...                   4  \n",
+       "4    A significant outbreak of severe thunderstorms...                   5  \n",
+       "..                                                 ...                 ...  \n",
+       "106  An outbreak of severe weather occurred on East...                 107  \n",
+       "107  A severe quasi-linear convective system (QLCS)...                 108  \n",
+       "108  A very unstable airmass was in place across th...                 109  \n",
+       "109  A lone weak cell appeared on radar at 430 pm C...                 110  \n",
+       "110  A lone weak cell appeared on radar at 430 pm C...                 111  \n",
        "\n",
-       "[111 rows x 2 columns]"
+       "[111 rows x 37 columns]"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "heat_df"
+    "weather_data"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
-   "id": "revised-peace",
+   "execution_count": 33,
+   "id": "excellent-lobby",
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>BEGIN_LOCATION</th>\n",
+       "      <th>STATE_ABBR</th>\n",
+       "      <th>BEGIN_DATE</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ENOLA</td>\n",
+       "      <td>MS</td>\n",
+       "      <td>04/24/2010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ZEIGLERVILLE</td>\n",
+       "      <td>MS</td>\n",
+       "      <td>04/24/2010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>RODENTOWN</td>\n",
+       "      <td>AL</td>\n",
+       "      <td>04/24/2010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NORMAN</td>\n",
+       "      <td>OK</td>\n",
+       "      <td>05/10/2010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>(TIK)TINKER AFB</td>\n",
+       "      <td>OK</td>\n",
+       "      <td>05/10/2010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>106</th>\n",
+       "      <td>MOSS</td>\n",
+       "      <td>MS</td>\n",
+       "      <td>04/12/2020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>107</th>\n",
+       "      <td>ESTILL MUNI ARPT</td>\n",
+       "      <td>SC</td>\n",
+       "      <td>04/13/2020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>108</th>\n",
+       "      <td>ST PAUL</td>\n",
+       "      <td>MS</td>\n",
+       "      <td>04/19/2020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>109</th>\n",
+       "      <td>ASHBY</td>\n",
+       "      <td>MN</td>\n",
+       "      <td>07/08/2020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>110</th>\n",
+       "      <td>DALTON</td>\n",
+       "      <td>MN</td>\n",
+       "      <td>07/08/2020</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>111 rows × 3 columns</p>\n",
+       "</div>"
+      ],
       "text/plain": [
-       "<folium.plugins.heat_map.HeatMap at 0x129c52b10>"
+       "       BEGIN_LOCATION STATE_ABBR  BEGIN_DATE\n",
+       "0               ENOLA         MS  04/24/2010\n",
+       "1        ZEIGLERVILLE         MS  04/24/2010\n",
+       "2           RODENTOWN         AL  04/24/2010\n",
+       "3              NORMAN         OK  05/10/2010\n",
+       "4     (TIK)TINKER AFB         OK  05/10/2010\n",
+       "..                ...        ...         ...\n",
+       "106              MOSS         MS  04/12/2020\n",
+       "107  ESTILL MUNI ARPT         SC  04/13/2020\n",
+       "108           ST PAUL         MS  04/19/2020\n",
+       "109             ASHBY         MN  07/08/2020\n",
+       "110            DALTON         MN  07/08/2020\n",
+       "\n",
+       "[111 rows x 3 columns]"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "heat_data = [[row['BEGIN_LAT'],row['BEGIN_LON']] for index, row in heat_df.iterrows()]\n",
-    "HeatMap(heat_data).add_to(base_map)"
+    "weather_data[['BEGIN_LOCATION', 'STATE_ABBR', 'BEGIN_DATE']]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
-   "id": "operating-consideration",
+   "execution_count": 16,
+   "id": "connected-recognition",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weather_data[['BEGIN_LOCATION', 'STATE_ABBR', 'BEGIN_DATE']].to_csv('export_dataframe.csv', index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "honest-collector",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weather_data['BEGIN_DATE'] = pd.to_datetime(weather_data['BEGIN_DATE'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "solid-discretion",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "from datetime import timedelta\n",
+    "import json\n",
+    "'''\n",
+    "Formatting:\n",
+    "'start': '2010-01-01',\n",
+    "'end': '2018-12-31',\n",
+    "'''\n",
+    "c = 0\n",
+    "frames = []\n",
+    "for index, row in weather_data.iterrows():\n",
+    "    c+=1\n",
+    "    if c>50:\n",
+    "        break\n",
+    "    end_date = row.BEGIN_DATE\n",
+    "    begin_date = end_date - timedelta(weeks=8)\n",
+    "    lat = row.BEGIN_LAT\n",
+    "    lon = row.BEGIN_LON\n",
+    "    r = requests.get('https://api.oikolab.com/weather',\n",
+    "                     params={'param': ['temperature', 'wind_speed', 'surface_solar_radiation', 'relative_humidity', 'surface_pressure', 'total_precipitation'],\n",
+    "                             'start': begin_date,\n",
+    "                             'end': end_date,\n",
+    "                             'freq': 'D',\n",
+    "                             'lat': lat,\n",
+    "                             'lon': lon,\n",
+    "                             'api-key': 'b03998e660494c2e8165d41369c13248'}\n",
+    "                     )\n",
+    "    w_data = json.loads(r.json()['data'])\n",
+    "    history_df = pd.DataFrame(index=pd.to_datetime(w_data['index'], \n",
+    "                                       unit='s'),\n",
+    "                  data=w_data['data'],\n",
+    "                  columns=w_data['columns'])\n",
+    "    history_df['latitude'] = lat\n",
+    "    history_df['longitude'] = lon\n",
+    "    frames.append(history_df)\n",
+    "result = pd.concat(frames)\n",
+    "result.to_csv(\"historical_data.csv\", encoding='utf-8', index=False)\n",
+    "    \n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "atmospheric-andorra",
+   "metadata": {},
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "accompanied-franklin",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "inner-hepatitis",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "cosmetic-judges",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result.index.name = 'datetime'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "mediterranean-eleven",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result.to_csv(\"historical_data.csv\", encoding='utf-8')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "clear-component",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "from datetime import timedelta\n",
+    "import json\n",
+    "from itertools import islice\n",
+    "\n",
+    "'''\n",
+    "Formatting:\n",
+    "'start': '2010-01-01',\n",
+    "'end': '2018-12-31',\n",
+    "'''\n",
+    "c = 0\n",
+    "frames = []\n",
+    "for index, row in islice(weather_data.iterrows(),51,None):\n",
+    "    end_date = row.BEGIN_DATE\n",
+    "    begin_date = end_date - timedelta(weeks=8)\n",
+    "    lat = row.BEGIN_LAT\n",
+    "    lon = row.BEGIN_LON\n",
+    "    r = requests.get('https://api.oikolab.com/weather',\n",
+    "                     params={'param': ['temperature', 'wind_speed', 'surface_solar_radiation', 'relative_humidity', 'surface_pressure', 'total_precipitation'],\n",
+    "                             'start': begin_date,\n",
+    "                             'end': end_date,\n",
+    "                             'freq': 'D',\n",
+    "                             'lat': lat,\n",
+    "                             'lon': lon,\n",
+    "                             'api-key': 'b03998e660494c2e8165d41369c13248'}\n",
+    "                     )\n",
+    "    w_data = json.loads(r.json()['data'])\n",
+    "    history_df = pd.DataFrame(index=pd.to_datetime(w_data['index'], \n",
+    "                                       unit='s'),\n",
+    "                  data=w_data['data'],\n",
+    "                  columns=w_data['columns'])\n",
+    "    history_df['latitude'] = lat\n",
+    "    history_df['longitude'] = lon\n",
+    "    frames.append(history_df)\n",
+    "result2 = pd.concat(frames)\n",
+    "result2.index.name = 'datetime'\n",
+    "result2.to_csv(\"historical_data2.csv\", encoding='utf-8')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "gross-canyon",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
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onload=\"this.contentDocument.open();this.contentDocument.write(    decodeURIComponent(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>temperature (degC)</th>\n",
+       "      <th>wind_speed (m/s)</th>\n",
+       "      <th>surface_solar_radiation (W/m^2)</th>\n",
+       "      <th>relative_humidity (0-1)</th>\n",
+       "      <th>surface_pressure (Pa)</th>\n",
+       "      <th>total_precipitation (mm of water equivalent)</th>\n",
+       "      <th>latitude</th>\n",
+       "      <th>longitude</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>datetime</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2011-03-02</th>\n",
+       "      <td>15.46</td>\n",
+       "      <td>3.17</td>\n",
+       "      <td>233</td>\n",
+       "      <td>0.53</td>\n",
+       "      <td>100151</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>32.7545</td>\n",
+       "      <td>-85.8826</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-03-03</th>\n",
+       "      <td>14.66</td>\n",
+       "      <td>5.03</td>\n",
+       "      <td>150</td>\n",
+       "      <td>0.62</td>\n",
+       "      <td>100264</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>32.7545</td>\n",
+       "      <td>-85.8826</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-03-04</th>\n",
+       "      <td>13.80</td>\n",
+       "      <td>4.30</td>\n",
+       "      <td>54</td>\n",
+       "      <td>0.87</td>\n",
+       "      <td>99872</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>32.7545</td>\n",
+       "      <td>-85.8826</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-03-05</th>\n",
+       "      <td>9.99</td>\n",
+       "      <td>2.03</td>\n",
+       "      <td>174</td>\n",
+       "      <td>0.84</td>\n",
+       "      <td>99289</td>\n",
+       "      <td>1.73</td>\n",
+       "      <td>32.7545</td>\n",
+       "      <td>-85.8826</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-03-06</th>\n",
+       "      <td>6.34</td>\n",
+       "      <td>1.78</td>\n",
+       "      <td>180</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>99772</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>32.7545</td>\n",
+       "      <td>-85.8826</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-07-04</th>\n",
+       "      <td>26.76</td>\n",
+       "      <td>3.30</td>\n",
+       "      <td>331</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>97023</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>46.1100</td>\n",
+       "      <td>-95.9000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-07-05</th>\n",
+       "      <td>24.55</td>\n",
+       "      <td>1.61</td>\n",
+       "      <td>233</td>\n",
+       "      <td>0.69</td>\n",
+       "      <td>97004</td>\n",
+       "      <td>0.11</td>\n",
+       "      <td>46.1100</td>\n",
+       "      <td>-95.9000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-07-06</th>\n",
+       "      <td>24.38</td>\n",
+       "      <td>1.65</td>\n",
+       "      <td>287</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>96966</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>46.1100</td>\n",
+       "      <td>-95.9000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-07-07</th>\n",
+       "      <td>25.59</td>\n",
+       "      <td>3.91</td>\n",
+       "      <td>267</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>96431</td>\n",
+       "      <td>0.50</td>\n",
+       "      <td>46.1100</td>\n",
+       "      <td>-95.9000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-07-08</th>\n",
+       "      <td>31.23</td>\n",
+       "      <td>1.21</td>\n",
+       "      <td>290</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>96143</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>46.1100</td>\n",
+       "      <td>-95.9000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3420 rows × 8 columns</p>\n",
+       "</div>"
       ],
       "text/plain": [
-       "<folium.folium.Map at 0x127108ed0>"
+       "            temperature (degC)  wind_speed (m/s)  \\\n",
+       "datetime                                           \n",
+       "2011-03-02               15.46              3.17   \n",
+       "2011-03-03               14.66              5.03   \n",
+       "2011-03-04               13.80              4.30   \n",
+       "2011-03-05                9.99              2.03   \n",
+       "2011-03-06                6.34              1.78   \n",
+       "...                        ...               ...   \n",
+       "2020-07-04               26.76              3.30   \n",
+       "2020-07-05               24.55              1.61   \n",
+       "2020-07-06               24.38              1.65   \n",
+       "2020-07-07               25.59              3.91   \n",
+       "2020-07-08               31.23              1.21   \n",
+       "\n",
+       "            surface_solar_radiation (W/m^2)  relative_humidity (0-1)  \\\n",
+       "datetime                                                               \n",
+       "2011-03-02                              233                     0.53   \n",
+       "2011-03-03                              150                     0.62   \n",
+       "2011-03-04                               54                     0.87   \n",
+       "2011-03-05                              174                     0.84   \n",
+       "2011-03-06                              180                     0.68   \n",
+       "...                                     ...                      ...   \n",
+       "2020-07-04                              331                     0.61   \n",
+       "2020-07-05                              233                     0.69   \n",
+       "2020-07-06                              287                     0.68   \n",
+       "2020-07-07                              267                     0.68   \n",
+       "2020-07-08                              290                     0.56   \n",
+       "\n",
+       "            surface_pressure (Pa)  \\\n",
+       "datetime                            \n",
+       "2011-03-02                 100151   \n",
+       "2011-03-03                 100264   \n",
+       "2011-03-04                  99872   \n",
+       "2011-03-05                  99289   \n",
+       "2011-03-06                  99772   \n",
+       "...                           ...   \n",
+       "2020-07-04                  97023   \n",
+       "2020-07-05                  97004   \n",
+       "2020-07-06                  96966   \n",
+       "2020-07-07                  96431   \n",
+       "2020-07-08                  96143   \n",
+       "\n",
+       "            total_precipitation (mm of water equivalent)  latitude  longitude  \n",
+       "datetime                                                                       \n",
+       "2011-03-02                                          0.00   32.7545   -85.8826  \n",
+       "2011-03-03                                          0.00   32.7545   -85.8826  \n",
+       "2011-03-04                                          0.67   32.7545   -85.8826  \n",
+       "2011-03-05                                          1.73   32.7545   -85.8826  \n",
+       "2011-03-06                                          0.00   32.7545   -85.8826  \n",
+       "...                                                  ...       ...        ...  \n",
+       "2020-07-04                                          0.00   46.1100   -95.9000  \n",
+       "2020-07-05                                          0.11   46.1100   -95.9000  \n",
+       "2020-07-06                                          0.01   46.1100   -95.9000  \n",
+       "2020-07-07                                          0.50   46.1100   -95.9000  \n",
+       "2020-07-08                                          0.01   46.1100   -95.9000  \n",
+       "\n",
+       "[3420 rows x 8 columns]"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "base_map"
+    "result2"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
-   "id": "respected-marketplace",
+   "execution_count": 50,
+   "id": "biological-timothy",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result_fin = pd.concat([result,result2])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "advised-theater",
    "metadata": {},
    "outputs": [],
    "source": [
-    "base_map.save('heatmap_weather.html')\n",
-    "base_map.save('choropleth_weather.html')"
+    "result_fin.to_csv(\"historical_data_fin.csv\", encoding='utf-8')"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "impossible-friday",
+   "id": "imposed-jurisdiction",
    "metadata": {},
    "outputs": [],
    "source": []

From b34d00c26e2564b3a4f2395342d50c549372371f Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Sun, 28 Feb 2021 00:50:06 -0500
Subject: [PATCH 12/38] python notebook fix

---
 .DS_Store                                     |  Bin 8196 -> 8196 bytes
 NaturalDisasterProject/.DS_Store              |  Bin 6148 -> 6148 bytes
 .../Deliverable_1/weather_data_scripts.ipynb  |  233 ++++
 .../weather_data_transforming.ipynb           | 1119 -----------------
 4 files changed, 233 insertions(+), 1119 deletions(-)
 create mode 100644 NaturalDisasterProject/Deliverable_1/weather_data_scripts.ipynb
 delete mode 100644 NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb

diff --git a/.DS_Store b/.DS_Store
index 33a087ec5ca6398fdde57b3d0376843cada3caaa..7add333b4740c32b5e02b353d605668c02087f1b 100644
GIT binary patch
delta 61
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B6JP)U

delta 86
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NW|wefC8W%b2>|WJ91#Ej

diff --git a/NaturalDisasterProject/.DS_Store b/NaturalDisasterProject/.DS_Store
index 7058c63ac89d8cec35d8378d42d0a5fbfd12a965..8c997c13430072c16c73461441f811642df87b65 100644
GIT binary patch
delta 65
zcmZoMXfc@J&&ahgU^g=(*Jd7;ON`3A3@!|*3^@#$3}ryNh#`?73CK%jh-WZNDNfEw
S%FoZ)e2bNhX)`;=Uw!~9g%OMZ

delta 32
ocmZoMXfc@J&&atkU^g=(=Vl(3ON^UY*_fCnHmGlA=lIJH0H3D`c>n+a

diff --git a/NaturalDisasterProject/Deliverable_1/weather_data_scripts.ipynb b/NaturalDisasterProject/Deliverable_1/weather_data_scripts.ipynb
new file mode 100644
index 00000000..b31498ee
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/weather_data_scripts.ipynb
@@ -0,0 +1,233 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "solid-order",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import folium\n",
+    "from folium.plugins import HeatMap\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import os\n",
+    "current_directory = os.getcwd()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "another-fetish",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "location=[32.7003, -90.6783]\n",
+    "weather_data = pd.read_csv('/Users/abdullaahrobins/Documents/GitHub/CS506Spring2021Repository/NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv')\n",
+    "# folium.Map(location=location, zoom_start=3)\n",
+    "# heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]\n",
+    "# heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])\n",
+    "# HeatMap(data=weather_data.groupby(['BEGIN_LAT', 'BEGIN_LON']).mean().reset_index().values.tolist(), radius=8, max_zoom=4).add_to(base_map)\n",
+    "# base_map.save('tornado_heat_map.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "geological-directory",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# info = weather_data.info()\n",
+    "# state_occ = weather_data['STATE_ABBR'].value_counts()\n",
+    "# df = weather_data['STATE_ABBR'].value_counts().rename_axis('states').reset_index(name='counts')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "developmental-lambda",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# url = (\n",
+    "#     \"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data\"\n",
+    "# )\n",
+    "# state_geo = f\"{url}/us-states.json\"\n",
+    "\n",
+    "# m = folium.Map(location=location, zoom_start=3)\n",
+    "\n",
+    "# folium.Choropleth(\n",
+    "#     geo_data=state_geo,\n",
+    "#     name=\"choropleth\",\n",
+    "#     data=df,\n",
+    "#     columns=[\"states\", \"counts\"],\n",
+    "#     key_on=\"feature.id\",\n",
+    "#     fill_color=\"YlGn\",\n",
+    "#     fill_opacity=0.7,\n",
+    "#     line_opacity=0.2,\n",
+    "#     legend_name=\"Tornado Occurrances\",\n",
+    "# ).add_to(m)\n",
+    "\n",
+    "# folium.LayerControl().add_to(m)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "crude-softball",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# heat_data = [[row['BEGIN_LAT'],row['BEGIN_LON']] for index, row in heat_df.iterrows()]\n",
+    "# HeatMap(heat_data).add_to(base_map)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "animal-overall",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# base_map.save('heatmap_weather.html')\n",
+    "# base_map.save('choropleth_weather.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "unique-panel",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weather_data['BEGIN_DATE'] = pd.to_datetime(weather_data['BEGIN_DATE'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "purple-permit",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "from datetime import timedelta\n",
+    "import json\n",
+    "'''\n",
+    "Formatting:\n",
+    "'start': '2010-01-01',\n",
+    "'end': '2018-12-31',\n",
+    "'''\n",
+    "c = 0\n",
+    "frames = []\n",
+    "for index, row in weather_data.iterrows():\n",
+    "    c+=1\n",
+    "    if c>50:\n",
+    "        break\n",
+    "    end_date = row.BEGIN_DATE\n",
+    "    begin_date = end_date - timedelta(weeks=8)\n",
+    "    lat = row.BEGIN_LAT\n",
+    "    lon = row.BEGIN_LON\n",
+    "    r = requests.get('https://api.oikolab.com/weather',\n",
+    "                     params={'param': ['temperature', 'wind_speed', 'surface_solar_radiation', 'relative_humidity', 'surface_pressure', 'total_precipitation'],\n",
+    "                             'start': begin_date,\n",
+    "                             'end': end_date,\n",
+    "                             'freq': 'D',\n",
+    "                             'lat': lat,\n",
+    "                             'lon': lon,\n",
+    "                             'api-key': 'b03998e660494c2e8165d41369c13248'}\n",
+    "                     )\n",
+    "    w_data = json.loads(r.json()['data'])\n",
+    "    history_df = pd.DataFrame(index=pd.to_datetime(w_data['index'], \n",
+    "                                       unit='s'),\n",
+    "                  data=w_data['data'],\n",
+    "                  columns=w_data['columns'])\n",
+    "    history_df['latitude'] = lat\n",
+    "    history_df['longitude'] = lon\n",
+    "    frames.append(history_df)\n",
+    "result = pd.concat(frames)\n",
+    "result.index.name = 'datetime'\n",
+    "result.to_csv(\"historical_data.csv\", encoding='utf-8', index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "liquid-contrast",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "from datetime import timedelta\n",
+    "import json\n",
+    "from itertools import islice\n",
+    "\n",
+    "'''\n",
+    "Formatting:\n",
+    "'start': '2010-01-01',\n",
+    "'end': '2018-12-31',\n",
+    "'''\n",
+    "c = 0\n",
+    "frames = []\n",
+    "for index, row in islice(weather_data.iterrows(),51,None):\n",
+    "    end_date = row.BEGIN_DATE\n",
+    "    begin_date = end_date - timedelta(weeks=8)\n",
+    "    lat = row.BEGIN_LAT\n",
+    "    lon = row.BEGIN_LON\n",
+    "    r = requests.get('https://api.oikolab.com/weather',\n",
+    "                     params={'param': ['temperature', 'wind_speed', 'surface_solar_radiation', 'relative_humidity', 'surface_pressure', 'total_precipitation'],\n",
+    "                             'start': begin_date,\n",
+    "                             'end': end_date,\n",
+    "                             'freq': 'D',\n",
+    "                             'lat': lat,\n",
+    "                             'lon': lon,\n",
+    "                             'api-key': 'b03998e660494c2e8165d41369c13248'}\n",
+    "                     )\n",
+    "    w_data = json.loads(r.json()['data'])\n",
+    "    history_df = pd.DataFrame(index=pd.to_datetime(w_data['index'], \n",
+    "                                       unit='s'),\n",
+    "                  data=w_data['data'],\n",
+    "                  columns=w_data['columns'])\n",
+    "    history_df['latitude'] = lat\n",
+    "    history_df['longitude'] = lon\n",
+    "    frames.append(history_df)\n",
+    "result2 = pd.concat(frames)\n",
+    "result2.index.name = 'datetime'\n",
+    "result2.to_csv(\"historical_data2.csv\", encoding='utf-8')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "composed-fifteen",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result_fin = pd.concat([result,result2])\n",
+    "result_fin.to_csv(\"historical_data_fin.csv\", encoding='utf-8')\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb b/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
deleted file mode 100644
index ec14c01e..00000000
--- a/NaturalDisasterProject/Deliverable_1/weather_data_transforming.ipynb
+++ /dev/null
@@ -1,1119 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "id": "beneficial-storm",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import folium\n",
-    "from folium.plugins import HeatMap\n",
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "import os\n",
-    "current_directory = os.getcwd()\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "id": "bigger-standing",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "location=[32.7003, -90.6783]\n",
-    "weather_data = pd.read_csv('/Users/abdullaahrobins/Documents/GitHub/CS506Spring2021Repository/NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv')\n",
-    "# folium.Map(location=location, zoom_start=3)\n",
-    "# heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]\n",
-    "# heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])\n",
-    "# HeatMap(data=weather_data.groupby(['BEGIN_LAT', 'BEGIN_LON']).mean().reset_index().values.tolist(), radius=8, max_zoom=4).add_to(base_map)\n",
-    "# base_map.save('tornado_heat_map.html')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "prospective-career",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# info = weather_data.info()\n",
-    "# state_occ = weather_data['STATE_ABBR'].value_counts()\n",
-    "# df = weather_data['STATE_ABBR'].value_counts().rename_axis('states').reset_index(name='counts')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "administrative-score",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# df.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "owned-superior",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# url = (\n",
-    "#     \"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data\"\n",
-    "# )\n",
-    "# state_geo = f\"{url}/us-states.json\"\n",
-    "\n",
-    "# m = folium.Map(location=location, zoom_start=3)\n",
-    "\n",
-    "# folium.Choropleth(\n",
-    "#     geo_data=state_geo,\n",
-    "#     name=\"choropleth\",\n",
-    "#     data=df,\n",
-    "#     columns=[\"states\", \"counts\"],\n",
-    "#     key_on=\"feature.id\",\n",
-    "#     fill_color=\"YlGn\",\n",
-    "#     fill_opacity=0.7,\n",
-    "#     line_opacity=0.2,\n",
-    "#     legend_name=\"Tornado Occurrances\",\n",
-    "# ).add_to(m)\n",
-    "\n",
-    "# folium.LayerControl().add_to(m)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "manufactured-dictionary",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# m"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "passive-density",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# heat_df"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "revised-peace",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# heat_data = [[row['BEGIN_LAT'],row['BEGIN_LON']] for index, row in heat_df.iterrows()]\n",
-    "# HeatMap(heat_data).add_to(base_map)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "operating-consideration",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# base_map"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "respected-marketplace",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# base_map.save('heatmap_weather.html')\n",
-    "# base_map.save('choropleth_weather.html')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "id": "impossible-friday",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
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-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>EVENT_ID</th>\n",
-       "      <th>CZ_NAME_STR</th>\n",
-       "      <th>BEGIN_LOCATION</th>\n",
-       "      <th>BEGIN_DATE</th>\n",
-       "      <th>BEGIN_TIME</th>\n",
-       "      <th>EVENT_TYPE</th>\n",
-       "      <th>MAGNITUDE</th>\n",
-       "      <th>TOR_F_SCALE</th>\n",
-       "      <th>DEATHS_DIRECT</th>\n",
-       "      <th>INJURIES_DIRECT</th>\n",
-       "      <th>...</th>\n",
-       "      <th>END_RANGE</th>\n",
-       "      <th>END_AZIMUTH</th>\n",
-       "      <th>END_LOCATION</th>\n",
-       "      <th>BEGIN_LAT</th>\n",
-       "      <th>BEGIN_LON</th>\n",
-       "      <th>END_LAT</th>\n",
-       "      <th>END_LON</th>\n",
-       "      <th>EVENT_NARRATIVE</th>\n",
-       "      <th>EPISODE_NARRATIVE</th>\n",
-       "      <th>ABSOLUTE_ROWNUMBER</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>224551</td>\n",
-       "      <td>YAZOO CO.</td>\n",
-       "      <td>ENOLA</td>\n",
-       "      <td>04/24/2010</td>\n",
-       "      <td>1053</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>4</td>\n",
-       "      <td>53</td>\n",
-       "      <td>...</td>\n",
-       "      <td>3</td>\n",
-       "      <td>NNW</td>\n",
-       "      <td>FORDYKE</td>\n",
-       "      <td>32.7003</td>\n",
-       "      <td>-90.6783</td>\n",
-       "      <td>32.9456</td>\n",
-       "      <td>-90.1539</td>\n",
-       "      <td>The tornado moved out of extreme southeast Sha...</td>\n",
-       "      <td>During the midday hours of April 24th, an inte...</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>224552</td>\n",
-       "      <td>HOLMES CO.</td>\n",
-       "      <td>ZEIGLERVILLE</td>\n",
-       "      <td>04/24/2010</td>\n",
-       "      <td>1133</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>1</td>\n",
-       "      <td>40</td>\n",
-       "      <td>...</td>\n",
-       "      <td>3</td>\n",
-       "      <td>E</td>\n",
-       "      <td>DURANT</td>\n",
-       "      <td>32.9456</td>\n",
-       "      <td>-90.1539</td>\n",
-       "      <td>33.0802</td>\n",
-       "      <td>-89.8241</td>\n",
-       "      <td>The tornado continued northeast into rural sou...</td>\n",
-       "      <td>During the midday hours of April 24th, an inte...</td>\n",
-       "      <td>2</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>220277</td>\n",
-       "      <td>DEKALB CO.</td>\n",
-       "      <td>RODENTOWN</td>\n",
-       "      <td>04/24/2010</td>\n",
-       "      <td>2301</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>0</td>\n",
-       "      <td>5</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1</td>\n",
-       "      <td>ESE</td>\n",
-       "      <td>DOG TOWN</td>\n",
-       "      <td>34.2203</td>\n",
-       "      <td>-85.9602</td>\n",
-       "      <td>34.3439</td>\n",
-       "      <td>-85.7105</td>\n",
-       "      <td>A long track tornado began it's 16.6 mile path...</td>\n",
-       "      <td>Four damaging tornadoes tore tracks through no...</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>231948</td>\n",
-       "      <td>CLEVELAND CO.</td>\n",
-       "      <td>NORMAN</td>\n",
-       "      <td>05/10/2010</td>\n",
-       "      <td>1632</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>1</td>\n",
-       "      <td>32</td>\n",
-       "      <td>...</td>\n",
-       "      <td>5</td>\n",
-       "      <td>ENE</td>\n",
-       "      <td>LAKE THUNDERBIRD DAM</td>\n",
-       "      <td>35.1808</td>\n",
-       "      <td>-97.4273</td>\n",
-       "      <td>35.2490</td>\n",
-       "      <td>-97.1420</td>\n",
-       "      <td>This tornado is labeled #J1, and moved into Po...</td>\n",
-       "      <td>A significant outbreak of severe thunderstorms...</td>\n",
-       "      <td>4</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>231939</td>\n",
-       "      <td>OKLAHOMA CO.</td>\n",
-       "      <td>(TIK)TINKER AFB</td>\n",
-       "      <td>05/10/2010</td>\n",
-       "      <td>1635</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>2</td>\n",
-       "      <td>29</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1</td>\n",
-       "      <td>SSE</td>\n",
-       "      <td>HARRAH</td>\n",
-       "      <td>35.3770</td>\n",
-       "      <td>-97.3050</td>\n",
-       "      <td>35.4700</td>\n",
-       "      <td>-97.1550</td>\n",
-       "      <td>This tornado is a continuation of the tornado ...</td>\n",
-       "      <td>A significant outbreak of severe thunderstorms...</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>106</th>\n",
-       "      <td>902844</td>\n",
-       "      <td>JASPER CO.</td>\n",
-       "      <td>MOSS</td>\n",
-       "      <td>04/12/2020</td>\n",
-       "      <td>1559</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>0</td>\n",
-       "      <td>6</td>\n",
-       "      <td>...</td>\n",
-       "      <td>5</td>\n",
-       "      <td>S</td>\n",
-       "      <td>ORANGE</td>\n",
-       "      <td>31.8100</td>\n",
-       "      <td>-89.1863</td>\n",
-       "      <td>32.0311</td>\n",
-       "      <td>-88.9125</td>\n",
-       "      <td>This violent, deadly tornado traveled 68 miles...</td>\n",
-       "      <td>An outbreak of severe weather occurred on East...</td>\n",
-       "      <td>107</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>107</th>\n",
-       "      <td>889068</td>\n",
-       "      <td>HAMPTON CO.</td>\n",
-       "      <td>ESTILL MUNI ARPT</td>\n",
-       "      <td>04/13/2020</td>\n",
-       "      <td>510</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>5</td>\n",
-       "      <td>60</td>\n",
-       "      <td>...</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NE</td>\n",
-       "      <td>FECHTIG</td>\n",
-       "      <td>32.7045</td>\n",
-       "      <td>-81.2899</td>\n",
-       "      <td>32.8290</td>\n",
-       "      <td>-80.9092</td>\n",
-       "      <td>A National Weather Service Storm Survey Team c...</td>\n",
-       "      <td>A severe quasi-linear convective system (QLCS)...</td>\n",
-       "      <td>108</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>108</th>\n",
-       "      <td>899721</td>\n",
-       "      <td>MARION CO.</td>\n",
-       "      <td>ST PAUL</td>\n",
-       "      <td>04/19/2020</td>\n",
-       "      <td>1813</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>4</td>\n",
-       "      <td>E</td>\n",
-       "      <td>PINEBUR</td>\n",
-       "      <td>31.0750</td>\n",
-       "      <td>-89.9209</td>\n",
-       "      <td>31.1348</td>\n",
-       "      <td>-89.6537</td>\n",
-       "      <td>This violent tornado began over southeastern W...</td>\n",
-       "      <td>A very unstable airmass was in place across th...</td>\n",
-       "      <td>109</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>109</th>\n",
-       "      <td>898306</td>\n",
-       "      <td>GRANT CO.</td>\n",
-       "      <td>ASHBY</td>\n",
-       "      <td>07/08/2020</td>\n",
-       "      <td>1608</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>4</td>\n",
-       "      <td>W</td>\n",
-       "      <td>ASHBY</td>\n",
-       "      <td>46.0900</td>\n",
-       "      <td>-95.9400</td>\n",
-       "      <td>46.1100</td>\n",
-       "      <td>-95.9000</td>\n",
-       "      <td>This tornado began in Grant County, but after ...</td>\n",
-       "      <td>A lone weak cell appeared on radar at 430 pm C...</td>\n",
-       "      <td>110</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>110</th>\n",
-       "      <td>898307</td>\n",
-       "      <td>OTTER TAIL CO.</td>\n",
-       "      <td>DALTON</td>\n",
-       "      <td>07/08/2020</td>\n",
-       "      <td>1615</td>\n",
-       "      <td>Tornado</td>\n",
-       "      <td></td>\n",
-       "      <td>EF4</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2</td>\n",
-       "      <td>...</td>\n",
-       "      <td>5</td>\n",
-       "      <td>E</td>\n",
-       "      <td>DALTON</td>\n",
-       "      <td>46.1100</td>\n",
-       "      <td>-95.9000</td>\n",
-       "      <td>46.1700</td>\n",
-       "      <td>-95.7955</td>\n",
-       "      <td>This tornado began in Grant County, but after ...</td>\n",
-       "      <td>A lone weak cell appeared on radar at 430 pm C...</td>\n",
-       "      <td>111</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>111 rows × 37 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     EVENT_ID     CZ_NAME_STR    BEGIN_LOCATION  BEGIN_DATE  BEGIN_TIME  \\\n",
-       "0      224551       YAZOO CO.             ENOLA  04/24/2010        1053   \n",
-       "1      224552      HOLMES CO.      ZEIGLERVILLE  04/24/2010        1133   \n",
-       "2      220277      DEKALB CO.         RODENTOWN  04/24/2010        2301   \n",
-       "3      231948   CLEVELAND CO.            NORMAN  05/10/2010        1632   \n",
-       "4      231939    OKLAHOMA CO.   (TIK)TINKER AFB  05/10/2010        1635   \n",
-       "..        ...             ...               ...         ...         ...   \n",
-       "106    902844      JASPER CO.              MOSS  04/12/2020        1559   \n",
-       "107    889068     HAMPTON CO.  ESTILL MUNI ARPT  04/13/2020         510   \n",
-       "108    899721      MARION CO.           ST PAUL  04/19/2020        1813   \n",
-       "109    898306       GRANT CO.             ASHBY  07/08/2020        1608   \n",
-       "110    898307  OTTER TAIL CO.            DALTON  07/08/2020        1615   \n",
-       "\n",
-       "    EVENT_TYPE MAGNITUDE TOR_F_SCALE  DEATHS_DIRECT  INJURIES_DIRECT  ...  \\\n",
-       "0      Tornado                   EF4              4               53  ...   \n",
-       "1      Tornado                   EF4              1               40  ...   \n",
-       "2      Tornado                   EF4              0                5  ...   \n",
-       "3      Tornado                   EF4              1               32  ...   \n",
-       "4      Tornado                   EF4              2               29  ...   \n",
-       "..         ...       ...         ...            ...              ...  ...   \n",
-       "106    Tornado                   EF4              0                6  ...   \n",
-       "107    Tornado                   EF4              5               60  ...   \n",
-       "108    Tornado                   EF4              1                0  ...   \n",
-       "109    Tornado                   EF4              0                0  ...   \n",
-       "110    Tornado                   EF4              1                2  ...   \n",
-       "\n",
-       "     END_RANGE  END_AZIMUTH          END_LOCATION BEGIN_LAT BEGIN_LON  \\\n",
-       "0            3          NNW               FORDYKE   32.7003  -90.6783   \n",
-       "1            3            E                DURANT   32.9456  -90.1539   \n",
-       "2            1          ESE              DOG TOWN   34.2203  -85.9602   \n",
-       "3            5          ENE  LAKE THUNDERBIRD DAM   35.1808  -97.4273   \n",
-       "4            1          SSE                HARRAH   35.3770  -97.3050   \n",
-       "..         ...          ...                   ...       ...       ...   \n",
-       "106          5            S                ORANGE   31.8100  -89.1863   \n",
-       "107          5           NE               FECHTIG   32.7045  -81.2899   \n",
-       "108          4            E               PINEBUR   31.0750  -89.9209   \n",
-       "109          4            W                 ASHBY   46.0900  -95.9400   \n",
-       "110          5            E                DALTON   46.1100  -95.9000   \n",
-       "\n",
-       "     END_LAT  END_LON                                    EVENT_NARRATIVE  \\\n",
-       "0    32.9456 -90.1539  The tornado moved out of extreme southeast Sha...   \n",
-       "1    33.0802 -89.8241  The tornado continued northeast into rural sou...   \n",
-       "2    34.3439 -85.7105  A long track tornado began it's 16.6 mile path...   \n",
-       "3    35.2490 -97.1420  This tornado is labeled #J1, and moved into Po...   \n",
-       "4    35.4700 -97.1550  This tornado is a continuation of the tornado ...   \n",
-       "..       ...      ...                                                ...   \n",
-       "106  32.0311 -88.9125  This violent, deadly tornado traveled 68 miles...   \n",
-       "107  32.8290 -80.9092  A National Weather Service Storm Survey Team c...   \n",
-       "108  31.1348 -89.6537  This violent tornado began over southeastern W...   \n",
-       "109  46.1100 -95.9000  This tornado began in Grant County, but after ...   \n",
-       "110  46.1700 -95.7955  This tornado began in Grant County, but after ...   \n",
-       "\n",
-       "                                     EPISODE_NARRATIVE  ABSOLUTE_ROWNUMBER  \n",
-       "0    During the midday hours of April 24th, an inte...                   1  \n",
-       "1    During the midday hours of April 24th, an inte...                   2  \n",
-       "2    Four damaging tornadoes tore tracks through no...                   3  \n",
-       "3    A significant outbreak of severe thunderstorms...                   4  \n",
-       "4    A significant outbreak of severe thunderstorms...                   5  \n",
-       "..                                                 ...                 ...  \n",
-       "106  An outbreak of severe weather occurred on East...                 107  \n",
-       "107  A severe quasi-linear convective system (QLCS)...                 108  \n",
-       "108  A very unstable airmass was in place across th...                 109  \n",
-       "109  A lone weak cell appeared on radar at 430 pm C...                 110  \n",
-       "110  A lone weak cell appeared on radar at 430 pm C...                 111  \n",
-       "\n",
-       "[111 rows x 37 columns]"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "weather_data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "id": "excellent-lobby",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>BEGIN_LOCATION</th>\n",
-       "      <th>STATE_ABBR</th>\n",
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-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>ENOLA</td>\n",
-       "      <td>MS</td>\n",
-       "      <td>04/24/2010</td>\n",
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-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>ZEIGLERVILLE</td>\n",
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-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>RODENTOWN</td>\n",
-       "      <td>AL</td>\n",
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-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>NORMAN</td>\n",
-       "      <td>OK</td>\n",
-       "      <td>05/10/2010</td>\n",
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-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>(TIK)TINKER AFB</td>\n",
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-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
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-       "      <td>...</td>\n",
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-       "    <tr>\n",
-       "      <th>106</th>\n",
-       "      <td>MOSS</td>\n",
-       "      <td>MS</td>\n",
-       "      <td>04/12/2020</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>107</th>\n",
-       "      <td>ESTILL MUNI ARPT</td>\n",
-       "      <td>SC</td>\n",
-       "      <td>04/13/2020</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>108</th>\n",
-       "      <td>ST PAUL</td>\n",
-       "      <td>MS</td>\n",
-       "      <td>04/19/2020</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>109</th>\n",
-       "      <td>ASHBY</td>\n",
-       "      <td>MN</td>\n",
-       "      <td>07/08/2020</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>110</th>\n",
-       "      <td>DALTON</td>\n",
-       "      <td>MN</td>\n",
-       "      <td>07/08/2020</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>111 rows × 3 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       BEGIN_LOCATION STATE_ABBR  BEGIN_DATE\n",
-       "0               ENOLA         MS  04/24/2010\n",
-       "1        ZEIGLERVILLE         MS  04/24/2010\n",
-       "2           RODENTOWN         AL  04/24/2010\n",
-       "3              NORMAN         OK  05/10/2010\n",
-       "4     (TIK)TINKER AFB         OK  05/10/2010\n",
-       "..                ...        ...         ...\n",
-       "106              MOSS         MS  04/12/2020\n",
-       "107  ESTILL MUNI ARPT         SC  04/13/2020\n",
-       "108           ST PAUL         MS  04/19/2020\n",
-       "109             ASHBY         MN  07/08/2020\n",
-       "110            DALTON         MN  07/08/2020\n",
-       "\n",
-       "[111 rows x 3 columns]"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "weather_data[['BEGIN_LOCATION', 'STATE_ABBR', 'BEGIN_DATE']]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "connected-recognition",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "weather_data[['BEGIN_LOCATION', 'STATE_ABBR', 'BEGIN_DATE']].to_csv('export_dataframe.csv', index=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "id": "honest-collector",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "weather_data['BEGIN_DATE'] = pd.to_datetime(weather_data['BEGIN_DATE'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "id": "solid-discretion",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import requests\n",
-    "from datetime import timedelta\n",
-    "import json\n",
-    "'''\n",
-    "Formatting:\n",
-    "'start': '2010-01-01',\n",
-    "'end': '2018-12-31',\n",
-    "'''\n",
-    "c = 0\n",
-    "frames = []\n",
-    "for index, row in weather_data.iterrows():\n",
-    "    c+=1\n",
-    "    if c>50:\n",
-    "        break\n",
-    "    end_date = row.BEGIN_DATE\n",
-    "    begin_date = end_date - timedelta(weeks=8)\n",
-    "    lat = row.BEGIN_LAT\n",
-    "    lon = row.BEGIN_LON\n",
-    "    r = requests.get('https://api.oikolab.com/weather',\n",
-    "                     params={'param': ['temperature', 'wind_speed', 'surface_solar_radiation', 'relative_humidity', 'surface_pressure', 'total_precipitation'],\n",
-    "                             'start': begin_date,\n",
-    "                             'end': end_date,\n",
-    "                             'freq': 'D',\n",
-    "                             'lat': lat,\n",
-    "                             'lon': lon,\n",
-    "                             'api-key': 'b03998e660494c2e8165d41369c13248'}\n",
-    "                     )\n",
-    "    w_data = json.loads(r.json()['data'])\n",
-    "    history_df = pd.DataFrame(index=pd.to_datetime(w_data['index'], \n",
-    "                                       unit='s'),\n",
-    "                  data=w_data['data'],\n",
-    "                  columns=w_data['columns'])\n",
-    "    history_df['latitude'] = lat\n",
-    "    history_df['longitude'] = lon\n",
-    "    frames.append(history_df)\n",
-    "result = pd.concat(frames)\n",
-    "result.to_csv(\"historical_data.csv\", encoding='utf-8', index=False)\n",
-    "    \n",
-    "    "
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "id": "atmospheric-andorra",
-   "metadata": {},
-   "source": [
-    "result"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "id": "accompanied-franklin",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "id": "inner-hepatitis",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "id": "cosmetic-judges",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "result.index.name = 'datetime'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "id": "mediterranean-eleven",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "result.to_csv(\"historical_data.csv\", encoding='utf-8')\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "clear-component",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import requests\n",
-    "from datetime import timedelta\n",
-    "import json\n",
-    "from itertools import islice\n",
-    "\n",
-    "'''\n",
-    "Formatting:\n",
-    "'start': '2010-01-01',\n",
-    "'end': '2018-12-31',\n",
-    "'''\n",
-    "c = 0\n",
-    "frames = []\n",
-    "for index, row in islice(weather_data.iterrows(),51,None):\n",
-    "    end_date = row.BEGIN_DATE\n",
-    "    begin_date = end_date - timedelta(weeks=8)\n",
-    "    lat = row.BEGIN_LAT\n",
-    "    lon = row.BEGIN_LON\n",
-    "    r = requests.get('https://api.oikolab.com/weather',\n",
-    "                     params={'param': ['temperature', 'wind_speed', 'surface_solar_radiation', 'relative_humidity', 'surface_pressure', 'total_precipitation'],\n",
-    "                             'start': begin_date,\n",
-    "                             'end': end_date,\n",
-    "                             'freq': 'D',\n",
-    "                             'lat': lat,\n",
-    "                             'lon': lon,\n",
-    "                             'api-key': 'b03998e660494c2e8165d41369c13248'}\n",
-    "                     )\n",
-    "    w_data = json.loads(r.json()['data'])\n",
-    "    history_df = pd.DataFrame(index=pd.to_datetime(w_data['index'], \n",
-    "                                       unit='s'),\n",
-    "                  data=w_data['data'],\n",
-    "                  columns=w_data['columns'])\n",
-    "    history_df['latitude'] = lat\n",
-    "    history_df['longitude'] = lon\n",
-    "    frames.append(history_df)\n",
-    "result2 = pd.concat(frames)\n",
-    "result2.index.name = 'datetime'\n",
-    "result2.to_csv(\"historical_data2.csv\", encoding='utf-8')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "id": "gross-canyon",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>temperature (degC)</th>\n",
-       "      <th>wind_speed (m/s)</th>\n",
-       "      <th>surface_solar_radiation (W/m^2)</th>\n",
-       "      <th>relative_humidity (0-1)</th>\n",
-       "      <th>surface_pressure (Pa)</th>\n",
-       "      <th>total_precipitation (mm of water equivalent)</th>\n",
-       "      <th>latitude</th>\n",
-       "      <th>longitude</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>datetime</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2011-03-02</th>\n",
-       "      <td>15.46</td>\n",
-       "      <td>3.17</td>\n",
-       "      <td>233</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>100151</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>32.7545</td>\n",
-       "      <td>-85.8826</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2011-03-03</th>\n",
-       "      <td>14.66</td>\n",
-       "      <td>5.03</td>\n",
-       "      <td>150</td>\n",
-       "      <td>0.62</td>\n",
-       "      <td>100264</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>32.7545</td>\n",
-       "      <td>-85.8826</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2011-03-04</th>\n",
-       "      <td>13.80</td>\n",
-       "      <td>4.30</td>\n",
-       "      <td>54</td>\n",
-       "      <td>0.87</td>\n",
-       "      <td>99872</td>\n",
-       "      <td>0.67</td>\n",
-       "      <td>32.7545</td>\n",
-       "      <td>-85.8826</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2011-03-05</th>\n",
-       "      <td>9.99</td>\n",
-       "      <td>2.03</td>\n",
-       "      <td>174</td>\n",
-       "      <td>0.84</td>\n",
-       "      <td>99289</td>\n",
-       "      <td>1.73</td>\n",
-       "      <td>32.7545</td>\n",
-       "      <td>-85.8826</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2011-03-06</th>\n",
-       "      <td>6.34</td>\n",
-       "      <td>1.78</td>\n",
-       "      <td>180</td>\n",
-       "      <td>0.68</td>\n",
-       "      <td>99772</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>32.7545</td>\n",
-       "      <td>-85.8826</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-07-04</th>\n",
-       "      <td>26.76</td>\n",
-       "      <td>3.30</td>\n",
-       "      <td>331</td>\n",
-       "      <td>0.61</td>\n",
-       "      <td>97023</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>46.1100</td>\n",
-       "      <td>-95.9000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-07-05</th>\n",
-       "      <td>24.55</td>\n",
-       "      <td>1.61</td>\n",
-       "      <td>233</td>\n",
-       "      <td>0.69</td>\n",
-       "      <td>97004</td>\n",
-       "      <td>0.11</td>\n",
-       "      <td>46.1100</td>\n",
-       "      <td>-95.9000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-07-06</th>\n",
-       "      <td>24.38</td>\n",
-       "      <td>1.65</td>\n",
-       "      <td>287</td>\n",
-       "      <td>0.68</td>\n",
-       "      <td>96966</td>\n",
-       "      <td>0.01</td>\n",
-       "      <td>46.1100</td>\n",
-       "      <td>-95.9000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-07-07</th>\n",
-       "      <td>25.59</td>\n",
-       "      <td>3.91</td>\n",
-       "      <td>267</td>\n",
-       "      <td>0.68</td>\n",
-       "      <td>96431</td>\n",
-       "      <td>0.50</td>\n",
-       "      <td>46.1100</td>\n",
-       "      <td>-95.9000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-07-08</th>\n",
-       "      <td>31.23</td>\n",
-       "      <td>1.21</td>\n",
-       "      <td>290</td>\n",
-       "      <td>0.56</td>\n",
-       "      <td>96143</td>\n",
-       "      <td>0.01</td>\n",
-       "      <td>46.1100</td>\n",
-       "      <td>-95.9000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>3420 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            temperature (degC)  wind_speed (m/s)  \\\n",
-       "datetime                                           \n",
-       "2011-03-02               15.46              3.17   \n",
-       "2011-03-03               14.66              5.03   \n",
-       "2011-03-04               13.80              4.30   \n",
-       "2011-03-05                9.99              2.03   \n",
-       "2011-03-06                6.34              1.78   \n",
-       "...                        ...               ...   \n",
-       "2020-07-04               26.76              3.30   \n",
-       "2020-07-05               24.55              1.61   \n",
-       "2020-07-06               24.38              1.65   \n",
-       "2020-07-07               25.59              3.91   \n",
-       "2020-07-08               31.23              1.21   \n",
-       "\n",
-       "            surface_solar_radiation (W/m^2)  relative_humidity (0-1)  \\\n",
-       "datetime                                                               \n",
-       "2011-03-02                              233                     0.53   \n",
-       "2011-03-03                              150                     0.62   \n",
-       "2011-03-04                               54                     0.87   \n",
-       "2011-03-05                              174                     0.84   \n",
-       "2011-03-06                              180                     0.68   \n",
-       "...                                     ...                      ...   \n",
-       "2020-07-04                              331                     0.61   \n",
-       "2020-07-05                              233                     0.69   \n",
-       "2020-07-06                              287                     0.68   \n",
-       "2020-07-07                              267                     0.68   \n",
-       "2020-07-08                              290                     0.56   \n",
-       "\n",
-       "            surface_pressure (Pa)  \\\n",
-       "datetime                            \n",
-       "2011-03-02                 100151   \n",
-       "2011-03-03                 100264   \n",
-       "2011-03-04                  99872   \n",
-       "2011-03-05                  99289   \n",
-       "2011-03-06                  99772   \n",
-       "...                           ...   \n",
-       "2020-07-04                  97023   \n",
-       "2020-07-05                  97004   \n",
-       "2020-07-06                  96966   \n",
-       "2020-07-07                  96431   \n",
-       "2020-07-08                  96143   \n",
-       "\n",
-       "            total_precipitation (mm of water equivalent)  latitude  longitude  \n",
-       "datetime                                                                       \n",
-       "2011-03-02                                          0.00   32.7545   -85.8826  \n",
-       "2011-03-03                                          0.00   32.7545   -85.8826  \n",
-       "2011-03-04                                          0.67   32.7545   -85.8826  \n",
-       "2011-03-05                                          1.73   32.7545   -85.8826  \n",
-       "2011-03-06                                          0.00   32.7545   -85.8826  \n",
-       "...                                                  ...       ...        ...  \n",
-       "2020-07-04                                          0.00   46.1100   -95.9000  \n",
-       "2020-07-05                                          0.11   46.1100   -95.9000  \n",
-       "2020-07-06                                          0.01   46.1100   -95.9000  \n",
-       "2020-07-07                                          0.50   46.1100   -95.9000  \n",
-       "2020-07-08                                          0.01   46.1100   -95.9000  \n",
-       "\n",
-       "[3420 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 49,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "result2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "id": "biological-timothy",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "result_fin = pd.concat([result,result2])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "id": "advised-theater",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "result_fin.to_csv(\"historical_data_fin.csv\", encoding='utf-8')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "imposed-jurisdiction",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.9"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

From 91d5102f1d27ae3b3e2ec10164f259d8461d0758 Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Sun, 28 Feb 2021 00:54:49 -0500
Subject: [PATCH 13/38] Python script to get weather data from API (#6)

* HeatMap/Transform Data

Transform weather data into heat map and choropleth map

* Fixed Chloropleth Map

* Python script to get weather data from API

gathered data from API & stored in dataframe & csv

* python notebook fix
---
 .DS_Store                                     |  Bin 8196 -> 8196 bytes
 NaturalDisasterProject/.DS_Store              |  Bin 6148 -> 6148 bytes
 .../Deliverable_1/historical_data.csv         | 2851 ++++++++
 .../Deliverable_1/historical_data2.csv        | 3421 +++++++++
 .../Deliverable_1/historical_data_fin.csv     | 6271 +++++++++++++++++
 .../Deliverable_1/weather_data.py             |    0
 .../Deliverable_1/weather_data_scripts.ipynb  |  233 +
 7 files changed, 12776 insertions(+)
 create mode 100644 NaturalDisasterProject/Deliverable_1/historical_data.csv
 create mode 100644 NaturalDisasterProject/Deliverable_1/historical_data2.csv
 create mode 100644 NaturalDisasterProject/Deliverable_1/historical_data_fin.csv
 create mode 100644 NaturalDisasterProject/Deliverable_1/weather_data.py
 create mode 100644 NaturalDisasterProject/Deliverable_1/weather_data_scripts.ipynb

diff --git a/.DS_Store b/.DS_Store
index 33a087ec5ca6398fdde57b3d0376843cada3caaa..7add333b4740c32b5e02b353d605668c02087f1b 100644
GIT binary patch
delta 61
zcmZp1XmQwZT4ZvdU<<p6g^q%*iRI)wf{v3Xi|B4XChEwvnN`A_l}o(38dK7N2>@&p
B6JP)U

delta 86
zcmZp1XmQwZT7>b`<TD}-Jd)MbW+uiu3c7{{7L)G?$}-NH{7X=tarWd1A_kj}h&nQD
NW|wefC8W%b2>|WJ91#Ej

diff --git a/NaturalDisasterProject/.DS_Store b/NaturalDisasterProject/.DS_Store
index 7058c63ac89d8cec35d8378d42d0a5fbfd12a965..8c997c13430072c16c73461441f811642df87b65 100644
GIT binary patch
delta 65
zcmZoMXfc@J&&ahgU^g=(*Jd7;ON`3A3@!|*3^@#$3}ryNh#`?73CK%jh-WZNDNfEw
S%FoZ)e2bNhX)`;=Uw!~9g%OMZ

delta 32
ocmZoMXfc@J&&atkU^g=(=Vl(3ON^UY*_fCnHmGlA=lIJH0H3D`c>n+a

diff --git a/NaturalDisasterProject/Deliverable_1/historical_data.csv b/NaturalDisasterProject/Deliverable_1/historical_data.csv
new file mode 100644
index 00000000..e287a872
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/historical_data.csv
@@ -0,0 +1,2851 @@
+datetime,temperature (degC),wind_speed (m/s),surface_solar_radiation (W/m^2),relative_humidity (0-1),surface_pressure (Pa),total_precipitation (mm of water equivalent),latitude,longitude
+2010-02-27,8.5,1.51,233,0.5,101170,0.0,32.7003,-90.6783
+2010-02-28,8.04,2.59,75,0.62,100953,0.19,32.7003,-90.6783
+2010-03-01,5.64,4.81,89,0.76,100742,0.3,32.7003,-90.6783
+2010-03-02,5.33,3.02,182,0.59,101282,0.0,32.7003,-90.6783
+2010-03-03,5.36,0.77,242,0.56,101601,0.0,32.7003,-90.6783
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diff --git a/NaturalDisasterProject/Deliverable_1/historical_data2.csv b/NaturalDisasterProject/Deliverable_1/historical_data2.csv
new file mode 100644
index 00000000..37004de0
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/historical_data2.csv
@@ -0,0 +1,3421 @@
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diff --git a/NaturalDisasterProject/Deliverable_1/historical_data_fin.csv b/NaturalDisasterProject/Deliverable_1/historical_data_fin.csv
new file mode 100644
index 00000000..4b2cc969
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/historical_data_fin.csv
@@ -0,0 +1,6271 @@
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diff --git a/NaturalDisasterProject/Deliverable_1/weather_data.py b/NaturalDisasterProject/Deliverable_1/weather_data.py
new file mode 100644
index 00000000..e69de29b
diff --git a/NaturalDisasterProject/Deliverable_1/weather_data_scripts.ipynb b/NaturalDisasterProject/Deliverable_1/weather_data_scripts.ipynb
new file mode 100644
index 00000000..b31498ee
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/weather_data_scripts.ipynb
@@ -0,0 +1,233 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "solid-order",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import folium\n",
+    "from folium.plugins import HeatMap\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import os\n",
+    "current_directory = os.getcwd()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "another-fetish",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "location=[32.7003, -90.6783]\n",
+    "weather_data = pd.read_csv('/Users/abdullaahrobins/Documents/GitHub/CS506Spring2021Repository/NaturalDisasterProject/Datasets/Tornado_Data_2010-2020.csv')\n",
+    "# folium.Map(location=location, zoom_start=3)\n",
+    "# heat_df = weather_data[['BEGIN_LAT', 'BEGIN_LON']]\n",
+    "# heat_df = heat_df.dropna(axis=0, subset=['BEGIN_LAT','BEGIN_LON'])\n",
+    "# HeatMap(data=weather_data.groupby(['BEGIN_LAT', 'BEGIN_LON']).mean().reset_index().values.tolist(), radius=8, max_zoom=4).add_to(base_map)\n",
+    "# base_map.save('tornado_heat_map.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "geological-directory",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# info = weather_data.info()\n",
+    "# state_occ = weather_data['STATE_ABBR'].value_counts()\n",
+    "# df = weather_data['STATE_ABBR'].value_counts().rename_axis('states').reset_index(name='counts')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "developmental-lambda",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# url = (\n",
+    "#     \"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data\"\n",
+    "# )\n",
+    "# state_geo = f\"{url}/us-states.json\"\n",
+    "\n",
+    "# m = folium.Map(location=location, zoom_start=3)\n",
+    "\n",
+    "# folium.Choropleth(\n",
+    "#     geo_data=state_geo,\n",
+    "#     name=\"choropleth\",\n",
+    "#     data=df,\n",
+    "#     columns=[\"states\", \"counts\"],\n",
+    "#     key_on=\"feature.id\",\n",
+    "#     fill_color=\"YlGn\",\n",
+    "#     fill_opacity=0.7,\n",
+    "#     line_opacity=0.2,\n",
+    "#     legend_name=\"Tornado Occurrances\",\n",
+    "# ).add_to(m)\n",
+    "\n",
+    "# folium.LayerControl().add_to(m)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "crude-softball",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# heat_data = [[row['BEGIN_LAT'],row['BEGIN_LON']] for index, row in heat_df.iterrows()]\n",
+    "# HeatMap(heat_data).add_to(base_map)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "animal-overall",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# base_map.save('heatmap_weather.html')\n",
+    "# base_map.save('choropleth_weather.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "unique-panel",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weather_data['BEGIN_DATE'] = pd.to_datetime(weather_data['BEGIN_DATE'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "purple-permit",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "from datetime import timedelta\n",
+    "import json\n",
+    "'''\n",
+    "Formatting:\n",
+    "'start': '2010-01-01',\n",
+    "'end': '2018-12-31',\n",
+    "'''\n",
+    "c = 0\n",
+    "frames = []\n",
+    "for index, row in weather_data.iterrows():\n",
+    "    c+=1\n",
+    "    if c>50:\n",
+    "        break\n",
+    "    end_date = row.BEGIN_DATE\n",
+    "    begin_date = end_date - timedelta(weeks=8)\n",
+    "    lat = row.BEGIN_LAT\n",
+    "    lon = row.BEGIN_LON\n",
+    "    r = requests.get('https://api.oikolab.com/weather',\n",
+    "                     params={'param': ['temperature', 'wind_speed', 'surface_solar_radiation', 'relative_humidity', 'surface_pressure', 'total_precipitation'],\n",
+    "                             'start': begin_date,\n",
+    "                             'end': end_date,\n",
+    "                             'freq': 'D',\n",
+    "                             'lat': lat,\n",
+    "                             'lon': lon,\n",
+    "                             'api-key': 'b03998e660494c2e8165d41369c13248'}\n",
+    "                     )\n",
+    "    w_data = json.loads(r.json()['data'])\n",
+    "    history_df = pd.DataFrame(index=pd.to_datetime(w_data['index'], \n",
+    "                                       unit='s'),\n",
+    "                  data=w_data['data'],\n",
+    "                  columns=w_data['columns'])\n",
+    "    history_df['latitude'] = lat\n",
+    "    history_df['longitude'] = lon\n",
+    "    frames.append(history_df)\n",
+    "result = pd.concat(frames)\n",
+    "result.index.name = 'datetime'\n",
+    "result.to_csv(\"historical_data.csv\", encoding='utf-8', index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "liquid-contrast",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "from datetime import timedelta\n",
+    "import json\n",
+    "from itertools import islice\n",
+    "\n",
+    "'''\n",
+    "Formatting:\n",
+    "'start': '2010-01-01',\n",
+    "'end': '2018-12-31',\n",
+    "'''\n",
+    "c = 0\n",
+    "frames = []\n",
+    "for index, row in islice(weather_data.iterrows(),51,None):\n",
+    "    end_date = row.BEGIN_DATE\n",
+    "    begin_date = end_date - timedelta(weeks=8)\n",
+    "    lat = row.BEGIN_LAT\n",
+    "    lon = row.BEGIN_LON\n",
+    "    r = requests.get('https://api.oikolab.com/weather',\n",
+    "                     params={'param': ['temperature', 'wind_speed', 'surface_solar_radiation', 'relative_humidity', 'surface_pressure', 'total_precipitation'],\n",
+    "                             'start': begin_date,\n",
+    "                             'end': end_date,\n",
+    "                             'freq': 'D',\n",
+    "                             'lat': lat,\n",
+    "                             'lon': lon,\n",
+    "                             'api-key': 'b03998e660494c2e8165d41369c13248'}\n",
+    "                     )\n",
+    "    w_data = json.loads(r.json()['data'])\n",
+    "    history_df = pd.DataFrame(index=pd.to_datetime(w_data['index'], \n",
+    "                                       unit='s'),\n",
+    "                  data=w_data['data'],\n",
+    "                  columns=w_data['columns'])\n",
+    "    history_df['latitude'] = lat\n",
+    "    history_df['longitude'] = lon\n",
+    "    frames.append(history_df)\n",
+    "result2 = pd.concat(frames)\n",
+    "result2.index.name = 'datetime'\n",
+    "result2.to_csv(\"historical_data2.csv\", encoding='utf-8')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "composed-fifteen",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result_fin = pd.concat([result,result2])\n",
+    "result_fin.to_csv(\"historical_data_fin.csv\", encoding='utf-8')\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From 4fcdd2a9b1e5538a718484e2713c63ed90198c9e Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Sun, 28 Feb 2021 12:59:54 -0500
Subject: [PATCH 14/38] Created README for Deliverable 1

Created Markdown version of Project proposal for easier future editing.
---
 .../Deliverable_1/Project_Proposal_CS506.md     | 17 +++++++++++++++++
 NaturalDisasterProject/Deliverable_1/README.md  | 14 ++++++++++++++
 2 files changed, 31 insertions(+)
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 create mode 100644 NaturalDisasterProject/Deliverable_1/README.md

diff --git a/NaturalDisasterProject/Deliverable_1/Project_Proposal_CS506.md b/NaturalDisasterProject/Deliverable_1/Project_Proposal_CS506.md
new file mode 100644
index 00000000..5efa509d
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/Project_Proposal_CS506.md
@@ -0,0 +1,17 @@
+# Project Proposal CS506
+
+## Correlating Natural disasters to Climate change and other environmental factors
+
+
+| Syntax      | Description |
+| ----------- | ----------- |
+| Contact      | Name: Simon Angel, Abdullaah Robins, Andrew Eramo, Alvaro Carrascosa|
+| Email | varo@bu.edu, arobins@bu.edu, aeramo@bu.edu, simonang@bu.edu |
+|Cell Phone| (786) 863-0176, (470) 269-5940, (954) 707-0907, (305) 393-9302 |
+| Organization   |         |
+| Project Type   |  Data Science  |
+| Project Description  |  This project invloves collecting data about the prevalence of occurrences of certain natural disasters, specifically tornadoes and earthquakes, with the purpose of identifying climate and weather trends leading up to the occurrence. <br><br> The environmental patterns we would like to investigate are surface weather, rainfall, and general weather data to determine patterns and correlation between the various natural disasters. <br><br> Today we can find historical weather data and data on the significant natural disasters, but there isn’t much indication to the general public when these natural disasters will happen. <br><br> Our goal is to bring knowledge of trends and visualized quantification of aspects within the environment that lead up to the occurrence and to help predict when these disasters will happen. |
+| DataSets |  Climate Change: Earth Surface Temperature Data <br>https://www.kaggle.com/berkeleyearth/climate-change-earth-surface-temperature-data <br><br> Significant Earthquakes <br> https://www.kaggle.com/usgs/earthquake-database <br><br> Fires <br> https://www.kaggle.com/rtatman/188-million-us-wildfires<br><br> Glaciers <br> http://www.glims.org/download/ <br><br> Floods <br> https://www.eea.europa.eu/data-and-maps/data/european-past-floods/flood-phenomena/flood-phenomena-csv-files <br><br> Storm Events Database <br> https://www.ncdc.noaa.gov/stormevents/choosedates.jsp?statefips=-999%2CALL <br><br> Weather API <br> https://oikolab.com/api-details#api=weather&operation=weather-data         |
+| Suggested Steps | <ul><li>Clean temperature data put into Pandas dataframes.<ul><li>This could be the “n” most volatile days or the days on which the temperature changes, for example a 3% change.</li></ul></li><li>Clean the data from the non temperature data from various datasets into respective data frames.</li><li>We will make time series analytics for each distinct type of phenomenon.</li><li>Each form of data will be correlated with temperature change over time.<ul><li>We understand different phenomena can have a different relationship with temperature change, therefore they must be analyzed separately.</li></ul></li><li>Analyze the phenomena (disasters or disastrous trends) to see if there is acorrelation between them and the rise of temperatures.</li></ul>                           |
+| Questions to be Answered in Analysis       | <ul><li>When have each of these phenomena peaked in happening?</li><li>What are some consistent weather patterns leading up to the phenomena?</li><li>What weather data is unique to the phenomena?</li><li>When have the highest continuous periods of increase been?<ul><li>Are these periods related?<ul><li>Could this prove correlation?</li></ul></li></ul></li><li>Are there outlier years or periods?</li><li>Where do Tornados occur more often geographically?</li></ul>|
+|               |              |
\ No newline at end of file
diff --git a/NaturalDisasterProject/Deliverable_1/README.md b/NaturalDisasterProject/Deliverable_1/README.md
new file mode 100644
index 00000000..8f577d33
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_1/README.md
@@ -0,0 +1,14 @@
+# CS 506 - Final Project Repository
+
+## Project Deliverable 1
+
+- [x] Collect and pre-process a preliminary batch of data
+  - Tornado data collected from NOAA Storm Events Database
+  - Tornado data cleaned
+- [x] Perform a preliminary analysis of the data
+  - created heat-map & clhoropleth-map from tornado data for preliminary analysis
+- [x] Answer one key question
+  - Where are Stage 4 & higher tornados likely to appear? Answered through the visual maps. [heatmap](heatmap_weather.html), [clhoropleth-map](choropleth_weather.html)
+- [x] Refine project scope and list of limitations with data and potential risks of achieving project goal
+- [x] Submit a PR with the above report and modifications to original proposal
+  - [Proposal](Project_Proposal_CS506.md)
\ No newline at end of file

From 079dba1327bf405e7b4706be24659c9bf4a67910 Mon Sep 17 00:00:00 2001
From: varocarras <varocarras@gmail.com>
Date: Tue, 2 Mar 2021 01:55:49 -0500
Subject: [PATCH 15/38] Created .gitignore

Made a .gitignore file to include DS_Store
---
 .gitignore | 3 +++
 1 file changed, 3 insertions(+)
 create mode 100644 .gitignore

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 00000000..3e9537da
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,3 @@
+
+NaturalDisasterProject/Datasets/.DS_Store
+.DS_Store

From 1f72142d07c5e1e8ce39e859543f3a5757ebda70 Mon Sep 17 00:00:00 2001
From: varocarras <varocarras@gmail.com>
Date: Tue, 2 Mar 2021 02:03:21 -0500
Subject: [PATCH 16/38] Update DS_Store

Ignore
---
 NaturalDisasterProject/Datasets/.DS_Store | Bin 6148 -> 6148 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/NaturalDisasterProject/Datasets/.DS_Store b/NaturalDisasterProject/Datasets/.DS_Store
index 2093e67e156f942568b2e4c651b92cf3a296d649..4f8c3e55f7e130c4a93bbd35b3ded3c8827111b7 100644
GIT binary patch
delta 257
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delta 121
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From da1b01724630a1e7e8d697aed673f395621e1b88 Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Tue, 2 Mar 2021 18:39:19 -0500
Subject: [PATCH 17/38] Create .gitignore

---
 .gitignore | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 .gitignore

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 00000000..e43b0f98
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+.DS_Store

From e800d9322d177c7d72553e09b970dccdaa6a46e1 Mon Sep 17 00:00:00 2001
From: varocarras <34591902+varocarras@users.noreply.github.com>
Date: Tue, 2 Mar 2021 18:51:41 -0500
Subject: [PATCH 18/38] Remove unnecessary files

Removing historical_data
Removing historical_data2
Removing weather_data
---
 .../Deliverable_1/historical_data.csv         | 2851 --------------
 .../Deliverable_1/historical_data2.csv        | 3421 -----------------
 .../Deliverable_1/weather_data.py             |    0
 3 files changed, 6272 deletions(-)
 delete mode 100644 NaturalDisasterProject/Deliverable_1/historical_data.csv
 delete mode 100644 NaturalDisasterProject/Deliverable_1/historical_data2.csv
 delete mode 100644 NaturalDisasterProject/Deliverable_1/weather_data.py

diff --git a/NaturalDisasterProject/Deliverable_1/historical_data.csv b/NaturalDisasterProject/Deliverable_1/historical_data.csv
deleted file mode 100644
index e287a872..00000000
--- a/NaturalDisasterProject/Deliverable_1/historical_data.csv
+++ /dev/null
@@ -1,2851 +0,0 @@
-datetime,temperature (degC),wind_speed (m/s),surface_solar_radiation (W/m^2),relative_humidity (0-1),surface_pressure (Pa),total_precipitation (mm of water equivalent),latitude,longitude
-2010-02-27,8.5,1.51,233,0.5,101170,0.0,32.7003,-90.6783
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-2011-04-20,18.18,1.67,172,0.78,98922,0.29,34.9868,-85.0485
-2011-04-21,18.79,2.32,194,0.72,98723,0.07,34.9868,-85.0485
-2011-04-22,18.87,4.08,277,0.75,98713,0.0,34.9868,-85.0485
-2011-04-23,21.32,3.1,298,0.67,98747,0.0,34.9868,-85.0485
-2011-04-24,21.37,3.4,263,0.69,98407,0.04,34.9868,-85.0485
-2011-04-25,21.98,4.42,216,0.73,97910,0.03,34.9868,-85.0485
-2011-04-26,22.58,5.68,205,0.68,97521,0.29,34.9868,-85.0485
-2011-04-27,20.5,5.71,11,0.94,97210,3.14,34.9868,-85.0485
diff --git a/NaturalDisasterProject/Deliverable_1/historical_data2.csv b/NaturalDisasterProject/Deliverable_1/historical_data2.csv
deleted file mode 100644
index 37004de0..00000000
--- a/NaturalDisasterProject/Deliverable_1/historical_data2.csv
+++ /dev/null
@@ -1,3421 +0,0 @@
-datetime,temperature (degC),wind_speed (m/s),surface_solar_radiation (W/m^2),relative_humidity (0-1),surface_pressure (Pa),total_precipitation (mm of water equivalent),latitude,longitude
-2011-03-02,15.46,3.17,233,0.53,100151,0.0,32.7545,-85.8826
-2011-03-03,14.66,5.03,150,0.62,100264,0.0,32.7545,-85.8826
-2011-03-04,13.8,4.3,54,0.87,99872,0.67,32.7545,-85.8826
-2011-03-05,9.99,2.03,174,0.84,99289,1.73,32.7545,-85.8826
-2011-03-06,6.34,1.78,180,0.68,99772,0.0,32.7545,-85.8826
-2011-03-07,11.41,4.08,195,0.66,99915,0.0,32.7545,-85.8826
-2011-03-08,14.68,3.57,40,0.84,99461,1.62,32.7545,-85.8826
-2011-03-09,9.86,3.81,135,0.76,99530,0.07,32.7545,-85.8826
-2011-03-10,8.11,3.37,258,0.53,100055,0.0,32.7545,-85.8826
-2011-03-11,11.07,2.34,254,0.56,100091,0.0,32.7545,-85.8826
-2011-03-12,14.63,2.4,241,0.65,100101,0.0,32.7545,-85.8826
-2011-03-13,16.06,1.99,213,0.64,99957,0.0,32.7545,-85.8826
-2011-03-14,14.71,2.13,87,0.81,99796,0.57,32.7545,-85.8826
-2011-03-15,11.59,2.03,258,0.68,100136,0.0,32.7545,-85.8826
-2011-03-16,13.43,0.64,260,0.64,100327,0.0,32.7545,-85.8826
-2011-03-17,17.93,1.7,258,0.61,100200,0.0,32.7545,-85.8826
-2011-03-18,20.37,1.56,246,0.63,100080,0.0,32.7545,-85.8826
-2011-03-19,19.97,1.32,239,0.69,100242,0.0,32.7545,-85.8826
-2011-03-20,19.31,1.69,266,0.64,100382,0.0,32.7545,-85.8826
-2011-03-21,19.98,2.53,256,0.63,99844,0.0,32.7545,-85.8826
-2011-03-22,21.15,4.62,185,0.64,99137,0.01,32.7545,-85.8826
-2011-03-23,19.45,3.68,278,0.48,98942,0.0,32.7545,-85.8826
-2011-03-24,12.54,1.28,278,0.52,99365,0.0,32.7545,-85.8826
-2011-03-25,17.08,2.68,178,0.72,98886,0.31,32.7545,-85.8826
-2011-03-26,17.87,1.81,102,0.88,98748,0.12,32.7545,-85.8826
-2011-03-27,14.04,2.04,111,0.87,99159,0.39,32.7545,-85.8826
-2011-03-28,11.43,2.65,95,0.83,99649,0.0,32.7545,-85.8826
-2011-03-29,14.54,1.02,69,0.9,99082,0.4,32.7545,-85.8826
-2011-03-30,11.71,3.28,242,0.75,98653,0.06,32.7545,-85.8826
-2011-03-31,11.57,1.85,204,0.66,98770,0.01,32.7545,-85.8826
-2011-04-01,15.52,2.59,276,0.52,99344,0.0,32.7545,-85.8826
-2011-04-02,16.84,1.27,290,0.52,99645,0.0,32.7545,-85.8826
-2011-04-03,21.17,4.72,243,0.61,99090,0.0,32.7545,-85.8826
-2011-04-04,13.65,3.73,303,0.56,99077,1.17,32.7545,-85.8826
-2011-04-05,13.09,0.87,301,0.49,99856,0.0,32.7545,-85.8826
-2011-04-06,16.28,2.08,270,0.6,99682,0.0,32.7545,-85.8826
-2011-04-07,21.9,2.62,129,0.77,99500,0.04,32.7545,-85.8826
-2011-04-08,23.75,2.55,243,0.74,99679,0.0,32.7545,-85.8826
-2011-04-09,22.85,2.46,266,0.7,99672,0.0,32.7545,-85.8826
-2011-04-10,23.32,3.53,221,0.68,99370,0.0,32.7545,-85.8826
-2011-04-11,19.13,3.69,288,0.64,99128,0.39,32.7545,-85.8826
-2011-04-12,16.76,1.95,312,0.55,99487,0.0,32.7545,-85.8826
-2011-04-13,18.29,0.55,276,0.59,99414,0.0,32.7545,-85.8826
-2011-04-14,19.11,3.65,184,0.66,99126,0.1,32.7545,-85.8826
-2011-04-15,18.11,4.45,312,0.58,98829,0.63,32.7545,-85.8826
-2011-04-16,14.0,1.58,319,0.53,99548,0.0,32.7545,-85.8826
-2011-04-17,17.11,1.93,307,0.56,99481,0.0,32.7545,-85.8826
-2011-04-18,21.24,2.79,306,0.58,99469,0.0,32.7545,-85.8826
-2011-04-19,22.35,2.91,206,0.72,99657,0.01,32.7545,-85.8826
-2011-04-20,21.58,0.26,182,0.74,99828,0.08,32.7545,-85.8826
-2011-04-21,22.09,1.18,307,0.67,99672,0.0,32.7545,-85.8826
-2011-04-22,21.87,2.32,288,0.64,99724,0.0,32.7545,-85.8826
-2011-04-23,22.76,2.28,301,0.62,99793,0.0,32.7545,-85.8826
-2011-04-24,23.25,2.55,246,0.68,99427,0.04,32.7545,-85.8826
-2011-04-25,23.01,3.97,220,0.69,98972,0.03,32.7545,-85.8826
-2011-04-26,24.37,5.09,211,0.69,98621,0.01,32.7545,-85.8826
-2011-04-27,26.49,5.39,49,0.71,98426,0.98,32.7545,-85.8826
-2011-03-02,11.22,1.6,208,0.47,97485,0.0,35.5535,-85.1077
-2011-03-03,11.9,4.64,156,0.48,97525,0.0,35.5535,-85.1077
-2011-03-04,11.05,5.02,37,0.83,97024,0.67,35.5535,-85.1077
-2011-03-05,4.61,3.46,109,0.89,96591,2.04,35.5535,-85.1077
-2011-03-06,4.41,2.13,188,0.65,96980,0.0,35.5535,-85.1077
-2011-03-07,8.1,2.91,159,0.54,97180,0.07,35.5535,-85.1077
-2011-03-08,9.74,5.19,41,0.88,96630,1.95,35.5535,-85.1077
-2011-03-09,7.29,3.35,128,0.88,96441,0.51,35.5535,-85.1077
-2011-03-10,4.12,3.32,232,0.62,96980,0.01,35.5535,-85.1077
-2011-03-11,9.46,2.98,243,0.47,96989,0.0,35.5535,-85.1077
-2011-03-12,13.49,1.87,145,0.59,97114,0.0,35.5535,-85.1077
-2011-03-13,11.37,1.0,107,0.73,97124,0.07,35.5535,-85.1077
-2011-03-14,10.6,2.67,88,0.83,96842,0.63,35.5535,-85.1077
-2011-03-15,8.18,1.63,189,0.73,97266,0.01,35.5535,-85.1077
-2011-03-16,12.42,1.54,250,0.56,97436,0.0,35.5535,-85.1077
-2011-03-17,17.73,2.73,238,0.56,97220,0.0,35.5535,-85.1077
-2011-03-18,17.06,1.57,145,0.62,97339,0.0,35.5535,-85.1077
-2011-03-19,16.26,1.65,198,0.49,97590,0.0,35.5535,-85.1077
-2011-03-20,18.16,3.52,199,0.63,97460,0.0,35.5535,-85.1077
-2011-03-21,18.96,2.87,242,0.54,96831,0.0,35.5535,-85.1077
-2011-03-22,18.45,4.29,100,0.67,95998,0.3,35.5535,-85.1077
-2011-03-23,10.72,3.87,144,0.62,96084,0.36,35.5535,-85.1077
-2011-03-24,5.95,1.21,215,0.66,96628,0.06,35.5535,-85.1077
-2011-03-25,8.66,1.55,61,0.86,96202,0.42,35.5535,-85.1077
-2011-03-26,6.9,2.23,151,0.84,96088,0.52,35.5535,-85.1077
-2011-03-27,6.57,1.99,126,0.79,96543,0.4,35.5535,-85.1077
-2011-03-28,8.81,0.89,242,0.7,96878,0.0,35.5535,-85.1077
-2011-03-29,10.63,0.94,43,0.88,96292,1.02,35.5535,-85.1077
-2011-03-30,5.04,2.5,117,0.76,95899,0.03,35.5535,-85.1077
-2011-03-31,6.43,1.92,191,0.65,95811,0.03,35.5535,-85.1077
-2011-04-01,10.71,3.55,280,0.49,96304,0.0,35.5535,-85.1077
-2011-04-02,13.91,2.03,286,0.4,96728,0.0,35.5535,-85.1077
-2011-04-03,19.04,5.2,183,0.57,95985,0.12,35.5535,-85.1077
-2011-04-04,9.09,4.16,288,0.59,96017,1.01,35.5535,-85.1077
-2011-04-05,10.32,2.63,293,0.43,96857,0.0,35.5535,-85.1077
-2011-04-06,15.1,2.65,280,0.52,96734,0.0,35.5535,-85.1077
-2011-04-07,19.2,2.86,142,0.72,96578,0.09,35.5535,-85.1077
-2011-04-08,23.1,2.24,234,0.65,96722,0.05,35.5535,-85.1077
-2011-04-09,22.73,2.67,284,0.6,96745,0.0,35.5535,-85.1077
-2011-04-10,21.4,4.22,262,0.68,96350,0.0,35.5535,-85.1077
-2011-04-11,14.62,4.14,121,0.73,95965,0.71,35.5535,-85.1077
-2011-04-12,13.33,1.67,300,0.52,96714,0.0,35.5535,-85.1077
-2011-04-13,14.96,0.85,295,0.49,96720,0.0,35.5535,-85.1077
-2011-04-14,15.82,3.17,125,0.68,96393,0.42,35.5535,-85.1077
-2011-04-15,12.71,4.3,142,0.74,95701,0.99,35.5535,-85.1077
-2011-04-16,10.84,1.66,311,0.56,96651,0.0,35.5535,-85.1077
-2011-04-17,15.88,3.31,254,0.51,96580,0.0,35.5535,-85.1077
-2011-04-18,20.88,4.19,292,0.58,96499,0.0,35.5535,-85.1077
-2011-04-19,19.48,3.53,103,0.76,96656,0.35,35.5535,-85.1077
-2011-04-20,16.18,1.97,188,0.7,97191,0.08,35.5535,-85.1077
-2011-04-21,16.89,2.29,182,0.75,96912,0.23,35.5535,-85.1077
-2011-04-22,18.13,4.11,269,0.77,96856,0.01,35.5535,-85.1077
-2011-04-23,20.51,3.17,275,0.69,96935,0.01,35.5535,-85.1077
-2011-04-24,20.62,3.5,264,0.68,96613,0.05,35.5535,-85.1077
-2011-04-25,20.55,4.52,194,0.76,96102,0.04,35.5535,-85.1077
-2011-04-26,20.64,5.3,198,0.74,95709,0.63,35.5535,-85.1077
-2011-04-27,19.26,6.31,12,0.97,95361,4.59,35.5535,-85.1077
-2011-03-27,4.61,2.46,232,0.72,98247,0.02,37.056,-94.5701
-2011-03-28,9.11,1.95,103,0.69,98191,0.05,37.056,-94.5701
-2011-03-29,4.29,2.58,108,0.83,98381,0.08,37.056,-94.5701
-2011-03-30,4.49,0.97,130,0.8,97673,0.16,37.056,-94.5701
-2011-03-31,9.0,0.96,209,0.73,97430,0.01,37.056,-94.5701
-2011-04-01,13.82,1.76,270,0.51,97974,0.0,37.056,-94.5701
-2011-04-02,22.21,6.6,263,0.53,96946,0.0,37.056,-94.5701
-2011-04-03,13.79,3.56,168,0.57,97091,0.34,37.056,-94.5701
-2011-04-04,9.11,3.28,290,0.37,98075,0.0,37.056,-94.5701
-2011-04-05,16.72,5.59,285,0.33,97349,0.0,37.056,-94.5701
-2011-04-06,16.93,2.65,156,0.65,97397,0.02,37.056,-94.5701
-2011-04-07,20.16,3.7,256,0.77,97295,0.0,37.056,-94.5701
-2011-04-08,24.02,4.04,276,0.65,97442,0.22,37.056,-94.5701
-2011-04-09,25.09,6.5,192,0.55,97117,0.01,37.056,-94.5701
-2011-04-10,18.12,2.67,255,0.56,97522,0.09,37.056,-94.5701
-2011-04-11,14.19,1.1,302,0.45,98352,0.0,37.056,-94.5701
-2011-04-12,17.41,2.57,298,0.51,98063,0.0,37.056,-94.5701
-2011-04-13,19.82,4.63,269,0.48,97479,0.0,37.056,-94.5701
-2011-04-14,11.67,3.7,77,0.79,96511,1.77,37.056,-94.5701
-2011-04-15,8.21,5.63,299,0.59,97566,0.01,37.056,-94.5701
-2011-04-16,14.74,4.65,287,0.43,97690,0.0,37.056,-94.5701
-2011-04-17,18.77,4.11,173,0.55,97050,0.03,37.056,-94.5701
-2011-04-18,21.11,4.1,227,0.77,96640,0.02,37.056,-94.5701
-2011-04-19,10.22,3.3,249,0.67,98255,0.0,37.056,-94.5701
-2011-04-20,12.01,3.57,70,0.68,98470,0.4,37.056,-94.5701
-2011-04-21,18.52,5.28,155,0.87,97244,0.45,37.056,-94.5701
-2011-04-22,16.55,1.48,64,0.84,97570,1.77,37.056,-94.5701
-2011-04-23,11.93,2.72,56,0.88,97882,1.59,37.056,-94.5701
-2011-04-24,14.2,2.25,64,0.94,97173,0.69,37.056,-94.5701
-2011-04-25,12.97,2.41,234,0.81,96622,0.42,37.056,-94.5701
-2011-04-26,11.69,3.7,127,0.79,96666,0.2,37.056,-94.5701
-2011-04-27,12.64,3.68,310,0.55,98011,0.0,37.056,-94.5701
-2011-04-28,16.68,3.96,324,0.51,97890,0.0,37.056,-94.5701
-2011-04-29,20.02,5.16,230,0.52,97018,0.0,37.056,-94.5701
-2011-04-30,11.72,3.7,88,0.58,98084,0.35,37.056,-94.5701
-2011-05-01,7.41,2.56,108,0.77,98696,0.04,37.056,-94.5701
-2011-05-02,10.22,1.55,305,0.63,99075,0.01,37.056,-94.5701
-2011-05-03,14.05,2.45,329,0.59,99078,0.0,37.056,-94.5701
-2011-05-04,15.42,2.95,230,0.63,98694,0.15,37.056,-94.5701
-2011-05-05,13.94,1.23,317,0.68,98173,0.0,37.056,-94.5701
-2011-05-06,20.72,2.94,308,0.6,97383,0.04,37.056,-94.5701
-2011-05-07,23.21,3.3,299,0.71,97342,0.0,37.056,-94.5701
-2011-05-08,25.63,5.56,317,0.69,97010,0.0,37.056,-94.5701
-2011-05-09,26.07,5.65,274,0.64,97094,0.0,37.056,-94.5701
-2011-05-10,24.85,4.37,258,0.7,97413,0.04,37.056,-94.5701
-2011-05-11,19.87,3.92,190,0.84,97558,0.21,37.056,-94.5701
-2011-05-12,15.49,2.9,145,0.82,97521,0.19,37.056,-94.5701
-2011-05-13,11.2,4.9,167,0.64,98051,0.0,37.056,-94.5701
-2011-05-14,11.42,4.12,187,0.59,98079,0.0,37.056,-94.5701
-2011-05-15,12.82,2.93,339,0.57,98199,0.0,37.056,-94.5701
-2011-05-16,13.65,1.86,349,0.52,97948,0.0,37.056,-94.5701
-2011-05-17,13.85,3.76,187,0.68,97446,0.21,37.056,-94.5701
-2011-05-18,19.93,3.91,185,0.71,97357,0.14,37.056,-94.5701
-2011-05-19,20.66,4.18,87,0.8,97512,0.95,37.056,-94.5701
-2011-05-20,21.02,4.49,291,0.8,97400,0.61,37.056,-94.5701
-2011-05-21,24.26,5.54,161,0.78,97220,0.09,37.056,-94.5701
-2011-05-22,25.63,0.66,200,0.74,97045,0.11,37.056,-94.5701
-2011-03-29,5.49,2.81,183,0.72,96563,0.0,35.444,-98.287
-2011-03-30,9.39,1.53,266,0.56,95759,0.01,35.444,-98.287
-2011-03-31,15.86,1.24,279,0.34,95575,0.0,35.444,-98.287
-2011-04-01,18.2,2.88,281,0.38,96092,0.0,35.444,-98.287
-2011-04-02,25.95,8.76,263,0.48,95048,0.0,35.444,-98.287
-2011-04-03,15.95,5.88,242,0.28,95631,0.0,35.444,-98.287
-2011-04-04,11.55,3.88,298,0.19,96369,0.0,35.444,-98.287
-2011-04-05,21.04,5.73,296,0.18,95372,0.0,35.444,-98.287
-2011-04-06,20.39,0.89,259,0.33,95319,0.0,35.444,-98.287
-2011-04-07,23.48,4.91,252,0.51,95287,0.03,35.444,-98.287
-2011-04-08,26.57,6.99,281,0.51,95354,0.0,35.444,-98.287
-2011-04-09,25.67,6.3,266,0.35,95266,0.0,35.444,-98.287
-2011-04-10,18.55,5.57,281,0.24,96060,0.0,35.444,-98.287
-2011-04-11,16.77,1.17,308,0.23,96596,0.0,35.444,-98.287
-2011-04-12,20.52,5.69,304,0.27,95990,0.0,35.444,-98.287
-2011-04-13,22.19,5.51,298,0.29,95266,0.0,35.444,-98.287
-2011-04-14,13.27,10.36,202,0.34,95322,0.0,35.444,-98.287
-2011-04-15,13.03,4.25,316,0.19,96267,0.0,35.444,-98.287
-2011-04-16,18.28,6.66,289,0.23,95718,0.0,35.444,-98.287
-2011-04-17,24.63,4.87,304,0.36,94844,0.0,35.444,-98.287
-2011-04-18,23.37,2.63,304,0.3,94877,0.0,35.444,-98.287
-2011-04-19,13.65,5.62,253,0.5,96250,0.0,35.444,-98.287
-2011-04-20,14.38,3.29,57,0.63,96286,0.27,35.444,-98.287
-2011-04-21,23.03,3.89,295,0.56,95290,0.01,35.444,-98.287
-2011-04-22,18.65,5.27,106,0.5,95575,0.01,35.444,-98.287
-2011-04-23,12.76,3.67,56,0.65,95950,1.62,35.444,-98.287
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-2011-04-25,12.13,1.32,258,0.71,94985,0.02,35.444,-98.287
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diff --git a/NaturalDisasterProject/Deliverable_1/weather_data.py b/NaturalDisasterProject/Deliverable_1/weather_data.py
deleted file mode 100644
index e69de29b..00000000

From 2d9ab0d963afc4b937e658365a5ead86875256d1 Mon Sep 17 00:00:00 2001
From: Frazier Horn <37252035+fhorn97@users.noreply.github.com>
Date: Tue, 2 Mar 2021 19:05:27 -0500
Subject: [PATCH 19/38] Update Project_Proposal_CS506.md

---
 .../Deliverable_1/Project_Proposal_CS506.md               | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/NaturalDisasterProject/Deliverable_1/Project_Proposal_CS506.md b/NaturalDisasterProject/Deliverable_1/Project_Proposal_CS506.md
index 5efa509d..ffe58f7d 100644
--- a/NaturalDisasterProject/Deliverable_1/Project_Proposal_CS506.md
+++ b/NaturalDisasterProject/Deliverable_1/Project_Proposal_CS506.md
@@ -5,13 +5,13 @@
 
 | Syntax      | Description |
 | ----------- | ----------- |
-| Contact      | Name: Simon Angel, Abdullaah Robins, Andrew Eramo, Alvaro Carrascosa|
-| Email | varo@bu.edu, arobins@bu.edu, aeramo@bu.edu, simonang@bu.edu |
-|Cell Phone| (786) 863-0176, (470) 269-5940, (954) 707-0907, (305) 393-9302 |
+| Contact      | Name: Simon Angel, Abdullaah Robins, Frazier Horn, Alvaro Carrascosa|
+| Email | varo@bu.edu, arobins@bu.edu, fhorn@bu.edu, simonang@bu.edu |
+|Cell Phone| (786) 863-0176, (470) 269-5940, (617) 840-4970, (305) 393-9302 |
 | Organization   |         |
 | Project Type   |  Data Science  |
 | Project Description  |  This project invloves collecting data about the prevalence of occurrences of certain natural disasters, specifically tornadoes and earthquakes, with the purpose of identifying climate and weather trends leading up to the occurrence. <br><br> The environmental patterns we would like to investigate are surface weather, rainfall, and general weather data to determine patterns and correlation between the various natural disasters. <br><br> Today we can find historical weather data and data on the significant natural disasters, but there isn’t much indication to the general public when these natural disasters will happen. <br><br> Our goal is to bring knowledge of trends and visualized quantification of aspects within the environment that lead up to the occurrence and to help predict when these disasters will happen. |
 | DataSets |  Climate Change: Earth Surface Temperature Data <br>https://www.kaggle.com/berkeleyearth/climate-change-earth-surface-temperature-data <br><br> Significant Earthquakes <br> https://www.kaggle.com/usgs/earthquake-database <br><br> Fires <br> https://www.kaggle.com/rtatman/188-million-us-wildfires<br><br> Glaciers <br> http://www.glims.org/download/ <br><br> Floods <br> https://www.eea.europa.eu/data-and-maps/data/european-past-floods/flood-phenomena/flood-phenomena-csv-files <br><br> Storm Events Database <br> https://www.ncdc.noaa.gov/stormevents/choosedates.jsp?statefips=-999%2CALL <br><br> Weather API <br> https://oikolab.com/api-details#api=weather&operation=weather-data         |
 | Suggested Steps | <ul><li>Clean temperature data put into Pandas dataframes.<ul><li>This could be the “n” most volatile days or the days on which the temperature changes, for example a 3% change.</li></ul></li><li>Clean the data from the non temperature data from various datasets into respective data frames.</li><li>We will make time series analytics for each distinct type of phenomenon.</li><li>Each form of data will be correlated with temperature change over time.<ul><li>We understand different phenomena can have a different relationship with temperature change, therefore they must be analyzed separately.</li></ul></li><li>Analyze the phenomena (disasters or disastrous trends) to see if there is acorrelation between them and the rise of temperatures.</li></ul>                           |
 | Questions to be Answered in Analysis       | <ul><li>When have each of these phenomena peaked in happening?</li><li>What are some consistent weather patterns leading up to the phenomena?</li><li>What weather data is unique to the phenomena?</li><li>When have the highest continuous periods of increase been?<ul><li>Are these periods related?<ul><li>Could this prove correlation?</li></ul></li></ul></li><li>Are there outlier years or periods?</li><li>Where do Tornados occur more often geographically?</li></ul>|
-|               |              |
\ No newline at end of file
+|               |              |

From fed0a699a2d93787c0bf4301995025d4cc92645b Mon Sep 17 00:00:00 2001
From: varocarras <34591902+varocarras@users.noreply.github.com>
Date: Tue, 2 Mar 2021 19:28:14 -0500
Subject: [PATCH 20/38] Delete testFile

---
 NaturalDisasterProject/Datasets/testFile | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 NaturalDisasterProject/Datasets/testFile

diff --git a/NaturalDisasterProject/Datasets/testFile b/NaturalDisasterProject/Datasets/testFile
deleted file mode 100644
index efb7a7cd..00000000
--- a/NaturalDisasterProject/Datasets/testFile
+++ /dev/null
@@ -1 +0,0 @@
-this is a test. 
\ No newline at end of file

From 6e1fdd0445c46f1745e939b1409eef60e511db98 Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Tue, 2 Mar 2021 19:28:45 -0500
Subject: [PATCH 21/38] Deliverable 1

---
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 .gitignore                                    |   1 -
 .../Deliverable_1/{README.md => D1_README.md} |   0
 NaturalDisasterProject/README.md              |  66 ------------------
 4 files changed, 67 deletions(-)
 delete mode 100644 .gitignore
 rename NaturalDisasterProject/Deliverable_1/{README.md => D1_README.md} (100%)
 delete mode 100644 NaturalDisasterProject/README.md

diff --git a/.DS_Store b/.DS_Store
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diff --git a/.gitignore b/.gitignore
deleted file mode 100644
index e43b0f98..00000000
--- a/.gitignore
+++ /dev/null
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diff --git a/NaturalDisasterProject/Deliverable_1/README.md b/NaturalDisasterProject/Deliverable_1/D1_README.md
similarity index 100%
rename from NaturalDisasterProject/Deliverable_1/README.md
rename to NaturalDisasterProject/Deliverable_1/D1_README.md
diff --git a/NaturalDisasterProject/README.md b/NaturalDisasterProject/README.md
deleted file mode 100644
index f020892e..00000000
--- a/NaturalDisasterProject/README.md
+++ /dev/null
@@ -1,66 +0,0 @@
-# CS 506 - Final Project Repository
-
-All final projects for CS506.
-
-## Deliverables
-
-See Syllabus for due dates. Project deliverables can be modified with approval of PMs, the client, or the instructor.
-
-### Project Deliverable 0
-
-Teams should have set up weekly meetings with their client for the remainder of the semester,  reviewed the project scope, and submitted a pull request with the revised and final project description. Project descriptions should include data sources that your team will collect, including any additional datasets you identify that you think would enhance the project, specific questions that will be answered and the step by step approach you will take for transforming the data (cleaning) and answering strategic questions.
-
-#### Checklist
-
-- [ ] Reviewed all previous material
-- [ ] Revised scope of the project if needed
-- [ ] Identify / list limitations with data and potential risks of achieving project goal
-- [ ] Meet with client to review the project
-- [ ] Schedule weekly meetings with PMs and bi-weekly with client
-- [ ] Submit a PR with the revised project proposal including list of limitations
-
-### Project Deliverable 1
-
-Sufficient data should have been collected to perform a preliminary analysis of the data and attempt to answer one question relevant to your project proposal which you will submit as a pull request. If data has already been collected for your project you must answer two questions.
-
-#### Checklist
-
-- [ ] Collect and pre-process a preliminary batch of data
-- [ ] Perform a preliminary analysis of the data
-- [ ] Answer one key question
-- [ ] Refine project scope and list of limitations with data and potential risks of achieving project goal
-- [ ] Submit a PR with the above report and modifications to original proposal
-
-### Project Deliverable 2
-
-More data should have been collected to perform a more thorough analysis of the data and attempt to answer one additional question relevant to your project proposal which you will submit as a pull request.
-
-#### Checklist
-
-- [ ] Collect and pre-process a secondary batch of data
-- [ ] Refine the preliminary analysis of the data performed in PD1
-- [ ] Answer another key question
-- [ ] Refine project scope and list of limitations with data and potential risks of achieving project goal
-- [ ] Submit a PR with the above report and modifications to original proposal
-
-### Project Deliverable 3 (v1 Final Report)
-
-All data should have been collected. All project questions should have been reviewed, answered, and submitted in a written document outlining findings as a PR. You will also be asked to submit the associated data and a README explaining what each label/feature in your dataset represents. Your team should meet with the client before this deliverable.
-
-#### Checklist
-
-- [ ] All data is collected
-- [ ] Refine the preliminary analysis of the data performed in PD1&2
-- [ ] Answer another key question
-- [ ] Attempt to answer overarching project question
-- [ ] Create a draft of your final report
-- [ ] Refine project scope and list of limitations with data and potential risks of achieving project goal
-- [ ] Submit a PR with the above report and modifications to original proposal
-
-### Project Deliverable 4 (v2 Final Report)
-
-This is a draft of your final report that has been reviewed by your client. It includes all visualizations, results, data, and code up to this point, along with proper documentation on how to reproduce your results, compile and use your codebase, and navigate your dataset. Your team will submit this as a PR.
-
-### Final Project Deliverable
-
-This should be an enhancement of deliverable 4.

From 40a272d601ca5f6d2f600a8bb95249038701f47c Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Tue, 2 Mar 2021 19:30:54 -0500
Subject: [PATCH 22/38] Checklist update

---
 .../Deliverable_1/{D1_README.md => Deliverable_Checklist.md}      | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 rename NaturalDisasterProject/Deliverable_1/{D1_README.md => Deliverable_Checklist.md} (100%)

diff --git a/NaturalDisasterProject/Deliverable_1/D1_README.md b/NaturalDisasterProject/Deliverable_1/Deliverable_Checklist.md
similarity index 100%
rename from NaturalDisasterProject/Deliverable_1/D1_README.md
rename to NaturalDisasterProject/Deliverable_1/Deliverable_Checklist.md

From d54fcf79dd07c24b3e656392bdef86057646ea3f Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Tue, 2 Mar 2021 19:38:35 -0500
Subject: [PATCH 23/38] Delete .DS_Store

---
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 delete mode 100644 NaturalDisasterProject/.DS_Store

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From 4cbe51f29665c3afd45633ae6628d6ab1e648a67 Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Tue, 2 Mar 2021 19:38:52 -0500
Subject: [PATCH 24/38] Delete .DS_Store

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From 5365e15a74ea652fd36945cc395eaf278b2808bc Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Tue, 2 Mar 2021 19:40:08 -0500
Subject: [PATCH 25/38] Delete .DS_Store

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From 18592847e7139cb64c4442401c4ebdeb6f186929 Mon Sep 17 00:00:00 2001
From: icyair100 <34012403+icyair100@users.noreply.github.com>
Date: Tue, 2 Mar 2021 19:43:27 -0500
Subject: [PATCH 26/38] Create README.md

---
 README.md | 67 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 67 insertions(+)
 create mode 100644 README.md

diff --git a/README.md b/README.md
new file mode 100644
index 00000000..0e19f031
--- /dev/null
+++ b/README.md
@@ -0,0 +1,67 @@
+# CS 506 - Final Project Repository
+
+All final projects for CS506.
+
+## Deliverables
+
+See Syllabus for due dates. Project deliverables can be modified with approval of PMs, the client, or the instructor.
+
+### Project Deliverable 0
+
+Teams should have set up weekly meetings with their client for the remainder of the semester,  reviewed the project scope, and submitted a pull request with the revised and final project description. Project descriptions should include data sources that your team will collect, including any additional datasets you identify that you think would enhance the project, specific questions that will be answered and the step by step approach you will take for transforming the data (cleaning) and answering strategic questions.
+
+#### Checklist
+
+- [ ] Reviewed all previous material
+- [ ] Revised scope of the project if needed
+- [ ] Identify / list limitations with data and potential risks of achieving project goal
+- [ ] Meet with client to review the project
+- [ ] Schedule weekly meetings with PMs and bi-weekly with client
+- [ ] Submit a PR with the revised project proposal including list of limitations
+
+### Project Deliverable 1
+
+Sufficient data should have been collected to perform a preliminary analysis of the data and attempt to answer one question relevant to your project proposal which you will submit as a pull request. If data has already been collected for your project you must answer two questions.
+
+#### Checklist
+
+- [ ] Collect and pre-process a preliminary batch of data
+- [ ] Perform a preliminary analysis of the data
+- [ ] Answer one key question
+- [ ] Refine project scope and list of limitations with data and potential risks of achieving project goal
+- [ ] Submit a PR with the above report and modifications to original proposal
+
+### Project Deliverable 2
+
+More data should have been collected to perform a more thorough analysis of the data and attempt to answer one additional question relevant to your project proposal which you will submit as a pull request.
+
+#### Checklist
+
+- [ ] Collect and pre-process a secondary batch of data
+- [ ] Refine the preliminary analysis of the data performed in PD1
+- [ ] Answer another key question
+- [ ] Refine project scope and list of limitations with data and potential risks of achieving project goal
+- [ ] Submit a PR with the above report and modifications to original proposal
+
+### Project Deliverable 3 (v1 Final Report)
+
+All data should have been collected. All project questions should have been reviewed, answered, and submitted in a written document outlining findings as a PR. You will also be asked to submit the associated data and a README explaining what each label/feature in your dataset represents. Your team should meet with the client before this deliverable.
+
+#### Checklist
+
+- [ ] All data is collected
+- [ ] Refine the preliminary analysis of the data performed in PD1&2
+- [ ] Answer another key question
+- [ ] Attempt to answer overarching project question
+- [ ] Create a draft of your final report
+- [ ] Refine project scope and list of limitations with data and potential risks of achieving project goal
+- [ ] Submit a PR with the above report and modifications to original proposal
+
+### Project Deliverable 4 (v2 Final Report)
+
+This is a draft of your final report that has been reviewed by your client. It includes all visualizations, results, data, and code up to this point, along with proper documentation on how to reproduce your results, compile and use your codebase, and navigate your dataset. Your team will submit this as a PR.
+
+### Final Project Deliverable
+
+This should be an enhancement of deliverable 4.
+

From 6bbe68a7d3492eecfb37a872e7c711045258d5ca Mon Sep 17 00:00:00 2001
From: varocarras <34591902+varocarras@users.noreply.github.com>
Date: Tue, 2 Mar 2021 21:27:19 -0500
Subject: [PATCH 27/38] Started Graphing Notebook

---
 .../Graphing-checkpoint.ipynb                 | 233 ++++++++++++++++++
 .../Deliverable_2/Graphing.ipynb              | 233 ++++++++++++++++++
 2 files changed, 466 insertions(+)
 create mode 100644 NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb
 create mode 100644 NaturalDisasterProject/Deliverable_2/Graphing.ipynb

diff --git a/NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb b/NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb
new file mode 100644
index 00000000..71ec896e
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb
@@ -0,0 +1,233 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "favorite-concept",
+   "metadata": {},
+   "source": [
+    "# Graphing function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "id": "transparent-shoulder",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline \n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "from matplotlib import colors\n",
+    "from matplotlib.ticker import PercentFormatter"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "african-reproduction",
+   "metadata": {},
+   "source": [
+    "## Global Values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "killing-redhead",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "miniature-timer",
+   "metadata": {},
+   "source": [
+    "## Loading Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "id": "framed-dispatch",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Field 0: 'datatime'\n",
+    "#Field 1: 'temperature'\n",
+    "#Field 2: 'windspeed'\n",
+    "#Field 3: 'surface solar radiation'\n",
+    "#Field 4: 'relative humidity'\n",
+    "#Field 5: 'surface pressure'\n",
+    "#Field 6: 'total precipitation'\n",
+    "#Field 7: 'latitude'\n",
+    "#Field 8: 'longitude'\n",
+    "\n",
+    "\n",
+    "data = pd.read_csv (\"historical_data_fin.csv\",header=None)\n",
+    "\n",
+    "#Take data to numPy\n",
+    "numData = data.to_numpy()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "working-transsexual",
+   "metadata": {},
+   "source": [
+    "## Helper functions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "id": "unnecessary-forest",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def getAllDataByField(field): \n",
+    "    return numData[1:,field:field+1]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "average-prime",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "id": "incorporate-cowboy",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "Image data of dtype object cannot be converted to float",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-108-0500433780e9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgetAllDataByField\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36mimshow\u001b[1;34m(X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, filternorm, filterrad, resample, url, data, **kwargs)\u001b[0m\n\u001b[0;32m   2722\u001b[0m         \u001b[0mfilternorm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilterrad\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m4.0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresample\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2723\u001b[0m         data=None, **kwargs):\n\u001b[1;32m-> 2724\u001b[1;33m     __ret = gca().imshow(\n\u001b[0m\u001b[0;32m   2725\u001b[0m         \u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcmap\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcmap\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnorm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnorm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maspect\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maspect\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2726\u001b[0m         \u001b[0minterpolation\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minterpolation\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0malpha\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvmin\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvmin\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\__init__.py\u001b[0m in \u001b[0;36minner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1445\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1446\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1447\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1448\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1449\u001b[0m         \u001b[0mbound\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\axes\\_axes.py\u001b[0m in \u001b[0;36mimshow\u001b[1;34m(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, filternorm, filterrad, resample, url, **kwargs)\u001b[0m\n\u001b[0;32m   5521\u001b[0m                               resample=resample, **kwargs)\n\u001b[0;32m   5522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 5523\u001b[1;33m         \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5524\u001b[0m         \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_alpha\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0malpha\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5525\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_clip_path\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\image.py\u001b[0m in \u001b[0;36mset_data\u001b[1;34m(self, A)\u001b[0m\n\u001b[0;32m    700\u001b[0m         if (self._A.dtype != np.uint8 and\n\u001b[0;32m    701\u001b[0m                 not np.can_cast(self._A.dtype, float, \"same_kind\")):\n\u001b[1;32m--> 702\u001b[1;33m             raise TypeError(\"Image data of dtype {} cannot be converted to \"\n\u001b[0m\u001b[0;32m    703\u001b[0m                             \"float\".format(self._A.dtype))\n\u001b[0;32m    704\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mTypeError\u001b[0m: Image data of dtype object cannot be converted to float"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(getAllDataByField(0))\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "wooden-receptor",
+   "metadata": {},
+   "source": [
+    "## Histogram"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "least-permit",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([5.0000e+00, 2.6000e+01, 1.2400e+02, 4.7400e+02, 1.3770e+03,\n",
+       "        3.3890e+03, 6.5770e+03, 1.1149e+04, 1.5483e+04, 1.7187e+04,\n",
+       "        1.6161e+04, 1.2524e+04, 8.1070e+03, 4.4260e+03, 1.9920e+03,\n",
+       "        6.9700e+02, 2.3000e+02, 6.1000e+01, 1.0000e+01, 1.0000e+00]),\n",
+       " array([0.44937032, 0.91990838, 1.39044644, 1.8609845 , 2.33152256,\n",
+       "        2.80206062, 3.27259868, 3.74313675, 4.21367481, 4.68421287,\n",
+       "        5.15475093, 5.62528899, 6.09582705, 6.56636511, 7.03690317,\n",
+       "        7.50744123, 7.97797929, 8.44851735, 8.91905541, 9.38959347,\n",
+       "        9.86013153]),\n",
+       " <BarContainer object of 20 artists>)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "N_points = 100000\n",
+    "n_bins = 20\n",
+    "\n",
+    "MAX_VAL = 100\n",
+    "# Generate a normal distribution, center at x=0 and y=5\n",
+    "x = np.random.randn(N_points)\n",
+    "y = MAX_VALUE\n",
+    "\n",
+    "fig, axs = plt.subplots(1, 2, sharey=True, tight_layout=True)\n",
+    "\n",
+    "# We can set the number of bins with the `bins` kwarg\n",
+    "axs[0].hist(x, bins=n_bins)\n",
+    "axs[1].hist(y, bins=n_bins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aquatic-dallas",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/NaturalDisasterProject/Deliverable_2/Graphing.ipynb b/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
new file mode 100644
index 00000000..71ec896e
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
@@ -0,0 +1,233 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "favorite-concept",
+   "metadata": {},
+   "source": [
+    "# Graphing function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "id": "transparent-shoulder",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline \n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "from matplotlib import colors\n",
+    "from matplotlib.ticker import PercentFormatter"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "african-reproduction",
+   "metadata": {},
+   "source": [
+    "## Global Values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "killing-redhead",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "miniature-timer",
+   "metadata": {},
+   "source": [
+    "## Loading Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "id": "framed-dispatch",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Field 0: 'datatime'\n",
+    "#Field 1: 'temperature'\n",
+    "#Field 2: 'windspeed'\n",
+    "#Field 3: 'surface solar radiation'\n",
+    "#Field 4: 'relative humidity'\n",
+    "#Field 5: 'surface pressure'\n",
+    "#Field 6: 'total precipitation'\n",
+    "#Field 7: 'latitude'\n",
+    "#Field 8: 'longitude'\n",
+    "\n",
+    "\n",
+    "data = pd.read_csv (\"historical_data_fin.csv\",header=None)\n",
+    "\n",
+    "#Take data to numPy\n",
+    "numData = data.to_numpy()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "working-transsexual",
+   "metadata": {},
+   "source": [
+    "## Helper functions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "id": "unnecessary-forest",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def getAllDataByField(field): \n",
+    "    return numData[1:,field:field+1]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "average-prime",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "id": "incorporate-cowboy",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "Image data of dtype object cannot be converted to float",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-108-0500433780e9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgetAllDataByField\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36mimshow\u001b[1;34m(X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, filternorm, filterrad, resample, url, data, **kwargs)\u001b[0m\n\u001b[0;32m   2722\u001b[0m         \u001b[0mfilternorm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilterrad\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m4.0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresample\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2723\u001b[0m         data=None, **kwargs):\n\u001b[1;32m-> 2724\u001b[1;33m     __ret = gca().imshow(\n\u001b[0m\u001b[0;32m   2725\u001b[0m         \u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcmap\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcmap\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnorm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnorm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maspect\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maspect\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2726\u001b[0m         \u001b[0minterpolation\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minterpolation\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0malpha\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvmin\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvmin\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\__init__.py\u001b[0m in \u001b[0;36minner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1445\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1446\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1447\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1448\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1449\u001b[0m         \u001b[0mbound\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\axes\\_axes.py\u001b[0m in \u001b[0;36mimshow\u001b[1;34m(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, filternorm, filterrad, resample, url, **kwargs)\u001b[0m\n\u001b[0;32m   5521\u001b[0m                               resample=resample, **kwargs)\n\u001b[0;32m   5522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 5523\u001b[1;33m         \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5524\u001b[0m         \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_alpha\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0malpha\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5525\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_clip_path\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\image.py\u001b[0m in \u001b[0;36mset_data\u001b[1;34m(self, A)\u001b[0m\n\u001b[0;32m    700\u001b[0m         if (self._A.dtype != np.uint8 and\n\u001b[0;32m    701\u001b[0m                 not np.can_cast(self._A.dtype, float, \"same_kind\")):\n\u001b[1;32m--> 702\u001b[1;33m             raise TypeError(\"Image data of dtype {} cannot be converted to \"\n\u001b[0m\u001b[0;32m    703\u001b[0m                             \"float\".format(self._A.dtype))\n\u001b[0;32m    704\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mTypeError\u001b[0m: Image data of dtype object cannot be converted to float"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(getAllDataByField(0))\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "wooden-receptor",
+   "metadata": {},
+   "source": [
+    "## Histogram"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "least-permit",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([5.0000e+00, 2.6000e+01, 1.2400e+02, 4.7400e+02, 1.3770e+03,\n",
+       "        3.3890e+03, 6.5770e+03, 1.1149e+04, 1.5483e+04, 1.7187e+04,\n",
+       "        1.6161e+04, 1.2524e+04, 8.1070e+03, 4.4260e+03, 1.9920e+03,\n",
+       "        6.9700e+02, 2.3000e+02, 6.1000e+01, 1.0000e+01, 1.0000e+00]),\n",
+       " array([0.44937032, 0.91990838, 1.39044644, 1.8609845 , 2.33152256,\n",
+       "        2.80206062, 3.27259868, 3.74313675, 4.21367481, 4.68421287,\n",
+       "        5.15475093, 5.62528899, 6.09582705, 6.56636511, 7.03690317,\n",
+       "        7.50744123, 7.97797929, 8.44851735, 8.91905541, 9.38959347,\n",
+       "        9.86013153]),\n",
+       " <BarContainer object of 20 artists>)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "N_points = 100000\n",
+    "n_bins = 20\n",
+    "\n",
+    "MAX_VAL = 100\n",
+    "# Generate a normal distribution, center at x=0 and y=5\n",
+    "x = np.random.randn(N_points)\n",
+    "y = MAX_VALUE\n",
+    "\n",
+    "fig, axs = plt.subplots(1, 2, sharey=True, tight_layout=True)\n",
+    "\n",
+    "# We can set the number of bins with the `bins` kwarg\n",
+    "axs[0].hist(x, bins=n_bins)\n",
+    "axs[1].hist(y, bins=n_bins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aquatic-dallas",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From 5dbc012368b0c6d29c913fb159b766ee8d7e47e4 Mon Sep 17 00:00:00 2001
From: varocarras <34591902+varocarras@users.noreply.github.com>
Date: Tue, 2 Mar 2021 21:28:00 -0500
Subject: [PATCH 28/38] Updated historical_data_fin fields

---
 .../Deliverable_2/historical_data_fin.csv     | 6271 +++++++++++++++++
 1 file changed, 6271 insertions(+)
 create mode 100644 NaturalDisasterProject/Deliverable_2/historical_data_fin.csv

diff --git a/NaturalDisasterProject/Deliverable_2/historical_data_fin.csv b/NaturalDisasterProject/Deliverable_2/historical_data_fin.csv
new file mode 100644
index 00000000..b5234eb2
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_2/historical_data_fin.csv
@@ -0,0 +1,6271 @@
+datetime,temperature,wind_speed,surface_solar_radiation,relative_humidity,surface_pressure,total_precipitation,latitude,longitude
+2010-02-27,8.5,1.51,233,0.5,101170,0.0,32.7003,-90.6783
+2010-02-28,8.04,2.59,75,0.62,100953,0.19,32.7003,-90.6783
+2010-03-01,5.64,4.81,89,0.76,100742,0.3,32.7003,-90.6783
+2010-03-02,5.33,3.02,182,0.59,101282,0.0,32.7003,-90.6783
+2010-03-03,5.36,0.77,242,0.56,101601,0.0,32.7003,-90.6783
+2010-03-04,7.5,1.68,240,0.49,101753,0.0,32.7003,-90.6783
+2010-03-05,9.39,1.87,241,0.46,101960,0.0,32.7003,-90.6783
+2010-03-06,10.81,1.32,182,0.5,101827,0.0,32.7003,-90.6783
+2010-03-07,14.21,2.0,211,0.58,101385,0.0,32.7003,-90.6783
+2010-03-08,14.23,4.24,66,0.71,100575,0.59,32.7003,-90.6783
+2010-03-09,18.18,3.99,102,0.89,100028,0.58,32.7003,-90.6783
+2010-03-10,19.06,1.19,229,0.68,99740,0.76,32.7003,-90.6783
+2010-03-11,15.27,2.71,193,0.6,99898,0.3,32.7003,-90.6783
+2010-03-12,11.35,3.91,121,0.55,100027,0.0,32.7003,-90.6783
+2010-03-13,12.31,3.29,191,0.63,100372,0.0,32.7003,-90.6783
+2010-03-14,13.47,3.57,236,0.63,101145,0.0,32.7003,-90.6783
+2010-03-15,12.03,3.12,191,0.65,101596,0.0,32.7003,-90.6783
+2010-03-16,11.88,2.5,123,0.68,101409,0.01,32.7003,-90.6783
+2010-03-17,12.51,2.53,194,0.64,101278,0.0,32.7003,-90.6783
+2010-03-18,13.13,1.36,241,0.57,101159,0.0,32.7003,-90.6783
+2010-03-19,14.55,2.91,169,0.63,100899,0.02,32.7003,-90.6783
+2010-03-20,7.48,4.78,108,0.73,100359,0.46,32.7003,-90.6783
+2010-03-21,7.46,4.25,101,0.75,100616,0.04,32.7003,-90.6783
+2010-03-22,13.73,1.81,266,0.64,101002,0.0,32.7003,-90.6783
+2010-03-23,15.55,2.99,269,0.66,101051,0.0,32.7003,-90.6783
+2010-03-24,17.89,3.69,164,0.69,100441,0.44,32.7003,-90.6783
+2010-03-25,13.7,3.34,250,0.56,100913,0.0,32.7003,-90.6783
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From 2bce8bc46c2b3c3c4dc7bc9effc2c1f0aefe4e20 Mon Sep 17 00:00:00 2001
From: Alvaro Carrascosa <varocarras@gmail.com>
Date: Wed, 3 Mar 2021 02:07:46 -0500
Subject: [PATCH 29/38] Created a Graphing Notebook

Added Graphing.ipynb to Deliverable 2.

Updated .gitignore for Deliverable 2
---
 .DS_Store                                     | Bin 8196 -> 6148 bytes
 .gitignore                                    |   6 +-
 NaturalDisasterProject/.DS_Store              | Bin 6148 -> 8196 bytes
 .../Deliverable_2/Graphing.ipynb              | 426 +++++++++++++++---
 4 files changed, 359 insertions(+), 73 deletions(-)

diff --git a/.DS_Store b/.DS_Store
index 7add333b4740c32b5e02b353d605668c02087f1b..8598a7393004894ce204abb2ba3c63280cb561aa 100644
GIT binary patch
delta 204
zcmZp1XfcprU|?W$DortDU=RQ@Ie-{Mvv5r;6q~50D9R3!2a6RkBr@bMxG-cg6mKkC
z&dkU@d4h<+<T(QTtnNTHI+JZgEG8ci;buHJ`HV<|rbKnMk(q&xg0YElt&T#qr4f*A
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literal 8196
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diff --git a/.gitignore b/.gitignore
index 3e9537da..f2487e7c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,5 @@
-
-NaturalDisasterProject/Datasets/.DS_Store
 .DS_Store
+NaturalDisasterProject/.DS_Store
+NaturalDisasterProject/Datasets/.DS_Store
+NaturalDisasterProject/Deliverable_1/.DS_Store
+NaturalDisasterProject/Deliverable_2/.DS_Store
diff --git a/NaturalDisasterProject/.DS_Store b/NaturalDisasterProject/.DS_Store
index 8c997c13430072c16c73461441f811642df87b65..a77882f1a7dbb8703213df72ff0be6a9145f291f 100644
GIT binary patch
delta 480
zcmZoMXmOBWU|?W$DortDU;r^WfEYvza8E20o2aMA$iFdQH}hr%jz7$c**Q2SHn1@A
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q!W9%hn*}+(Gf(Ch@to|>!@&UzSWwh4OpfQ7vALXW0^`Pp5=H<oC~R8*

delta 177
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I=b6I{0H#SM4FCWD

diff --git a/NaturalDisasterProject/Deliverable_2/Graphing.ipynb b/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
index 71ec896e..995a1e93 100644
--- a/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
+++ b/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
@@ -2,16 +2,14 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "favorite-concept",
    "metadata": {},
    "source": [
-    "# Graphing function"
+    "# Graphs"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
-   "id": "transparent-shoulder",
+   "execution_count": 222,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -26,7 +24,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "african-reproduction",
    "metadata": {},
    "source": [
     "## Global Values"
@@ -34,15 +31,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "killing-redhead",
+   "execution_count": 239,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "NUMBER_TORNADOS = 108 #Number of Tornados\n",
+    "NUMBER_DAYS = 57 #Number of days of data per Tornado\n",
+    "FILE_NAME = \"historical_data_fin.csv\""
+   ]
   },
   {
    "cell_type": "markdown",
-   "id": "miniature-timer",
    "metadata": {},
    "source": [
     "## Loading Data"
@@ -50,8 +49,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
-   "id": "framed-dispatch",
+   "execution_count": 240,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -66,7 +64,7 @@
     "#Field 8: 'longitude'\n",
     "\n",
     "\n",
-    "data = pd.read_csv (\"historical_data_fin.csv\",header=None)\n",
+    "data = pd.read_csv (FILE_NAME,header=None)\n",
     "\n",
     "#Take data to numPy\n",
     "numData = data.to_numpy()\n"
@@ -74,7 +72,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "working-transsexual",
    "metadata": {},
    "source": [
     "## Helper functions"
@@ -82,47 +79,163 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
-   "id": "unnecessary-forest",
+   "execution_count": 241,
    "metadata": {},
    "outputs": [],
    "source": [
     "def getAllDataByField(field): \n",
-    "    return numData[1:,field:field+1]\n"
+    "    \n",
+    "    return numData[1:,field:field+1]\n",
+    "\n",
+    "#Returns elements of a given field (0-8) for a particular event (0-107)\n",
+    "def getDataByFieldAndIndex(field, event):\n",
+    "    \n",
+    "    return numData[1+(NUMBER_DAYS*event):(NUMBER_DAYS*(event+1)+1),field:field+1]\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Sample Data Graph\n",
+    "##### Temperature leading to Tornado 0"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "average-prime",
+   "execution_count": 242,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.ylabel(\"Temperature C°\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(1,0).astype(np.float).flatten())\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "## Temperature"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Linear graph of Temperature for all Tornados"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
-   "id": "incorporate-cowboy",
+   "execution_count": 243,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.ylabel(\"Temperature C°\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(1,i).astype(np.float).flatten())\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Linear graph of Net Temperatures for all Tornados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 244,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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vw4vaOPtXce69jRce4Kkp3oufwHvpZcxPPE+y3GJwb5vxu+8Q3rpJurPDaBIRGi5emrHS79IcDdAetpeVMubaGvbm1gMBWF/HXJ8Jgd5sIrTZ4PMkzvgPb+zzM1++x+/c7APwqdMNfuzFDX74uTUcU+M/XLnFf7qzw9tRwr7tMPDKMHdhWmGMGGXkwwIRFxhAs+bwXWda/J3vWUyCeywLcVjwzcTjS7teJQxvsSjt+nuTRjl7N0bsXhuw/Xafzr3poQC8F3bJpLHmUfMlXrCHvfMOxpu/hX73KgKgVEI9dYmsWScXkI3H5O029AdYQYiT5pjyeF2ETNfp1puIVpP1E5vUzpzB2tjAXHtg/DXXfd/7ygvJr1/v8rOv7fCLb+2T5JJTTY/vvbREfcnntdGIa9MRfUMwKvlIbTbGYaUp3jhABpK0MFlyLM41fZ5drfDKagU7lVy7M+KLt/o8vVbh//wHLzzRe70QhwULvgl4UNp1ntl23ttIkv3DfR4t7TpLVPj7ubRrEuXcfbvHra902Ls2ZDpM33Nfy9GpLnusnCrT2ipRSnvYd94gu/zbBK++SjKZkBoa0nEQloWW5xhRjJWkPCy5uWVSVCtorRbm+gYHGyf4T5UWv+VVyVdW+DPPnOcvbC5RMr6+5JBKKd7eG/PTl7f5/Fd2GYYZhmvgLLvEvk7hKrKqTW7OIuGMIqcxHeOGMY4yWG22+PSJZV5ZrXCp5FLXdd7dn/A7N3v8zs0+v3urR5DEnK9f5w+ceI3l+gn+yg/+D1/v2w4sxGHBgm9qsmw0m5/xUL6pPB8f7vP7obTrLJY/4+D2iDtv9tm/MWTUiY6liThEgFsyaaz5rJ4ps7WqKOU90q+8xuS1Vwlu3iQf9BGFRC8kxkN2TAKxbZKXfGg0MFZXcU6epHTuHLWnn6F89hya7yOV4hc6I/6fdw54fRqxYZv8lyeW+XNrTVz9955hr5SiM0240Q64fKfPL75zwNX2hNg1kFULWTWhaiK9mRAIpagHY5YmQ5pFxvlale+9cIZXTp+gac32KaTinb3xXAx6/O6tPuM4p2KN+Z5TV3hh7TJr1jUskZMruDIu89f++Fee6DNZhLIuWPBNjGlWqdVeplZ78Bt9tLTrrC7411La1fNOfqyp0JVUTAbxYdbQzt0JnTsTRt0QWTz+GNNQNCo5K/6UZXGA27lBcuM22RfuwXjCWCnGR/aXukZqGkSeTVGpoK+uYG9s4p05Q+XiJRpPPU1lafnQ3/8wuVT8zH6fv3vngGthwhnX5m9f2uJPrtSxHnNMXkju9kNudAKutCd8dXfEtc6UnW5IYmvIqoWqWshNC3VpFebzG/w4YmXcZnlvwAmZ8dn1ZT554RynTn0G257lBCuk4u3dMT9zs8cXb/X44q0+kzhHIPnMVo//w8uvs+5+kYqY9TBHheDLE532fhnjlscP1k898Wf1fix6DgsWfAtxvLTrg3ToUXSHB6nQbXzv3Ide2rUoJKN2NEsfvRceppHu700psrldURKtmLl0Ct2Ceb4rvxjSiO9SOXiLysHbuEn/8LwKiEyDyDKILYPINMhNA71awdk6Se2ll2g+8yz1tQ2qyyvoxtc+UTGRkp/e7/P377S5E6c85Tv8n06u8EeXa+hCME1ybnamXG9PuXIw5Y39MTc6UzrDmEIqcHRk1UTWbWTVRJVMmM921nPJajxltb/H0njAejTlua0Nzp49y7lz52g0ZqHOeSF5e2/MF2/2Zz2D2zMxALi0rPEHz93lVOU38IvXMEWMVHA31bg+MRnd9Vna9fnuxkme+uz3s/rZH0F4tSf+DBdupQULfp9zv7Trwz2NJD043OdJS7tmScHwIKS/FxxLHz1qR4g0wk4G2HEfmxipNFLdJ3KbJM4sPl/IjMr4DrXRDaqjG5SibQqjIBAQmTrRXABSXUNXYEpFtdGkefY8y598iZXPfQ/uN1jtLCwkP7nb5R9ud9hLMp7xHP6o51Ob5FxtT3lrf8LtbsBo+mC8Q5oCuewiGzaqYiJcAzmPiEIq9EnGShJzYrjHqcFdqnHA2uoq586d4+zZs2xtbWEYxqEY3B8z+NKtPpNkJgZnlny+91zKJ5a+gpP+r4jiLppQRBKuRDrbPZv4ZplLQZNPX3iJC9/3J2ice/YDE/mFOCxY8G3Kg9KuD6r0TadXH1va1THPobKTJKMNJgdLDPcSprf2yPf3cZI+djzATfv4xQg7HpBgM/XWGVbPMqqeJbWrABh5RCm6h5NsI8Kb5OkesTnrDaSujWc5eEGE2x/iJxk+gqVLT1F9+RX8l1/B/cTzaM43PpaSFZK32mP+yd0u/yGcEgLeNIfrY4qD6HCAWukCWTaQTRtqNnbFQtk60RHb6MQFaS9GH2dsRRPOjm5zUvSp+O5hz+Ds2bOUSiXyQvLW7oMxgy/dHjCdi8HZJZ/PnKnw2c17tOS/Zzz9bXQxS0t/kAneDXU6ux7azQqvWKd4/tM/yLnv/AEqreVHnk8pRZb1ybIE319/ovdoIQ4LFiwAZgZlOojp7Nyid+/LhNtfRvauY0x2sYIxxlCi9wX6YLaI+RhBoVmMKqcY1C8yqF1gWtpE6rM00loRIJIdivw2qdpFqSGV5RVq1Rp+AW5/gHXzNs7eAU6Wo1cqeC+9NK9u9hLO008jzCfPYTWOM260p9zoBNzoTHlnf8I7/Sk7VYN8ywdTQ+vE6PcCKBTSN9BrFtWGi1uySIWik+Xcnx6xbBlsKJ3J/oR7t8aoUUpLBpzRupwzB1w4sXYoCKurq0gFbx4Rg8uPiEGTz5yEC+Yv0+n+O8LiDrqmyBVcjzVujE3Gd0o07lV5Zf0lnvrs93PmpU/hlHyS5IA42iYevkUwuML19pArPbgxrnArWObedIMXKzf5n/+r//aJ3ruFOCxY8G1GkeUMr+0yeOsW0xt3ie/skO3vQe8AO+xjx32sPDh2jBIaolGjqHmMnTpd+xxD4yyhtUKhu/PJWArNGmG4tzHd2/ilnGr9BLXWWUoFOPsH6G9fIXntNYr+bBxBX2o9qHv88svY58+/50Dxe6GUYm8Uc2M+HnCjPeXd9oTrnYDhEVeQcjSycxXkqgcaaLFkzdDZbLjousYwK7gTpwTFLELK1zVeKHu8WHZxg4w3vnKPL14dERXgkXJG7/FCLeUzT53g7NmznD59Gt20eHNnxO/c7PPFWz2+dKtPkM5U9Nxyic+cafCZ03WeL32VaP/fcG96GcwQgGEueCfW2Ok6yNs+5+Iyz1y6yNrZKn45JIu3iZJ92lHKjWmD7ekG96br3JussztdI1ezGCJD5GxYB2ypA55XXf7r//7vPtH3ZCEOCxb8PkNGEdnePvH2PcZX7xDcuEeyfQ/Z3kcMOphBH03lx48xHWR9GW1pBWN1CZplUtekG8H+uMIgXkKqGkI8KCyjlETXQ7z6gNbpfaondzD8XdL8LlneO9xPCwTGDpi7AjtsUG4+T/3C91B+6TswT578mn3kSV5wpxceCsD1zpQr7Sm3OlOSIwnzMATSN5AlE+UbWFULt+EwQKGAk47Fsm1yL0rZS7P7h/C07/JCxeOTFY8Xyh6Du3v89G/f5FdvhwwyHYOCU8aI79qy+EOfOMmF8+cpV2u8uftgAPny7QdicH65NOsZnGnySmMIez/Fdu8/09f20IxZ8tROLuhnGlqkUc8VTRsMXyHNglzq7AUr3JvMBGBnvM72dINhVj181Ko2ZUPrs6oSToYx5/ptLrT3qelLGK2LRFbB0//4//h1foNmLEJZFyz4FkIpRdHrke3tke3uke3tEt+5R3TnHunOHqp7gBaMjh+DQNpV8lIL1s+hVtcw15YQLZ+iajFVGYNhj/7eLsODADltoSWnEHoDIR64dDRN4VYUa2c8Ln56i62n1zAsHRmGRF/9KuGXLhNeHhF9NSU3TfJ1hfpEE3mpTHY2J750QCC79PnP3OE/4+ys448eLu16hkksuN6ZcKM9cwVd70y5cjBhZxBxrL3q6hSegVpzUSUTr2JxfrnE0w2fc57DKC/4pd6IN6cx8VwYAO7EKZqAz9ZLvFj2eLHi8UzJRcYRX3n7Kj/7K3f4O/cy9nMPUJx0Uv7YuRJ/8jMXOXPqBO8cBPzOzR7/8PM3uHy7TzgXgwsrJf7ES5t8+lSNF5tttP2fo9v7Nbq7O7zekQghkOaDCd1CwLKpWDIKprjsD9Z4uzcTgNvhJtvpKvncDOsULIuAU5riaT/h+ZLHJVlQH0vynoGiguY2MNc8xNqDnte+9WAS5QfJouewYMFHjEwS8r29ufHfnQvA7HW6s0u+vw/Z8VnCuWYROw0Sp0HiNhCtZcz1DZytVfQVH6oaaTpg1N47LBITjoYACG0Z3X4awzkDVIAHhsUwBY2NEiefaXH2pSUaqz5CExSjEeGrrxG+epnw8mXit96GPAdNw3nqqZmL6JWXcV96CaNePzzf0dKu08kVOoO3mUyvovI7CGY9mUJq7IfL7EzWuTddYzdcZ7vYoq2vIH0LWTKoVh0uLJd4qupxwbM579l4usbtKOUrk5DfHEx5N4i535dwNMErVZ/PVEu8WPF4oeLRMA2KouDevXu8e/Ua//GNHS53NbZlDYnGiiP5wYs1/ux3XCRU5uGYwat3BmR5RMMZ8MJazAsbMWcaU5bMXeT4bcL8gEzLeXjKdSohyoEp5IMlOuMT3IhOci3Z4na+xkQ9SMC4Ss5zhuBpx+C0q7Nm6VTQ0UcFVqBjqOPt9r4+Yt/qcWB22Td77Fs92kaXVD/gUjzg//rX33qi7+LCrbRgwUeEUopiMCDb2SXb252JwBHjn+3tUfR6x49BkHs1IqtGZNaJnQaxXaeotLA3N3BPr+O0THRjQpH3iccdBvszARh328cKv3i1OqXGsyDOksRV0kg/1hK3PYPWVolTz7U4+9Iy5fosKihrt4lefZXw8quEly+TXL0KSiFME+f55w/HC9wXX0AvlY7df5wV3OoGD8YDOgHX21NudqYk83TZushZq3VZbxywVtlj099l095hWe8cnkcKF8M9S618Cc1/lpuc5918idcD+Mo4ZJDPWu8asxnQpoDvb1T466dW+ETZO3RdDQYDrl+/zvXrN/jd6/u8E1e4VTRIMKlYgj90qcHLZ8pMgrvcbt+gN9qmYvVouX1OlnvU7QG6fnw8BqUQEqTGrHegZtFFNwKPvYOTTHvnmcYn2JXLdFQZE1jXYza1lHNGzknDYE1YNAuHWuLh5sdrQk+1kIO50T8weoyNEak2QGldDHWPFn2Wi5zlvKCVF7SKgqaUDDSdr1pn+IG/+WT2byEOCxZ8QMgkId/fP+byyXaPi4BKkuMH2Q6yukTiNQiNGmNVmYmAPRMCbWmZ2lqZcl1hOhNQQ/K4x2Swz3Bvl+H+LkX+YPzAcl3qa5vU19aprmxQyDWGbZfhfk4wTI+JgVs2WT5Z4cyLS5x5cQnHM2chkDs7hJdnvYLoS5dJ79wBQHge3gsv4L0yEwPn+efR5jN5+0F6bED4vjvoXj86lhfP8Awyz6DwDZRvIEsGq3WXSw2fC77DRc/hgu9w3rPxRUx3cp3Lvbu8NprwRqTzbtaiw6zWt1AFW2KPZSPlQC2xXZSpavATW03+i601qqZBmqbcvn2b69evc+PGDe50R9yhyg25Sj/zMDXJJ9c6fGLpTc6XX6VkHmAZ2bGPSEhw4wInKbBjiaYUsakxKFlIdyY6w1znzfES7/ROcaN7Hq+osiIEawLWlMGGcliTPst5hUZ+fO5IIlIOzD5de8jAGDAuepD0seUEz4poGmPWZZfVYo+mzDAAqQTj3CMtFJZWUDETMgG/bpf5fGmdV11BJmMuFM/yL//qv3yi7/NCHBYs+BpQSlEMh0eM/RGXz95MCIpO95Hj9KUlaCxTVFrETp2pqDEsygzSEpFVIzd80ASVpkOlpeP4Abo+RuZ94qDLeO4KSqPwwTkNg9rqOvW1deprG/NlnVJzlb3rKTe/0qF9e0I4fuB+EgL8ms3qmQrnXl7h5LNNDFOfpRa/cWMuBrOeQb4/81Nr1eqDsNJXXsa8cJHdaX5sPOBGZ8q19pRh+MCgarpAL5kkrn4oApRMNhsuFyseF3yHC0dE4H7yukIprgQxXx6Hs2US8G4QH4aRbjomL5Z9nvMVF7V9doI9frJf4e2sRY0Bf0R9nu/jP+EQA1XS1CGOFFFu8cbwIq/2nufq8DQA52vX+QPrX+Llla/gE+HGBV6S4yRyLgQSI3VQSYVxXuJO3WDQjDEbU1wjRyRV+sNNuqNNkmAJL62wmldZy5osZXV0HqQoKSgY2lOGbsDQDejYIbt2wB0jwhrs8NzubT43DjhhxtilCMtoI0Q+/94JYtmil9XZiyHLYspGzKo3pWIk3Cg8fl2tcI0y41zhRTrV2MUtPNBsPHfKX/v7P/dE3/mFOCxYAKg0JTs4mLt89o67feYuHxXHx44RjoO5toaxtobWWiErtYisOhNmxr89cZhOHkTRaLqg0rIoVWNMewIMyZIe4bDN6GCXYDg4cnJBpbV8TAAaa+vU1zcot5bQNJ14mnLlSwfc/mqX7vaE+EjBGjEXnLXzVS58apXNi3WEEKg8J373CuHlLx26iorB7LrG0hLeKy/DJ1/m4OyzbDsNbnTDmQi0p9zsBqT5g+cxHR3hm0SuhvTNuQgYnKp7XCy5cxGwueA7nPUcvCPJ6pRS3EuyuRAEfHkc8vo0IpyHkVYN/XCw+MV59NCybRKnIz6/t80/2I25Ehus6iF/yr7Mp+L/CNldNG3m8imkxtv9i/zW7it8pf08qbRY8dp8x/Lv8n313+F00cadKJJJhUHRYFf32cbgnibYMwosS3DJtrio+WzlDey4hRYuQbiEG7ew1HHXz1gPmLoJSQ16Xsquk3LLyrliCa7rikqecC6e8OnONT7VfoML2R5Vc4SmPfjMcrVEVGwxyJbZTSxuT0b0wpimHVG1EgxNMlBlDqgS4iM1B2lYKNOcry2UYR7WeABwwoK/+f/477/OX8P9r+BCHBb8Pud+q//BQO9RP/8u+e4eebcLD33f9VbrWKUuY22NvNQkNGqMVIXBWGdwENHfD45VEtMtjWozw/ECdGOEzAfEQZdpb59xp41SDwysV6090gOor21QW1nDsB4yQL2Iq1/c586bfXq7U7L4QaY63RBUlz02Lta59JlVlk/OXBcyTYnfeOOwVxC99hoyCFBAcPoi7U98hr2Tl9iurnIrEtzoBOwMo8PzCgG2byJ9g9DVZ64g30AvGZyp+lzw7cOewEXf4YxnYz9mnsIwy/nKZNYjeG3eM+hms/fMEoJnyy4vll2e8wqeMvssqx3SZJco3iWOd5hGe/xSfIrPyz/MnthgTe3wI/wMn5G/SR47JIlPHrsMxlVe75/nd+JzjDSBb7S56LzLqn8X3DEDs2AocqJCx4tbLGdLrKRN1rImZ4sm63mTWtLCzP1j9x9qCQcipCcnjIjolxTtNZ/bdZtrvkFHOKSiwmo+4WJwm0vBLS6Gt3h2dI3z0V0cHvTictkgVydJ5Bb78Qr3IpO70ZR+0SM3FJppIA2L3LCPGX31uDxRUqAVJrp00AoHIxc4cYYXRvjBmKm5z3/x//1n7/XTeF8W4rDgWx6VpmTt9vu4fPZQYXjsGGHbh2UZjbW1WZGWtTXMjXW05RVCvcqwnx9LGjfYDw5TSCulsL0MvxJiOlM0RmRxj3DcZtzZo8geuFlMx6WxvjF3Bc17AGsb1NbWcfzjA7iHz6QUvZ0pV3/3gO13+gz2Q4ojsfyGpVFf9TnxdINLn12ltjIzZjIICL/ylVmv4EuXmb7+BntGie3yMnunnmZn4xz3vBa3U51R8kBcDEPDLptknkHgaqh5T8AsmZwrzVxAR91Bp10bU3v8/IS4kLw9jXhtLgZfHofcjB6MtZyxJc/YUy4YB5zjBuv5WxTpPeJ4H6WOR2JJ5fOb6vv4GfFHaIsWG/F1nu/8NtXRAdNCoYsxmRGxoxm0BaRGiDAm6ELRymqsZi1WsyYraZP1dJnVbInlrEGjKB+/jpaROV1St8vQCOjrESN7yMTrsldWXHPPcsu8xA6nSLBZyvpcDG7z1PRdnglu8FR0l7PhDqX8wfcsyzyGyRb76ixt2aInXfoKQpGQaJJcN1CmhTQs0B/NlCsK0AodrbDRpYcmfaxM4UQxfjClNB2ipQMSY8zYjRlWJOFSGW19i8raaU62zvLU2gYXLi2K/TyWhTh8a6OUQo7HD4V2Hnf55J3Oo63+ZvNIXd714yKwvobeaJCn8oHhfyhpnJRqfv0UtxTMewGzsYAk6DLt7x8bB9B0g9rq2rHWf2Ntg/r6Bl619ntO9Cpyyf7NEdcut9m5OmDciY6XtHR0mhslTj3X5OKnVynNI4mK4ZDwtdfofuk1rrxxgxvtKdt+i+3yMjvNLXbsKtmR8FTHNTDLFomrERzpCTiewQXffUQETjgWxnuIAIBUiuthMusRjIa8NprwTiTJ1eyYhhZwQdvmjHyXk8VXOcN1PO6/bwIbDzs3yGNJPI2ZBiHjXHEgbX7du8RVt0GhpphZDyFHqPs5OxTUiworaZOVZI2VZI31dImNvMZqXqVelNGPPHeBoo1ioIfkXhu3eotS7TqZ26FrjHkjVbybmOyKS9SsNZZMizXR5VR6izPRDvU4pBwnlJKYUpxgFxkFGt2izE6+yn62Qi+vM9bKRJpNquvkuoE0zcNss0e+1IhcohUaWmGhSQdd+uiygpUpvCDAD8a4UR+lBoTmlJGX0KlqDCpl4soymr+FZ6zRDBWt7pBGd4Qexag0Q+UFuQ6DpsBmwl/4p//j+3733ouFOCz4WFFZRnbQJt/bfU+Xj3y41W+aGOv33T3rhz2A+0JgrK4eS84WTzP6+8ezhvb3Aqb9WWtWqQIY4fohlj1BiNlYQDRqE02GRy4sqLSWjglAfW3WIyg3lxBCQymFkszXCqV4aK2QUpFGOfs3Rtx5q0f7znzw+MjPzXR0aise6+dqrJ+vYnsmSiraOx3uvnOTe3c77A1C2tKk51aZWrOeg4ZACHAdA83WyUyNzBQISwdLw9E1lk2DZdNk2TJoGTotw6Cia3D0Xh95DkWeRXRkwFU95boJN22DO65DrM/i7u0iZ3M6YmsyZmsyZmMyoZwmTLWYQAsJRcBUTJjqIRMjYGpETMyQiRWQa48Wc6ikNU5GJzgRr7OeLLOaNWjlNRqyRFU5mA8Z3bGS7KPYRrIjJLtI+iJmuXadU8tf5uzKm3jOGKUEUe80wd7zTPeeIxluYYuAhnGXhrFNw9imbGxjGANiITgo6vRklb6aRZOFmkumW0j9uH8fACnR8hwtV4jCnBt+D02W0VUVJwEvGOPGfeykTy4GBFbA0M85qOocNJuMSsuk1jpCX6OcetSn0JgW1KcSQ86itFAKoSSgEEqhIbEFmE6I4cbYpqKkbKbxmB/92z/x9f0oD7/uC3H4luD9jM39H7GUChTIh7a/53GPPdfXfg2UQr7fNaREBQH0D2DQRvQ7iP4BYtBGDDpoww5i3J9/yR8gvSpFtUVRmS15ZYmi3CKrtMhLLQq3jFLaI9fN0oIszsnigiwpyNKCPJXIYvYMIBEUCE3O4hNVgZISKQvuT/4SaAhNQ+gGmqYjhD7P9aMB4tH3Tanfs4bxtyICSWLAXkNjp2Gy0zTYaZhMvFneB72IWBq2aQ071IIubtwDNSAyJ0zNCYE9JbCmZHr+yLmt3KKU+NTiCifC1bnhb84Nf4Wq8PE1F1M/PtkrkzmjPKOjcnaE4oYmuG7o7CHZQ6LnGRtxwCXjLs8sv8P6xg289QOErlCxgby5DDfr2Ac2upWBn5G7iqlpMhI+I8oEwiPWPArtMf79IkfLMrS8QCsEorDRpYsmS+iyiq7qWKnESwa4cR8j7ZGLEYEd0itJDmome0vL7DdPEDp1NCWpjzvUxx02Om3Obx9w6U4bP00QSpFrkshWhLYksAV5uYoqtdC8JobbxLValIwmVZYoUUXjuFhG+YR2dIPv+J8++PQZ39biMGyH/M7P3XjEELyX0XzYOB41nsyN6tdy3HsZ2m9GhCyw0hFO3MdJ+jjxAHu+dpIBTtzHKI5H+EhhENs1Eqcxm9XrPlhSt0HmN5GGhaYJEAJNzCJvhBCI+5OM5Oz9lLlE5pIilxRZMX+fJKgcQY6m5QiVo1SKzFNQEoEEpdCEwLAMTNPCtExM08SwTEzTmrl/5y0zMVNChFIICpAKVDETNClnayURsmCmlBKKgqQwCKTLRJaI8JBHQhtRCkMlePmIUryLGx1AGiKLHJXlKJmjyQJDFmiqQL+/FAUa8kiLcfYs4tjr2b3ymG3HjpuvxVw0C6Fxa2OT18+c4O3Tq1xfr9Ot6Qg5QiuGlIJd3LiNkCMSIyIzHv1OOhk0QqiHGo1QpxHZrEVNlpMWjaJJRdRxtTqWVce0a5jWcb9/oQqCImCcB7RVzg6K20rjpmZw1XIYafcFXOGJhLIW4WljSnqHc7UrnGzcZa0cYAqLNPEYTz2isYuaeqjUI8Un1jzkw5XwlELkGSLP0PJ05vLJ9dkgryyhyzI6NTRRx8wkbtLHjftoeY9MGxGaIb2yYqfpsbe0yn7rJHut05gyZX2yTzPeRYoD7jpdRloHI9/ntJZwKZWcGivMEXQTk4lsIJwlKlaLhr7EcrHMUtakntbwi9Ix46+UIiNmIiIGWkKYD1HRDuNph3E6oZB9Nqtdso0af+K//cUn+30vcis9niKT9HeDRwyTeIyx0nQNYfDAoGnM10f3f/S4R7Z/zfs++PvsmvNrw9z4PWQMZHFoKA4NmZIIKR8YumL+WkqQBcgcohA16MGwC6M+ajhAjYcwHiLHIwgmj/j6sW2E56PVfIRzAuE6aPOC7sI0EbqgLGcGVOUZ5B1UsY/KcxgUqE6OKnJUVlCkGTLNkGmOynNUUUCRz41agfZQj+MjRQiEYYBhoAyLSfkEveoFupWLTO1l5NGWp1LYxZhSvIMf3ECEO0RpSiRhIHS6QkNqGppQSEMjsw1i3yVzLDLbpDAMHMugZtvUHZuGa9N0HZZcm5JlgWFQEJGrCZkck8kRmRySFgOyYkAiewQqYKQLRrpgoAl2zCo7RpO2sBkpSSxDRNFGU3dn9yyhPC/AZkvFipQsGTZLeommvkxLLFEvVmlEJ/CGKxgjc9YZAww0bGXi6RZaSYPS/VMqAmKGWkzbznmzkXPVc9gtCvazgn6QIyYCkR2NFFLg5OjlNg1rj03usZW32SgknuEBLlnmkk43GQzPM3g4b4WUD4x+lqLnAWYu0QsDIX10WUJTNTSthtAqWDl4yRA77iGKPpm2S2gGDEqKnWaJ2+un2F86zX7jKWLXpTHssdrfZ2O0x4V4m+8pXqXc+3dcHwz5VVvnbd9k3xLYmc7ZcYNLLPG0OMNG3qCS1XDSGqZsYsg6Ag1iIAaFBG2IIfqY6i00rY8UIV1sbosau7JEngzJJ3vE0wNUkSE0A7O0gtM4heW/QEcTlB/Tc/sg+LYWh1pF8SPfPzNUM0M2N2b3Xxc55PmD10Uxa/Ud3f8995kZudk558fkBerQYM5fFznM9z++z/y8xez/ZNlsLd/bWKr3eP2BoWmg62i6DkUO4RSVRhCaSF1H6DoYBkLXD42q0HWU0MilRlbYZLkiSyFJFWmmUBRILUe5GULPUVpGUSTkRYoSoIRACTC9Ek61ilur49XqePUGXrOJV2ugWeaDa8+viT5/begwvx9hGA9e39/HvP/6wT5C14lTxcGtCffeHXD37R7Dg5CjOqWAzNHYcxWvFyk3RE4mTOAUjnGaii0Rek7k6QyWauRVB+UaoAlWZc4F3+Vis8pF3+WCZ3PO1XFljzjeObJs04t3uRndox3sMcwzRoVgfH+RJhNpMSlgkAsi6R7/vGSEyg5QWg0PixOFzgnqXNI0zpkVmuY6DbFFNTmNMVolGQjCSUAuZ8bGQMfGxOB4K3yq5QzNnAM9JZA94nzMRETcMwWvlRrcshqMCx8xLRB7IUIGWBR4ImVTJPgip2SEtIwOy1oPG5DKg8n9MaRVYJWUmZtJy1LIMkQeYuVDRJai5RKtMNFkCY0amtZC6FWEVsXOBW4ywo57KDkg19qE9m2Gbs5+xeXO2hlubj1Du/E8uTEzgc1hn6X+Ac3hAUuDfc7feZMl4x7POLd5yRjRJOfLdonfcE/xK/oGXvFpNtJl/ux0lY29JepFGVPZx4ISFJKcmJSEsZYQ6vcIRMZUpExEwkSlpEKSiZyUnAwHsNHDCcb4OsZkgFbkKE0jL9XIK3Vyv4qmaZhoGCLEUgZW+vhouG+Uj82tJITYAv4Fs2+CBP6xUurvCiEawL8CTgG3gT+tlBq813ngyd1K0RtvcPtP/emv+7hDzJlRetgYYugIY/4344ihOmY87782HrOPPt9uHHn98P76THjCkGI6RU4mFJMxcjymGI4ohkOK0egRMdFKJYxWaxbfv7yMsbqCsbKCubqGubaK3lpCc+wjBlZ/YFTfJxpHKUU4SueDwvdDQwP6uwHhqI8sBig5ADVEN8aoYkAa9Tlqcd1y5fhcgPX5YPDKKqb9jVcGez8m/Zi960O23x2w/U6fYDAfyGaWX00CfU1y0yi4bUp2DUmpYlEqW0izILCgW3HIyzZYGgjB2mjA2SLlYtnn6a0mF+oZq1oXke0Tx7uMw7vsT+/SCfboxkNGBQ8Zf4NRIYge0yAwEHjKRmkVAnOFqbWGNOoorcqGVDyjwSumxSvC43RWRY5bpAOXfJAQBzGFKhAIDHTMh4x/JAq6VkHb1dj3De76BntGRpH0cKb7NMZdwsKiq3x2jCoTZSJyhSdnAuCJFE/PKGsRvkxwkBjiUTujFQlGPjP8KssR2YPWv8hz9MJCEzWEXkNoVYRWmRn/QsNNplhJD2SfQgwJjQkjr+Cg7rG9cpKbG8+xvX4KeWQ+RnM4YLXfpjke0JyMqccB1TzCsxSW51LJfJq5QamwsLAR+AhcLOXgKBuH43NSJJKAhIkWMRExUxEzFQ9eBySo+8+tZmJrKAMdHUPqaOhookBSoKIRctJGTTuQ5wgd/FVJeUNRPjnAKI3RtAI7qaPFK3Rlk7ajM3YT9pMN/vYf/R+e6Hv/TTnmIIRYA9aUUq8JIcrAq8AfA/4i0FdK/S0hxN8E6kqpv/F+53pScZBBQHzl6pHW41FjOH/9cIv0vnF/TMzyB4kqCvJu930TuMnx+PhBhoG5snIYy380rPN+yKfm+4+/4NeIlIpJL2KwF86EYB4i2tvtkQYdVDFAygGCIUKMyJM+Sj6YD2DY9vHZwPejgdbWcUvl97nyB4eSiu69Ke++2eH2233G21NI5nMbUAgEBYquJrltKUYNg2DJIiubjCzoWFD4s8LympSsd/a52LnOU3qHs/Wc5WWFVknoZQe0wwM6UY9BFjMuxAPjLwWhfFRsTQQtYbAkFStpQisOUXqVibXOvnOGW+VnueE/Ta5XQAg2iXlBZXwqNHhmaLPVV+jDhCzKkEoiEI8Y/xxF1yrYtxW7ns7dssktz2TH09h1NcYm2EXGU8MOmwd76P0JeQap0lECDCSeyGYLs9TYx99ghSZTjDzFyGNIM4p0Zvwf+PxzNFyEXp8b/vmiV7FygRuHmPkAUfQQxYBcmzJxcw4aPjurp7m5foG7q5uMveOt5koUsxSENKOIehxRiyJqUUglCTHyHAsTRxl42JSUQ1m5h2v3IeNfIAnmhj4UCZGIiUVKIHICkROiZu5fUWAIiSFyDAo0oRB6htBTlJlR6CnKilB2gLBCDCPA0iPEICe8ZzG965CHBkKXVE5OqZ8ZUz4xRTff2zYrBVJoFBiM0gZ/5od+8+v4BTzgm1IcHkYI8Xng78+X71FK7c0F5FeVUhff79hvxWglGQQPJnAdTeB2XwAODmYpko+gVasP4vrvh3auz0VgfR2j1frARKvIJMP2vKj8PDS0tzNksLdLkfaPiYCSA2T+YMatpulUV1YfmhW8QX19nVK9+YEVR/9aiLOCG/sT3n2rx871IfG9AHuU8/BYa4Fi6AjaDYODFZObTYNdR6A8HQ3JkupyYXyFzcGbVLK7GGJA7uUEVsFAZIykOjT+jzP6hhA0DIclzWZJaaymOcvxlKVpn6U8ZSkvWCoKJtYKX1n5Dr5cf4Ev++d43VgiVDqNVHE+UnxqCk+PCrbGOfVpjiHVLLT1iB9eouibkgMbdlzB3ZLJ3ZLJjivYdTW6tsApck6pnE2ZUIsHlIe70BuQBxJVaBgobPFo6KlSEl0lmEWEmScYWYZMcrKkmBn/LEUU+exuhIvQaofunsOWfy5wkwRDDoAhhT4h1xISW2NYKbO/fIJbq5vs1er0PZfpQ71GN42pRlOqYUA1DqiGU6pRQDOKaOQmFelSUS4V5VBWDiVsPOVgYR9/FnJybURkDuhbA/bdHn33gKnTobACLE1SUy4lZWBoGZqeoRkJmhmjGfFs/Zjw3MeRSYO0sIj3XcY3faZ3HYpQBw2cDWidCqmf2UN3UpA6hOuM8w0ODI/Y61PSBlSSEU4SkhYWqeaQmw65Y5B2q/yVP/MzX9N9PMw3vTgIIU4BXwCeBe4qpWpH/jZQStUfc8xPAD8BcOLEiZfuzLNKfjOgpCTvdI/E9R+fzZvv7s5cPkfRdcyVlVls/9r6YTqH+61+Y23tkVTJHwRplB8a/5kATOje22XS2Zu5gu67gxgi88mxY0v1Jo2NjeMCsLZOZWkF3fhoh7MGRzKG3twZ07k9IduPqE0LlgsN/aFBzEJAv6Jza1nnympB2tymrO5SKXap5QcYaYc8HxOqlAmKsRQEjzH6OoK65dAwfZYMlxVhs5oLVuKI5XDI0miPpXBETcoHcShuA+onGTYu8pXa87zmnuatpEF7auCFio1IsRlJLkwkm4GklkkMdfzaI0Oybyt2XJ27JYN7ns6up7HjCEZ6RiWL2MwT1mTKajLCm3aRwZAiTskzHdSjn0+hQJM5joxx8wA7D9GymDQpSGIFaQ6yOPJOWkcM//2WfwUr1/CSDF2NQPQRdhe91EXUhgzKLve8S1zxn6btLjF2fUZuicA+Pl7iJzHNIGBpOqYVjFiKhmzEU06nkhYepnDQlI4pLSzp48oapjreK5YiI3V6ZE6P3OmSe20yr0vmdsmcHoU9gse4uwCk1Mhzm6ywZka9sIkKmzB3mOYuQeES4xIJl0j3iHWPRPfILJ/Y8hhZPrFyaPbGnLt9m7Xd2/j9NmYaIzWNbGWZ7FSV7hmDwHAoEhtiD5UoVJ5hZBKjKDCLAlvlODLFkQmuSvCKGE/GeCrGkxHvWif5r//GP3qvn8b78k0tDkKIEvBrwP9NKfUzQojh1yIOR/moew4yDMn29w9dPjODf8Tlc3AA2fGUwFq5/KDF/xiXj7G8/KG5qpRSRJNsPkEsoLcX0L2zT393h3DcPhQAJQeoYgQ88HFbrk9jY5PG+nEBqK+uYzof7jjAwxRSsTOIDjOF3uhMuX4w4WA/pDQp2Mw1tnKNhpyZYYVCioLYCBg7fXZadxk2dkjdA3KjRy4jgiIneMwYv4aigqCu27TcGkulFqtGmVVls54pVsIJS+M29cE22niHYyEAug21E1A/BfWTUD9F6J/knfEqNwcO/WFOFmSUYsl6NFtqx78uRJpi35m3/H2DHU9n14GemTAhpZyFLKcRa+mUVjzBTELyOCbLZvUhjqFAR82MjEqwiwAnD9CzAJnGhIkgjhRF/rD46ceM/v3XVqHhpBm6nKIYU2hTCiNB96fYqz3iM9Ber3CgrbMjN9mRG3TECmOjduzslXTEWrzPWrLHWr7LiuqzUSRsplAtaphZAyOpY8ZNzKiFnh9vHEktOTT0udslsQck1pDEnFBoY3RtiKemuHLCCMFdzea6ZtPRChIlyNMyeXySKDrDJD7FQFUZ4xFjk1s2yjHA1hCmhq4LPC3BUTFOMVv8PMTLIrw8xisi/CKaGe48xAmm6L2AfJRSpCCEoupnrJVDTpRGVPUIlwSfGFccTyfye5EqnQibEIdYWLxhfYIf+W9++us6x32+aUNZxaw+4f8C/Eul1P1+0YEQYu2IW6n9Ud6TkpK8233fBG7FcHj8IE2bDequr+O+8AKVo/l85j0Avfzh+9OVVEz68WFPoHOnQ+fuPYYHu6RR94gIDEE9sEa6YVFdXqW1+RSNjc1js4PdcuW9L/ghEaUFN7uzojH36wjfaE+51Q1IM8lSodhUOafQ+HRi4+YmoJNrKX13lzfKt9mpXmG7eoVCfyhvP4qKgmouaKWSWiipT6CZ2Wz4K5xorHOqsULLKDBGd2FwG26/CUfcZgCU12bG/9R3Qv0UqnqKXN8knTZJeiaddsionSDv5HiJpJEqVkhYYTbQnQro2NC2BV+qa4z0nCkBCRF5HmDkIXYeY0QJKsxoqYL642LQ1GxgVJLhEeHKELeY4mQBZhqSpgnj2CRMbPJCIwMyYDp/N462+g2nitDKWIWOk+XoMkAXQzSjj3CvQ3WCqkYMWy53aw0iu8zUrtIxNmlrKxywSk8sHbu9ijZiRdvjE3yZ1bzHRhqyFWacCDRq0wpm1MKMVjCSp9GL472HQqQk2oCpGDAVV5g4GWNDZ6CV6Io6I80mEjVGaolxrGEWber5PiUGgGQkdEI0hJI4RYEnc9yioCGzmRG/3wpX1/Hkm/gqwlMJrpr/jQSXGJ8ETzxUo+Phj0FBJ/G5Om5xZbzEMHMpUKz5U9abU5rVBGVopJiMVZl2sUQkHRKhEwlFrEGqGeS6Tq7rJAKmJCRCITEwDY+GtcyydKjnCV48wE67eLLPhlN933t7Uj42cRAzx/M/A95RSv3tI3/6t8BfAP7WfP35D+sest1dhv/mfzkc4M329sj39lAPt/p9f+bTX1/Dff55zPWN4y6f5eXZIPZHRFFIRu2IwX5Ad3vAwc1ters7THv7FOnRyKCjmTc1/PoSjfUtWif+wDEBKDea8xnCHx1KKXpBOi8aM6scdr0z5npvj4OgDcYYzZjgGmPOCJNTcYWX8xWa002suRGZWkPuVa+wX7nJXukmqT2krAsqpmTV13nOWWZFejSHgtrtCfV3dljuRXgix1svYa/7WKUCXQwRchcmt2AC3AGs8sz4N8/BuR9A1U5R2CfJslXSnkuyH5P2IortlCKVGMX9+dezKm8eCkRBoCX0RMQNI2AiAqYiIiAiETmFkqhYwRG7o88XgJzZoKhBjq8SyoSU5QQvH+NmE0QaMM4U/aRMmDhkucaU+4YfwAZRPxzo1c0qQpSxpI5dSAwVopt9NLeHUXkbp9XFW+kjljISx6TNCrusccAq+5xln3UOWKVPE3UkrUVZjVjJ93k6uMrq4KusjRVrocZ6YlEvKriqhi8/gaWOz0hOhWSkF+zrCSN7wljbY6pNiMSYRBuhM8FRycxgy5kLpSYTNor4iAGP8ZitXVK093ATPY5caYRi1gIPxawVHmsWibCYaC6ZpiGFQDGb0FpIQZZrZBlkiUaW6ARZiaywyaPZwDtAuW5z6uyU0jO3MJyCcVThzXCNrjiB5p9kqb5Mo9pgGk/pDDrsd/fp9A5oTTNOZjqrcUFTJVTUmAoTqkyoMKFM+MgzJJQYi1Nf8zN/PXyc0UrfCfw68AYP/Bj/DfBF4KeBE8Bd4E8ppfrvd64ndSvF777LrR/7ExjLy49J3nb//+sfSav/cWRJMXMD7U7Yv36Pzt1tRge7hMMD5HxAGHl8HMD2a1SX12md2GTpxNahK6i6/NGPAwDkheROf8rruzu8dXCP6/0dtscHdMI2CUNMc4BhDRHGlFyLcDKf1clpVsdnWJ2cYSnYQp/7xyd2l7E1IDYDpBHiVVNWVxwunl7i+TOn8XMH8fpbyDe/RLH9JmK8jemlmL5A9x0kLjEVEkpElEmcdWJzidSoEWs+mXShsCEz0RMNs9CwCgNHmXjKeiTePyChK8b0tCkjETAREaFIiUVGzpGBykeGKmZ5cgyRY+sJvhZQ1sZUtSFlOcRNQ8wwJox1DlKPflwhTB3yXHtkPiLCPjbYK7QKltQxiwJLROjmEMPp4pS7lOsH+I0BacVkqlfo0+COvsWOsc6+vsxAq9PVGgz0GpluHcsp5MqAVfZZF/dYZY/lZMrqwOH0wQrr3XOUiioGx42/JEKJHkJ0MEQbiz0csYulHWCIAwTTR9IWPUyhxMx44xBiEwuLDAOJhgRCoTPSdLq6zlRIIk0xNcpMrRUm9iZTZx1pCEwjxrZiPHNK2RhR0keU5AgvSfDCDBWY5BOdbKSRjRTZpCALTGR+XwRn4ytKr2B4LpIJedhGS2cNMK9h0jw3pHppB8Mt0KxT+OXvomx/jjCosLP9JtPdq2jjfbxkhK8CSoSUCPEIcYkRQIE+fzaNVFkkokam1ymsFsJrIfwlVKmFrDSg0kAaJo1Gg3Pnzr3/G/kefFOPOXwQPKk43J9UJszH5Fj5CImnGb29KfvXdzm4eZfezj0m3X2S8L4raMjRcQDddCk312isr7N86gStuQjUVtewHPc9r/NBI5VkEA/oRB22R3u809nlRn+HnckBnajDJOuRMQB9+tiBP18o1rImm5MzLI3PUB6dxQpWgdkEIqnnGIWBpSkst6C+olGvKFxziihGJJMxcRCQZjmpglQYJOikCFIhyIAURSoKMgok8jBssaLcY2GMZeXiHDFuOQUjEdLXxgz1KWM9JNAiIi0jISOTClUIHrb8QhSYRoRlRdh2gG8ElLUJFTGlJidUsyl2kJBODXqhw17m048qRKlLnuk8+ns0Hhh+vYIQFUxpYEiJRo40EjIrInUyEl+RlCHxTIRSmKpAIIlMl8DyGNslxk6FgV2l4zbo27VjPYBqNuFE2ONk0meFPnX7HlX/Giv6NqUiwes/jd99nlLnE5jxEoIphjhAF22U6JEzIBMjUjEmEVNyARk2uXJIlUFaSOI8J84yQmXT06r0tBpto0mseeSaTmZZFLYNToXUrSItk0vFm3wqusx3jr+EUfT4gufyC6UmX7UFuZAITHx9gyVthQ2tzBI5vgyw8wI7KyDVyGODItIpIo0iERSJRBXMnl/MP0dhgmajNAOpa0hDQ5kamimw0xit30eM+2jJTBDMBjTODWldbGO4BZPxMv3uJoPuOnFSYp705HhalQ+BlZPn+Kt/6c8/0bELcfgmQCnFdJBwcLvN7pU7dO7cZXiwSzA8mM0FKAbMvMEzhGbgVZepLq3ROrHFypmTNDdndYPdcuVDDQeVSjJMhnTCDp2oQyfs0A7bdKIO98YH7Ez26cVdpvkAxaOhfC46VU2jhkZFWVSkS1l6lLISzuQkxvgEIlhCxhUo5gZZFGAGKHNKbo7JrDGZyMnIUV/Dowql8DRJTbeo6S5VzcOXDq50cXIHO/Ow8plwpuSEImEiQkbmgIkxJtCms1h2JEmhkRWPNhh0PcWyQ2wrxLZDbCPE1hI8FeEXIdUioBqHGIEkCwS9zGAv9RlENeLEJc8N1CMT2sTc+D9o+d83/iYZppjgGgMqZpdlu03T36dsh/gixhCzc6XC4K6zxk13k1vuJrfcDW65m9x0N9lxlo/lGSpnIVvhiM0wZDOUbAUaW6HJqt7HqH+V6dJXSSqzyD89qmF1L1D0ThCOWkylIlAFkwKGoiDSBDo2JaVRQkPXZi6YAkmqUlIZk6mMghypGSjdRGk6UtNQ3M8NpdBQaEfskE/IeW5xgZuc4g7XbMGveB6/7Fa4PY9G9TKPtXCN1WiVpXgJXT2BAVbzKY4aaLqGrusYhoEugLyAaYga9mHcRUtmLh2zoWie79M838dwC9JhlbxbpehVEZl+2O6XykAKkwILZTjoTgWnvIxXW8WotdCrdXTDQNd1NE07XI7+//5rqQQ7o5hbvYgb3ZDrnYBrnYBJLJEIvuviMv/kL/2Br//5+SYekP79iCwk/d0x9969xf6NO/R2dph094gnHYq8f2wcAAS216Cxvkp97QVWTp9g9exJGhsblButD3wcQCnFKBnRjtqHBr8bdWkHbdrBAe2gTSfq0kt75OrRfC1OYeNLl3LucqKo4BUruLmHm3vYuYtV2Oi5hUQhhQKpYWaV2ZJWMbIymjJQQK7F5FYPygM0d4Bpj7GNFNuIcfQIywgx9QTDyNC1DEGMkAm6tDFkHZMlTNnCSBuYcR0zamLEDWIlCURCKBKmImLfHDDRp0ydhJCcuJgVbj9GMfPv54ZNpgsKWyCQ+DKgLke05IAV2WNZDqlHE5xpTJAqdgqHvcSjHdVJ4iZ5vjxPDPhQg0v4M8NvVNBEBVMZWFLiiJiSmFA12yyb77Lq7GN5QzLLIBYWCSYpBhkGkbC45Szza+7T3HPX2HVX2HOX2HeX6DvVYz0AN0tYm0w500n4vskepwODE7nLiVibR0WVKAyNYe01RktfJb3wDiN7ilKCZLzK8OanaPdXGYZl5GHrN0ZqAgOBpQkcdDx0NGbJCmOZUhQJWZGQy4TCsIgdj8ApETgeiWEi5z58KWZrXeTYIsYh4kx+lxfjd3kmukk17fJbnsv/2/P5DW+NiTbreC7HFT6532Kt3aI6NRF5gpAjUMPDRIQoA6H5oHtgu+iVEm6rTmNzhc2zJzixtYFvuUwmE8ajEcHubZLddzA6Y0pBGRGWuRl0uRtcJUuGCMCqS1ov9KidG+K4GfV+QXnbxhzUGBU+HV1jx5wwbFYQq6donfkET6+9yKXGJSz9+MS634tRlPHO3pi3d8e8tTvm7b0x19sTsnndD9vUWGv5NM+UKZcM2rbAPdn4uq7xtbLoOTwhaZxy79277F69Tef2NsODHYJBexYVJI/PXNbN8qwXsLxGa3OT1fOnWD1zgtrqGvrjygJ+DSilUJlERjnRJKA7arM73GN/us9B2KabdOlmPQbFgIEaMWLMREwpHjOxySosnMKZLbmDW7iPvi4cDEDXcyy9wNZzTKNA13N0QyKMHKQJUQOmLYrJMtl0CZQOKKzSAXbjNm7zBt7SFezKwSyt9hyJRoxNllfRojW0aBkzXMIKl7DDBl5YwkhNUpUTiIRgPmt1LCImWkRIQiryx8TzKCxSHGI8QkoqoMKUOkNaDGnRpy6mGEd6QKnUuJO7bBc++7HPOKyTxh5FbswLBD3U+j/0+x9p+SvQhAQtp9ATCjMndTKkn9IyxmyILi0xpM6EuhhRIqQQOtvOKjfcLd50z/Oue5rb7ga77jI9p4Y8JgAZa0HE5jTjdCA4E1uciARboaKazYJZi3RMlI4Yy4g9FHcqAfHmbZqr77JVv4EuCgLpcCVyuBKmvBOaTMKTePJZWuJZlkKPk/0RFyKNp/Q6LdNHCEGhJL3kgHZ0g3Z8l256QLu+zJXTF9heP83+8iZKhxZdmvOlRZcGXepySCULqUQxK/0JK8MJG2GPvp7xBdflP7kV3nB1pAAr1dnsuGy2HTY6DnY+7x0If+ZicyuY5Sp+q0Vzc4Otc+dY2VhGmRnT6YTJwT3i3RvI/m3EdA8jaeMWfapqQln5mPI8mXyefnqaG8EtbgZvEiez4U2zXtA636d+bojlQRzWeWMCv5yk7BsZFavCc63neG7pudm69Rx1530j7h/5/e4MI96eC8D99b3Bg8Zj1bdoNl30isXU19izIHZ1EAJDwHnP4emSy/c2yvzJ1ScTiCdyKwkh/hTwv2HWDPpXSqn/3xNd/SPggxaHWU0DSVEU9PfabL9zk/2b2/T395j228RBjyKfzJoz9/2VuoXp1nHLdUqNJpWVFvW1ZcqtOkI3kFLOzpnlqKSgiHLyOCOPU/IkJ5+nGCiynDwvKIqcvCgIZchIHzMSE8bGlEALZkVU9IDQCAn1iFiPkdqjwfpmYeJKG7ew8ZVJWVmUMagInaomqGlQMySOkaGbKZqeIrQcoeeztZaDlqNpBZqeIzRJhkmCQ6Qc4ukacecsaecUdDcwgllInRQFcXlE5I+I3RGZM0IjwSxynLygnls0c4tqMXM32YUHyiHDJhazgd77rf9ARIQiJnqMqJkqoyImVJhSZkrlcJlgqxhbxFjkyPn8YU1ITJWDytmRJtuFz0FQYhLWyRIfmd03/g9fyzjm89ex0JRGIQSBsOnpDvuGx47rYLgTntLv8pR2hxfFDS5o29SZooSYORwE3HNWD90+V91TXHNPcsvdoOM0jgtAXrAepJwIJKdDnROR4kQg2QoVtUyh4hFF1CPMhgxUxJ6Q3NB9XrfqvO5ViA242LjO8623eW7pLVa8LgDbaos30yZXJjvsx4ol50Wq9ktoyTlqHcVTQ8XLE8W6stCEQB6Kwc25GLTp1ersnl0hXXexlnIaeo+G7FPOQvw4wIoVWeKSJD5J7JPELtYk43S2zQXtNlvmHq97Br/quvyK67Nvz567PjbZbHtsdZdYDtew/QalxhLNtVmARXm1huZCEvaJdm+Qt2/B5B56fICTdSnzIMLnaE3nQtWIihcJ1StkxXMEuc7d4F1uhK8zjWcRZma9oHm+T/3siLwk+WooeD3SuZVanKtf4rnWczy/9DzPtZ7jZOXk1+zazQrJ9fb0SG9gxNu7Y8bxrHcugKWGS6luk5dM+q5G1xFgz8RwyTJ42nd5ujQTg6dLLuc9m+Hd27z2C5+nvrbBp//4k+WIe1JxuAx8av7fLymlXnqiq38EPKk47O3t8ZM/+ZMURUGR5xSFRD4uRbQCE32WpEzp8wRaGrN/4pH0BbMOrkIiKcTMB1tQkImCnIKEnEzLiIyZYY/1eP46Ijbmix4T6QmFePR+bKVRFgZloVHRBFVdUTUkVb2gauaUjRzbMEG3Dg35tPAJihJh7pFlNkVmoHIdMoHINbQc9EJhFBIzz7GLDFemhzMznSJFT2uodIU02SDITpDJ2RwIS0xYNa+wYb3FmvkuTXOIokUmV5ioVUYsM6bGBJ+JMAhI54Y/JhAJ2eMMPzmWSDBEhCYSdJGgyQiRR1hxQDWZUEsDPF1Dd210V8eyJWUtpJT12JM625lHd1omCGukSQmVmbMaGzw04wwNoZXnLf8yurLQ0RAaFLpgpFncNmu8ZS+zZzsoTdBgzFPaXS6IbZ7TbnNB32NN9LBFiqBg32pxx10/HAe47p3gpnuSXbtJoT3wj7t5wWZQcCqErVBxIpRshTMBqI4GEPaQYZckHdAhYEcvuG44vG0ucbO0Sset4ylBNUupJVM8q8fyqXucXL3B080rOEZKKk3e4lm+Kp7n7SAkHL9LoZ9Gc17gYnaRP9CWfOdewlauH4pBPzngIL5FJ7pLL91HVkGdKfCWcnw7QWYOSeLNjH/iE8Y2kzxHZjFGIjFjiZVkbNDngr3HWb+N6Uf8puvxq3aJVz2HRBMYhc5WuMoleZFnvRdYb21h+AYiPED2t1HjXbSoi5UOcNWEEiFlQjxiDoszzdcpPpmokRsNpLGEFOvkRQMZN9CzBlE+5W78FreitxlNZ9OnrFpO43yf+tkxhatxb9JgEp+mbr7AifJpTpS2WC+tY9z3wM8LPx0WgLq/lrNRlDgtaI9iDsYx7VFMe5zQnyZINevNmZrAd00MW6cwNUIdpKmhiVkyxYah0zQNmoZO0zCoGzquJu4bFaQs2N59m7eufYH9znUM3eT5l/4Q3/tf/dWvzeg9xJOKw18H7h/0plLqbz3R1T8CnlQcfvvnfoV3vvhlYP7ea2LuL4dCKHIhyZHzgdHisYZaiAJdz9CNWe4VZcTkRkxqxiR6QqQnhHpKINJZql6VM1E56WMcIKYQOJqJLWwsbCw1ywhpFzZu4eDmNl5u4RbMQhWLHLtIcWQ2N+LpbHq9mk+tPxIHfn82piMeNoyPJ5UOB9kF7qXPsJs9TSc7R6FmM6JLRp+62cWyQoRekAuDVFikaMRCEYqEcN76l49EKSksTaIZKdIIKVSIlifoSYIVZNjTlEYQsZYnNFVKTUvxzBTTSdH8DOFnTM2Ee8JhO3XpTyqEYZ0sKaFyCwo1N/7v4ffXKhhYmGjYQlHSCgxDZ2BbXHWqvG42uC5qpPMIEx3JKTHlrDbhBWOHZ4y7nND38dWQrmWwZ/ncdle56W5x0z3NLfcE95wGuXa0BzAz+icCyWYoZwIQFKwNhzT6HQi7yLCHCnuM1ZihkTGybKS3jumcRZY30MwyuhDossCQOZrKEUikrZM2dqH1JnrzdfTKrFaDjOvI4XPI8Uuo0SX0LEdTCk+6VHKBn4GpZvVClFIUqqBQGYXKkaqY1RLRBGj6YdTNfTQFQs0bRWrWLLrfOBJCcPjv4brKHwNxEbAdXOFO8A69+B4AVjWncaFP7cwE16xRO3iFysEr2JOTxxp5HyYFwP0gKXG/bgszT4SYre87JRCCTKbcGnyVK90vMU37eGaFC8uf4tzSJ6k+s0HtR84+0X080YC0UurvCCF8ZgIyfa/9vpVxdMGgdQNdzzG1HMsosHWJaRaYeoFp5AhjVsg7NBR9FF2l6EkYFgVBnhHJnLhISUhJVPpYn74hNXxpUC4MVnKbS4VNM1cs5QXLecZakbGeJTSZzcr8vWZjPkyqdCLhEOEQYxPjkAibVJTp0iLDQWGjlIXAQpMWhrIxlY0lbUxs8qLMJGswyssMCotEU+hGijBSNC/B0XbItIRYSzgQCbdIH4nf15WGr2w8bJZVFV86eMrGP7K4GBgMMUQHXbTn6whdDND9DqrUpm0m3MPiSuwzmJaIgjWKuAwTEyTI+fSwY9z3+5tlTBxMLBwsKnqJptHEc8oMHZ+7hs4NUXCdghtIekdEpIngLIK/yJgXtXucEbvk7oidUs62a3PTPcmvuz/AbXeVe26N7FgPQLEVSs6NJd+7n7EZFKxOJiz3D2h197HGM+Mvgx553GNoxUzKNaalVXzvFM7yJfDXMA2HJlBn1kApBBQa5Lo2q22h6UizQNWuIOtfhcbrWNYEpQRqdJr81h8mnbxEkZxHISnJgNUkw08sTGkeikEmEyZFSCJD0iKiEIrIloSOpBASvdCwpYGRaWj5rJjOLLuunE0Ku9+oFBamqVNzYqrGGEf02TMEt02DO6ZOqM3Ckhu54mSecS6NWJbZrPrerMmNUpAJl0LzkEYZYVcx/CZ6uYVWbaLVlxB+CXTtcF5EVkwJDq4T73ZRHYExWUKXNgpJ4LS5nr3N7f4N4n5/1mKvZKw+M6R2doz0Klj2pzjV+hFO1j6NpmnvaZQRkCvF3X7ItfaUa+0pVztTrh5MGMb54ehTpWJjVSzikk7bEaQlE+nomEJw3ne4VHa5NHcLPVX2aFlfWyzQuNPmy7/487zxy79IEgasnb/I9/yR/z3nXvnshz5v6T3PLoQ4B6wopX7zoe3fBewqpW58qHf2EdCvjploObkMyWVEVkQkWkKSxrPWvpYz1QtGhiR+TCPIkZKlouB0UbA8z6q5VBQzo3/kta8UudKJhH3EgNszA06ZTNgc6A672BTYSGUjcUA5KOmiSRcTF0s4GJqNJiwkFlIzkehoQmGpFFfGODKiWkSY6v4PcFYprgAydCJMxkKnJxyGyiRAklCQmSmpdUCs3SUVj0YqmWo2GcxCp6oMmhL0PMdIY/w4oxJLypHETzN8JpjWFNOaYlgBhjXFsAMMOyS2Ig4sjR1hsBd6jCdl4qCFTEqIvAbyApL8PVw/JYRRxhIOFhqukDT0jGU7ou6N8Z0ulnOPtlbiXa3FVZr8hnS4nudsJxrF3AdtIFkxIl4QPZ5V+zStCOXC0C+x5zd4w1vh37kvse1+7yM9gK1QcmYi+e6DnGYwpjnusdrbpdm9h9/vYY1mbiAVDYkNRa9V4p3lVcbL6/SNDXZ4gevmCh2rxMjTCXyN3NFRro7uzoJspKOTWQ7yvvgoxRo7vFL8Di9mX+KsdRNdk4SZx9vDLd6MFW/aywxrP0ZcP0kjifjxmyF/ZlvHVz5KKQZpm3Z8h3Z0h168T2akpFUb5TexEh09iJG9CSo/3g5UWGDVUHYFw/doVXQabsqKuM1Kdo2G3KNvpPya5/JrnsNlxyEXgnIh+Y4o4rvCmJcjE486ubmMaG6gqicxl86gr55CXzuFtrLxe+YVy/OAwb0vMXn7OvntDOtgAyOpY7FF4g+4vfI2l8dfpb23zdJtE6HETBA+OaR6ZoJeXWFj7U9z4dyP47qb73mdSZzx7v6Et3ZGs4HivTFX96ekxUwGDF1Qa7hoGz5TV2Psa6iSyZ6hsWabPO27/NCRsYEzro35SE7z90cpxe7Vd3ntFz7Ptd/9LQAufPo7+OQf/lHWL1z6us71jfB+bqWfB/4bpdTrD21/GfjvlFJ/9CO4v6+JJ3Ur/bNf+gf8nZ1/+Mh2SyoaBdSloFoYVJRJRdmUhUtFK1HRPCq6i2MYoEuEniK0ACFGSNFDiQm6lYNRIHWBNCwwV4jVEoOozu64wu1hmZvDKt2oQT+ukSuThpbQUgH1bICZj7HMkEY5ouEnVO2ElhizkXU4Ge2xnrTRj0TNpJjsa6sMRYuJqDEQTcZUCZVDpCziQidS8lE3jwIXC0faWNLClDaatCnyDBl3MUY3qB28wepgRC1QmKbE9AtMr8CYr0VFoZcUlpsROJJdw2AXne7UZTSpkIRLiMRHZBZCCSQFkod7R/f9/hWEcNCFga0rWvqUdbtPtTzEq44w/DGpWxB5GWMLbiSnuB6c5/b0JDvhCrtxg6l8kJq5rBSn8pDzbp96OacomQy8Ent+lW2vxrbrHRMAJ1dsRbNsqM0wpRpMaU46LPXv0urcxO91qB/0MIIhqFnvZezp9Goug3qDbvUEV90LvFbaYqfWQLkGytURjsDwFTgauW2RGcfTRwslqdM/jO5Z4oBz6hrrxQ5VNcQ3Z3H29yZrvDE4xVuxZFe7x5L7A+w3vpeuV2YrKPiLt1J+eCcjSDqHYjCMDtDyDKVBoEmOzqdRQkNZVYRbpexZVKwUX59S0seUtDG+GM0HeEeUCRHzo7/i2Pya5/IF1+WWNYu4O5lbfFZs8LnSJ/jkxmex18+ir51EPEGCRikzRp2vMHz7LbIbU/S9FnawAUBmBezVbvHbxuu8MbhKo6NY77qHgtA4O6JyeoJe3mRl5Yd4+qk/i+etHv/aK8X+OJ5FCd2PGNobc6f3IEWF6xj4dZu0ZDJwBXnZRHkGjqFx0Z8LwHyg+KmSS8P8xlryRZ5z7Yu/yau/8Hn2r1/F9n2e//4f4oUf/CNUWsvf0Lnfiycdc3hTKfXse/ztDaXUcx/gPX5DPKk49CZ7/Ny7P8WSv8pSeZPl0jpNt4ElA5Jk90i5xt3ZksxeS3ncsGmah6EtkeU1xmGF9rjEvVGF2+M618Il9pPmfNAMdJlTy4bUsyHNfEDLHNPyA7ZKE1p2SF2bsFJ02YoP8OUsrC1DZ0KJXX2FjtZiLEoElAhViVB5hNIikfojoxiaEoduHUfZM8Nf6IhcQGaQyypJ4ZBIKE3v0RhdYTl+k1Z+E8eZoqoCKqCXFLabY5sxfVOxZxjsKoNBYDMZV8nDFiL20XIboTSkKihEwqMhn/58speH1F1S2yd3bYyKpN7ocdJ/h3XvDQpXEusWgWwQZ3WyqE5/vM698RY7cYv93GdPWvSEdjhBzlVw3pJslWIsH0Lfpuv57Hg+O55NdqT1ZhezHsBamNKIEkpJSDXs0uzfpHpwBbezTfNgwNLgQZptKaBbthjUXCaVMlGpSbu8wdvLZ7jR3KBXLyM8g9wxiU3n2LwDAF9NaNKbG/8OTXpU8xGVNMCPYpw4o1Aauj3FdYbUvAmmXpAWBu/2L/B67xzvJJKmNuX7ivOM/Zf5d5t1dj2dc5OCH7/S5albb9ON7jIM9tGSKVLFBJ5L4fjYTommb1J1UkpmgMcIjwElxvPcPcfDeQFyZZALFw3FRIv5Tc/mC57Hb3oeU6EwhcEra5/ic5uf43Mbn2OrsvV1/wbvo5RkMr7C8J0vE1/vIe6VcUanEEqn0FL2qzf4kvsWXzCukA/GPNNrUduTIMEsZ9TPjqicCpDOOs3WD/Dcs3+Oen0mJnkhudkNeGt3dCx0dBA+EMlKxUavWkw9jcA3kGUTbI0NxzrsBTxdcnjadznt2hhfZ2/g/YimE9745V/ky7/480x7Xepr67z4wz/CM9/9/R96xoMnFYfrSqnHJux4v799HDxxmdBoh53dn5oJQDQTgiRt84hRy3xUUiIPHJKJRW/isT8tsR022E7X2GeFgVmn0B60HNwiopVPWS/GnBBDNu0xW06XdWePutajlXdo5EMSLMaUGePTFQ32jCWGWpkJPnHhkhY2+WNy75tKnxt+B1/Z2ErHKDS03AFVosgd0lxDhQOyZEqu22SeT9nsU9ba1OUNSto2jt3FsSaUjSmGFrBv6OzrOgfSYDi1CCZVZNBEi8vohQ1Km0dhJSgecj8JB6FV0ISL0G0Su0S3ssTe0jI3NtfRKhPW7WucKHbYStqsTWO0cYM8bJGFTfKkRpSWOUhd9tDY1RUdXTLQFbqAFTTqjkHVFbi+JPV0+r7Nnmez6xqk+nEB2AxTNqKY5TShJBOsdIjTv423+1Wszh1WOgEbPUX1SD6zRBfs1Hz26zVG1TqyVENzPablMpHtsFNrcae5ynZ9mXBeg8BQ2WGL//5SK4ZU0il+EuElMSrTmOQmvVzSzgt6MifQYxremDPlgKf9gjVzZqz6cZWvdp7j9e5F9iOLz2LwY+EJlqjz81suP3nKou1onO2N+d6vXmbzymXsLMR3ciqrDuVygq+N8BlRnYd12hxPCy2VRkiFiDqJ1gR3Dad5llLVwcy2Ef0vc210jV9zXX6tUuMNYzZC0HKafG7ru/nc5uf47Npn8Uzv6/7d3ScMt+nf+F3Cd3dRd03c/lm0wkEh6ZRu80bpHX7NuUK7HPGJYJPVu4rsZhtVKMxSRu3MmMqpkNhYpVr5bp599sepLZ3gyv7k2NyBd/cnpPnsN63rAr9mU5RMxp426w2UTVxL59JD4aJP+Q61b7A38H70d+/x2i/8W976wi+TJwknnn2eT/7hP8aZF1/+yBJhPqk4/BTwn5VS/+Sh7X8Z+ENKqR//wO/0CXlScbj9u7/A9fFfowhs0olFMtVJJjrJxCQIPNrJErvpCj29xdBsMLDqjHT/MCGZUIolkXHCDDljDTljH7Bp7HCSG6wk97CSmBCXMSXGlBhSYUdv0RMVIuVSSHs+Sew4tjIoKffYYK4jNaw0wQkmuEFClhuMdJ+OvcTQrJMjKakOVXUD3+zhWQFlY0xZ71LSO3hGh8iIZi4f3aCXGgwDk3hSRQQN9KSMnjuzlpqQ5CJFPeL6meX50YWLpesYliArW3Radd46cZY3GmcZeDYIQSmPODEdsjmKWe9L1vs61tQhSwxCBBNN0tEUB7qkp0tyTVLRBE10Kq6B6ZkoTyf1BH3PZNfXuedqDwmAZCuM2IqnrGUhZRmTF1OS0T3k3jvUuvus9kds9FPWe+AcGcYYOzr3mhW2l5bZWV6nvXKSpFLDVpL1UQ+7mA02tisNOvUKYV1glANaokdd9qhkU8pJgBcHiCRlWhh0JXQKSacoGOvJYZhyw2+w4q2w4q+w7tY4YUxpFDsY8buoYoxSgtvjDV49eIHXu89SxB4/mNv8CVmnoVlMDfgX6xn/+kyJiW1xeucuP/y7/5Hv7/0m51a7rJQfKhcLRJRIRINEb5FoDcayTDe16VMiLDWpX3qOC09d4tTGMub2b8GV/0B07T/yxXzIFzyXL5QrHMyj855tPsvntj7H5zY/x1ONp9CeMAopTfv07/4Og7evoW6D1z2LkVbnn8c+75Tf4Xf9W0w3Hc41z7LV8SjevsfuG28ic4npzwTBP5kQimU041Poje+no63wzkHA27tjbh9xC9m2jlWziXyd0DdQlZlbaMuzD3sB93sEp1wb/SOoUKiU4u4bX+XVX/g5bn35MrphcOk7v4eX/vCPsnTy9Nd0fBpFhKMBwWhINBrhVipsPvVYJ8/vyZOKwwrws0DKrL4zzEJbLeCPK6X2n+huPgSeVBx237rKT/39f8DYW2FoN+gZZQ5w2StMpsURI6RLTvkBJ402p8Q2p4o7rMk2K9kQqUyGlGiLCn1RYkCVkBJSOgge/RHZSqckHcp4lNSDaB5PmjhRiDcZI4IeKuwiwy5F2KdrldhrbFE0mjieTsUYUtK7+PoBntmlonXwRI/ufZePZjCIDcaBRTYuo4UNjKSCUTiAPg/TTZHEHA/5nPn9dc3F0A0cS2KXU4xWTFq32fZPcM0+xW1ng7tek3CesNAsFKuDnOVeTm2QURpkqLggEIpAz2eD/kJR0gzqGKwKHd/W0XyD1DOYejoHnsZdT2PH00iOCIBVFJyIppyMeqwnQ2rJmFEesDftkrf3qU5HbI37bA6nbPYLVgagH3mkbtVmZ7nG9soq19fPc2vjEndXN5l6HuujHqf6u/z/2fvvKDmv9LwX/e0vVw5d1TmhIzIaiQRIguDkGXKSdGQ5yZaTZB/ZlnR1r++5tta5Xucc+9jXvutYkuVzZFmybF3LCpbk4QRyyJkhhwRJkAABNHJ3o3MO1ZVzfd+37x/VaDQCSRAAhxwSz1rfqqqvuqp2hX6fvd/9vs/TmVrBX6oToWO6iFAZw5/DZ6yjV7MUbElCuqy7sObaJJUKZbWCo9o0+hpp8jbT5GuqE8AGCVy/HhA+lsdPs7zwIkXnbRTPDEKRlGsal5LdnF19lEuJ3fhqFs9Iky8Ji1YUstV1xt1F/nRbkFcH+yibFodnz/ErU/+Zx9wrlJUINS2GY7ag+NsxGrqxmvtxY+3M1WB0dpaxsTFyubpqb3t7OwMDAwwODtJo1RBjL8DYCyzOnuBVQ+EVf4DTlkEFiVfz8Fjr4zzZ/iTH2o8R88Te9/8WgOMUWV18g+ULZ1FmJf61bZjFFgDKeoaJwAjXoglKXUF6u7ezIzAAk0lG3/gB08PDODUHzWvXCaGzSoEmkrntTNb2czYXZqG4RTU2YEBAJ+dVcAM6btDA49W2pIQ87PTV9waC2gcrhHcn2NUqV1/7IWefe5bE3AzeUJh9n3uafZ/7Et5giFI+RzGTpphJbwT9+mVxy3GdDOzazavAgUcf5yu/8o/vaVz3JbwnhPgUdftOgMtSypfuaRQfIO6VHF67cpWf+f3JzdsRLUe3tsQ2ZYk2kkRkDoMqFaGSE/Ucf1X6QN4hDyglphR4XYOg9BIkQAAP3o20j9fVMcslKKwji2u4xXVq5SRJUWHVdEn6wY6oqAGFoCaIU6TRTRGVSYLKGq6WYVHTWNZUltBIl3TyeQsn50MrRTAqAXTHg0TDEZKaUsOhyJ3y/qriRdd0dEuieQSKT0N6LBzFi+0GqMgYy55mFvxB5v0G82GNrP9G5Yw/a+NN19AzZUS2RLVQA6nRJFRaUGhCoRmBx1SRXo2iT2PVqzLvFcx6FebvSABpukurdJfmiJRWqRZzrNRsUoUSFMpE8xk6shnakkXakpKGLUrltgJLDT5mmuLMtrQz1drPbEsvC41NeKxiXb5BrtJYTBJOlDGTCuQNkAoIB9vKkDWTLJirLGhpinoZTbo0Vh2aXJdmT5imUDdNjXtpbj1IU6CdJm8TUSuKIhRy62kWx2ZYmZojubBIen0e1zNOoHmeUNs6mq9OPOmixaVkP6eWjnE13Y/PVfmM0PkiOp21LGulWVZLcyy6Od7avZPX9z1CVdM5lpjk5+0kj+/YjdE1iBKJ3tSdm8lkuHbtGqOjo0xNTWHbNoZh0Nvby+DgIH29Pfiz12D0u9hjz3MhNcYrXotXAyHGN77WzkAHT7bX00WHmg6hq+9f1sVxqlxb+B6rV05jzUE40Y0nsw2Bgq1UWAxNsBTP4fQ1sa1/kF2x3ehSZfrcGa689l2mzp2vE4KnTghWm6SgxFlNbONCpo9rTpx1EcAMmVT8GhWfhhusp4W6NtNBNzaKuzz1Du8PA45do5jNsD43y+Uffp/Jc6eplkp4AkHCza3opkkpm6G4cdwuyAhCUfCGwvUjGMIXCuMNR/AGQ3hD4c3b/mgD3uC9Gf48VGV9B3z/t3+V18ezoKlIVUMqJnVzulsgHQxX4nU0Aq5JSAYIiTB+xb+Z9jHQkJUCspjALq1TcPKkRYU1zWHRK8kEa2jeGj6jRIOSoc1N0OysE7cz+NwcOc3ZTPmsOSrpkkmpYCDzHoxCA1Y1gOZ4kOjUlOvBvwS3lnwKq75Brhpouo6q67iGSc3wUjWiQATNDaNWPFTLCllFshBWmG/QWI1qpCM6hYAGGxtuomQj0hXCKZu2dI2WgkuLK+jEphXQTJOS12DVqzHrE8x5lc1jKwHorkNnaZ2e4gLbytNsK07hK+VJl2HOVci6KlqpQjCdoSmRpiVRpm0dfFsyW0VTYT4eZKapiZmWLlZa2sm3BnBikoiaJOKk8Nl5PJUcRiVHrVwiXwhSK0YxSw0YTr1qJqtlyehJHJEhoGTpcLO0VtdoU8s0I2lq3E2k6zii5zh0PIKj6KzNLLE8Psfy9BxrS/Pks6tYdgq/WiCgV/D5MmixJDKWpxyxkWrdmS+V83F17RHeXDzGlXIcDTiKxnG7wrbSLKnSPIXcMt7COjmvxjcf+yyn9z6KVFS+YAn+p919bA/eYo/puiwtLTE6OsrY2BjLy/VFfDgcZnBwkIGBAbpaYmizr8Ho82TGX+R1N8crXi+v+3xkhEQTKgeaDvBk+3GOtx+nO9T9vv9/UqUUFxaeIz1xjtC8QmOyC39qEMU1cXFIhRZINhcwBrro3bOP5mC9YsiuVpkafptzP/wOCxcu4tZcNMuul5w2K5TVOMn1LqaKHUxaLYyGmqiFrPreQNBgV8B7296A/0ewGqiVyxuz+RTFTGZjNn/j+tajXLhza5iqG/jCEbyhLQF+6xEM4wvXr1s+/017D1JKUsUaC6kS86ki86kSC+kS/U1+/uqjXff0nh6Swzvg//g3/4z8egndActV8bgGATyERICICBNWQvikuWnyYrtVCrU0RTtD3s6ScwukKZJTi9hGBp+Ro0HP06jmaCRLhDx+UUChzIqusaSpm/n+bNGkXNAReQ+eYhRPNYjq1oN/VRWbwV9SvmXUOoriQ1EsVNVAFRaK8KHIIIIIVSNKRQ1QUAR5IckrG4eAvOaS9gnSIY1C2MAOmcigDqogXJO05Bw6khW2ZUr0FMt0VBwirkHV9LLiNZj1Ksx56wQw41OY9yhUtBsEoLkOraV1+kvT9Jam6SnN01Oax1etsKp5GDXDJIsSJ1XAn8jStJqjbd2mJQn6lkKZpN9gvjHEUnMD6ZYI5dYgdpOCGqjhd/Lo1Sx2JUXaLpFwHValzaqsUZWCxmIzbYV24uUYPsdT73iVLl5sOk3J/kCeHmUcPXUW7DIIBVr2UWl5gnmxm7msh5WFJWrp+boNo5LBr+bxqQV8So4AWUIih48CuYBGImqQaDDI++sbl05FJZvqYnHpcd5IDHFK6rjAdlfySDVJb24ckZ3DV0jipUzKLjPa0cmp41/mfPsAqhD8pZYo/6CriS7PjXLXarXKxMQEY2NjXLt2jXw+jxCCjo4OBgYGGBgYIG5UENdeQI48z8TCG7xiqrzqCzBsarhA1AzzRHt97+Cx1scIGHdvYlV1qowkR7iy/Cq5+XM0L+t0pnsJJXei1eoyKgVfgkJrEf/OPrbtG0L31sfvuJLxpRRn3niT5XMvImcnoeaiWjah7hxus0FFaSST7GDNjjEWaWO0rYuG5oY6EWzZKO6wHtxqQEpJuZC/LbAXN1M6mQ0iqN+2K3duTjV9PrzBMJ5gCKRLZm2VQiqJoml07t7HruOfobmnH28ohG553lGT6bo74vxG8K+TwMb1dP16sXpzRZnf1PiJ/W38b1//Ee45/DjhXsnhP/6LX+PzmRuSUa50KNXy5GSBDCVSokhalHBEAosFIiwTk1lCIk9AKeFTS/i0CvbGrH9JU1lSNJJlnVzBwC6oaHkPvlIUqxpCc704wqCqCWqKjS1KSFm4ZVQKQvhRRF122NU8OIofTTQglEYKapC8CgWFzeBfUBwKGuQUSR5JZaN1WWoCN2QggwZRn0KTodPkKHVT+6JLV75Ca8klVlXJ6SpzXmVz9j/pVZjxKix5FapbCEBxHeKlFNtK8+wsT9JfmqGnNE93aR7NlZz3N3NF8ZHIgEiViSQKtK0VaE+4xDLcVBq6GjVZbfSRafJRbvbhNBqUG1yqaopsLcP6RuBPuC4lCabjw1MOECgHCVQb8NWiBKohAraB5VZwjRpuXQSWJq+XvqYAA5Ec7dlTiJmTJEomk5Vu1tRtOIoHgwIekcOnZPEpOXwiS0hkCZK/qYcEoCZ1slqI9WiAbFwlHy7gaDWQArvchljcTnb5EV4qtPMyNiUg5trsLy2zc/0K3ckpGrwKOcVl1i5TNHTsoUd56+CnOGkEsBTBX2uN8T92xmkx6zLP6XSasbExxsbGmJqawnEcTNOkr6+PgYEB+np78KVHYey7VEaf53R2nFe8Hk74AixsTKR3RAY51lFfHeyO7b6rzWQpJXO5OS4kLnB19TTF1WF6kj62ZwdpSO/EKNZXADUzT6WtRHRXP9HdA2ghk2LVZmQ5V68Umk+yfPU80eXXaUovo9gS1XQIdOWptngpqs2UE82UHD/Zti78AzvY3tPNbr+XQZ+F7x5WA67jUMplKaTrQb2YzVBMb2zeZjP1oJ9OU8zWg7/r3N7wKYSCJxjcTOd4Q/XZvCd4PZUTxheK4Nm4z3VsLr38fc49/03SK0sEGuLs/+KX2fPpL2D5b6z6XFeSyFeY25jxb87+txBAuXbz7y7k0WkLe2iPeGiPeGmLXL/uoT3sJejR7svb5b7JQQjRBfRLKb8vhPAAmpQy916P+1HhXsnh1IvfYfKNGfzaCnE5R6M9R1gm8ZBBUwooVJA4JFWlvtGraaxIlUxJp1RUcYsqWs5LoNiAVQmh4sMRBmVdoara2JSpK4/c/IUL4UWIAIoSBCUMagiJi3QyuPYCuLeX07oIqopBRTGpbLmsKQaa6hLSDaxwI4Y/hmVG8YogUUentSRpKbmYLqwb19M+gms+wcRG/n/Nq1DTbgQN4bqESlk6yqsMlmfYUxxjsDTJttI8beU15o0gb/ibGK0FyedUPMki8bUC7YnSbaWhVU2wGjdIx03yjQalmEsyWmIqUmNZdUg5CnkXolaMJl8TcbMRo+DDXpBoqwaeXAif04qvFkVzDRS7iCKnsH1ZikGHglb/nAI+H+2NYbz5Vcy1eUQ5gyaqeNQi3o3AHxDZjbLOm1NxzvWyThGlpjQgva0YDdswG3uRTV5SnlmS5dNksmeQ0gHXh0j0E1neTz4xxIu2yXdllTUBpuuwOz/PY0vneEJLISMhJktZlipFhKLSvmMXtUeP861YFz/MVQioCn+rPc7PtceJagoLCwuMjY0xOjrK6mpdHC4ajW5uJnc2R1GnX4XR77Iy8QKvUuRVr5e3PF5KQuJRTR5tOcqTHU9yrO0Yzb6bm7/uhEwlw8XERS6uXeRy4iyV9CX2FxrZU9hOc3onVrYbgYKjVXFbSwS3txPY2Ufaq202j11ZzHJpMcvcWpaOyiyH7HM0p1cQNVAMh0BXgUJHmJLZRXUuiOvoBFvb2Dc0xON792C9S6OcXa2+Ywrn1k3bUj7H7V6qoGoa3tCNdM71w7clnVMP+mGsQABFeW9iyq6tcva73+LSSy9SKRZo6huk+zNfxejexWKmctOM/3oK6HpJ7XVEvDrtES/tEc9tJNAW8RC0bk9zSymplh3K2TLFtQyarhAfbHnP8d4J97sh/XPAzwNRKWWvEKIf+C0p5WfuaTQfAO5ZlfU//CNiC7/NsqaxqKksqRprrkq2qFMpalBQMHNeQsUoVjWMgp+aej34O9iiguvmuC3vj4Wi+BFKEKlEcLUQihJCU8IIJYAtVNZUh3ndZVpzmFUBXAy3hulWMN0KHrtEQzVN1MkQJUOTKmlQDQL48YoAiqcJw2ggqPiIOgaGrItlJDcIYMwHEz6XOctlyaOy4jOpbq3ZdiWeUpF4KUlPaZ5d5QkOlq6yqzRBW3kVFYdRI8QbnhamK36qWYlvvURTokjb+u2loQWPYC2mkoxL1mIu8w2SiahgJqgS8TbSfEtFT6O3kYAdRkxUyV0ukJgpUSzr2OqNVIdRSeMpLiK9BZxmKARhvVrG3XAPi5Cn2V2lS8zSxiJhkcPHVjOlOorST4kQJaLYWhx87XhbBwh27URr60FtbkdsdPk6ToV0+i0S6y+RSPyQcnkOAKXQgm9lL+HEIcqZbl6wyzxPhUnVQJEug5lZni5PcSwmSOuSkeV5CsU8qq7TtXc/fYePsty/h99ay/N6Ok9UV/n59jh/ORZgfXaG0dFRrl27RrFYRAhBZ2fn5v5BTCvC2Au4I89xaektXjE1XvX7GdHrAazN28yxjqc43nGcw82HMVXzts/gOmpOjdHUKBfWLnAxcZHLiQtQmuYxt5WDhe10ZHbiTQ+guAZSuMjGIkZfhEJbJ1eE5MpKfVVwcTFDMl+vmhHSpUfMcaB2lqa1ZUQFFN3B311G6W9B+vtZG9eplGyCwSD79u1j5/ZBLEVsCe43UjjFTGZLbj9NtXT7dwpgeDz1oL4Z7EN4Q5GNgH+dBOqEYHp99+2eaDsuy9ky5y+McPK1txifXSGrB7Cj7RTMMKtFZ9OU5zpifoO2jeDffkvwbw1ZGFJQylUorqYprmYoJ3OU0kXK2TLlXJVy0aFScalWBRVHpSZ1asK8qcmyTVvk67/5IdiECiGGqUt3vyWl3L9x7mPRIf3s7/19pr53knCxAasWRuCnqpmUDIWK6taDv8zf4t4G1+v9FREENYxUQ1SUIFktQE7zoyomja5KyK1/gWUhmVdd5jSXec2mInI0VDPEi2nCuSzBSomwohHxWQR9XjyeEKYZwSOCBKVFVGro11NFQMoQXA4pXAmqjPsVFixB0lLI6ILalk1gXIlaqhEsZmktrdJfmmF/aYSj5YvsrEyj4VADxhWLy7aPpbxJJa9i5iGcdWlNyttKQ1M+wXpQJeVXSXl1iiE/xaYwaixKIBghGGygIdRIPNpKS7Sd5mgHpsdHejrN0pkJ1sbXWF2ukK16sZX6bFFKG6O6gEeZx+dPY/mKlA2HNBprMkBJ1KvDYiTpY5pepuliAQObijQpEqLkhikTwdbiiGAn/o7tRHftR+/sQ/G9e6NWubLMeuJlEus/JJl8HdctgaNjrW8nlNiPL7GPUsHkheoaP1BUrhhBXKGwrbTGl30FjsQc0uUkEyOXqFXKGB4vPQcO0//IUbr2HeCVQo1fm1nhbLZIk6HxN2J+9ieXmb02xvT0NK7rYlkW/f399XRRzzY8ySsw9l1yo8/zRn6KV70eXvP5SSqgIBhqHOJ4x1M82fYkveHeOwY+KSXz+Xkurl3kYuIiFxIXGFm/SlSt8AgRHivvojsziC+5Ha1WJ2UnXCTXZDEbbuCU7XJ2Ncvoco7K9XSHAPw6jl+l153i0eRbNM4tQ0mi6A7BrgoN/a1gbWNy1iJbrCGAkAreUgGZSVDKpHFqd1YHtgLBenDfSNl4w+FNAri+UVu/HUI3378sx7uh5rgsZ8rM3ZTuKbGQLjKfLLGYKeHeEi5jXo3WiIcmn07cVIjgEKpVCFTL+MolZKlCuVSjWrGp1lxqrsR2BTUUHKEiN4QJEbJunSrczUukjZA1FGyEcEFxEYpEKNTzs2pdSbqrsZmf+nt/857e8/2Sw1tSykeFEOeklPuFEBpwVkq5955G8wHgXsnh9//1b7B25g24TXRWAeFHqkEcNQxKCH3jEEqIgmIyr0uSSl3DPeQIOhyFkKyTQVXYlLUkur6AqizilrKoZR+aHUVTwphWBI8ZIKR7aVAM4kLZDP5QJ4BJS3AprDAS1pj2KSx5BClDoayBszUQSIladlALFaKFFF3lRXaUJjlYHeFo5SLtbt3gpSgElw0/w0qMZEGDtIt/vUZ83aEtIYlu+QhsBVbDgkREJx/24YbCEIzi+kKo6Kg1CWUbu1SmWihQLhbuuJS/CUJHUVR0BQzVxlBtTLWCV63gU0ugqmSUMKtqIwk1hlQ0dMWhTU3QRoq4LKM7OjXHg4KGJxImuns3oSNfQIn1bTYm3g2kdMhmz5NIvExi9SXypREA1FKUwNoQvsQ+lLUuEsVlTtXynBQmF3xNlDSLBlnhS3GXwzEbe/EKs5cu4Do2vnCE3kOP0n/4KB2794Kq8e21NL8xs8LlfJkWTeELlQwtYxdJbaSLYrHY5mZyR2MYdfoVGP0u05Pf4xVR5lWvl7OWiS0gpPt5vP1Jjrcf5/G2xwmZt5cuZqtZLq1d4kKiviq4lLhEspwkoroc1AN8uraHrvQ2/OuDGKW6Vk/FrLIYElw0LL5bqHAxXdz8KlXVxbRqWEYNj1YhqlbYXZmmNTmGs1zAKSsomou/rYBquRQqYdJ2D44/DEKglPIY2SQhXHzB4G2VOddJwBMKY/oDGN56g6njOA/8cF2Xcs1hveSQKEnWy5JkGZIVQaoqSNdUcrZykzQ5SHyihp8KPlHBLyr4RXXjqOAVVbTbJOnvHYoQqEJBVZW6v7Sm1SsOVfVdj46ODo4ePXpPr3m/5PCvgDTw14F/CPwCcEVK+av3NJoPAPdKDn/0py9x9VvPkdMCpDQ/FS2MhxBNMkCTq6Ft/FDWFYclo0hJK+KjTGNVI2JHUN2NGakoo+lpHN2mouogfQQVD3Gh0YxCI2Lzua4jrcKST+FaVGc8qDDpE8yagoQmqF7Xdb8OKVGqNkrJRstXacqv0VuaY2/pGodqV9glZmiRyXpaSVEY0T2MOkHSOR0yEv+6S9O6vK00tGQIEk0mhdYISncHke17adyxn6bevYT9De+5DM8tp5k9eYW5y5MUU7PgJtFFGp0UmsyiuEUUt4JwHRwHKq5G2dGoOBpF16DgmNRcdcN3+Z0hkJiGguX1YgYjmKEYlteH6fdjen1YPj+mz4/p89XP+3yYPn/9vNeHZhjUalmSyVdZW/oBieQrOGRACjzpfnxr+zBWBkklbNbLq8wXMlwUFmcb+ln2RrGE5FNtJoeCeaxrJ1m+dhWkJNzUQt8jR+k7fJTW/kGEolBzJX+2kuQ3pleYLFdpcqoMTY/SuTCJLgRdXV2bhNCg5GHsu9RGnuPtldO8aum86qvLigP0hbZxvOPTPNn+JHvje9G2yLPU3BpjqbEbq4K1C0xnpwHwKpLjgSYer/bRmmzBSnSh59uQAsrCZkorM1IrMlHOkHdzdTVfUcNQqliyhuHWPUJU264HedNFMcCpqriOBiroPgfN0kENUXW9lN269LYiBF6PB6/Xi6brSHjPwP2gimJsKShIk7w0yG9cFrHIS4OcNChKna068wKJjxoBagSw8WPjxyUobfyyjM9ZQ7HXQToIEUAVMTR8aK6LhoMmJLoCuqpgGAqmqWF6TCy/iSfkwxv242kIYEXC6MFgPeC/Q4BXFGVTTr1oF8lVc+SrefK1fP36lsvr5/PVPLlajn3xffydPX/nnj6z+yUHAfwd4PMbn+wLwO/Ij1CZ072Sw//vxZc48VyONlsnZteXqC4uBT2Jo6+giiKKqyOdJiJ2jJBi4FWoi26pEksVBIWgAYG2JZC6UlJwKhRFlXRQYanZy1LMy7gF11SYUxTySl2ffxNSIlwJFQdRdNCzJToyC2wvTjNUGWMnMwyo87STwAEWNZVrislkxUsup6GkFEJJaNk4tpaG5oI6hdYwSncHDduHaN99BF//AFpj47sSgOM4ZDNpMjNjpM+fobw4jiivYMokXiWNnzQBkcW/oda5FSXpoUCYkhuk6ATI2QGWiLOiR0nqXoobndleQ6XPX6KreJmW7DkUx6GiBqlEd1IO9lPxtVNRApQLBSrFApVCnnKxQCWf37hduK1jdOMDxQxXCXblCXUV8DUV6s5uZY3qYiO1hRZKCxEqJYFbLaLk0qxpQS627WbUaqKqmOxoDbHPk6Nh6iSZ2QlAEOveRs+BR+gaOkioqWXTTrZUs/mz6QW+sZomJyWRYp6+lTk6ynlam5tpamoiFo2iZOdwlq+QXR1hspZjWjNY1E1sqaCj0expptnbQtyKYwhjM4AWq0Vy5RyFaoFStUTFriBcgbLxOAMVxVXq2leS27w2HhQEcsNHQGxa3wIYhoHX68Xj8bznTPf9HEiBU7apZUvk0yVWUmWWszYrRYdEBRKOYN1VSFH/n9oKRULAFYRcQXDjCLmCsO3QUC0Rtct4qGKoDobuYhhQUdZJ5CdJ5RdRFJWubTvZc/Q4bTu3Y8YiKIHAO+oeudKlUCtsBu2bgvsdzhVqhZsCfq5WP3dHN8qt70so+HQfAT2A3/BzvP04v3jgF+/t+7xXchB1K6cL76TO+lHBvZLDd775Pcafl6TUMllNAcWgRSh0SYUWFAKKwKsILMFNtdUSSVlWKJfS9S5npcBMRGemOcJMQ5DpgI8Vw0POMG+yhKw/WIIjoeygFG30dIltyRl25SfYIWYZFPMMKHN0iDVqQjKt6Uy4BnNFi2JOx0irRJLQti5vKw0txP04nS1Yvb1EBvcQ37Efq7cXNRi87b1LKSkWCmSXZ8hPjVJdGcdNz6HkF9Arq3jcNH4yBMXtZZ1VqVMgRNENUXIDFGw/hZpJvuohVfOT0RuwGluIdTZhWwqpUo65hQVs20ZVBJ0Bhz53gp7cW8RI4mp+nPZHcDqO4rQ9gtMwiCPffcZ5PSg7jkOtUqFSLlEpZalVLuHaF9B919A99YK6cjZCdrWF1FojmWQY97qRqwCpKPXNPSFAiDphX7/OjfN8kEJoAlRNRdd0NLVemmjLGlWnQtWpULMruI6NkBLVrYsu6i7ojoqFF68SwKcGMISOgkLVKVKsZcnWsiRlkZKqUTVMhNeLL+QnHAzSGArREY3SGKmndnRdY2nyJJNnX2VlZJFqXiCEQ6RLo+fgHnY//tOspxTOnz/P6OgoruvS0tLC0NAQe/bswet9930du+ZQThcpLKcpJTKU1vOUUgVK2TKVfJVy0SZTdlmxFdbQWBcaSVUlrQqyiiSrSIq3fAWKhJDjEnFcoo5NzK0RFw7NqkOLBc1eFV/Iwgp58TT48caCeJvC9SDvv9FgVqtWuHLiZc489w1S8/MYAT8tjx8i9OgOyqZ7U/DOV/O3Bfrr9xdqhfp+wbtAFSp+w49f9xMwAvh1P37DvxnoN8/f4ZxP9xEwAng1731vrl/H/a4c/gD4x1LK2Qcymg8A90oOV1+bRH57ngA3bA6hHjgrqsC2wNbLFKsJFitpxnSb0aifqYYwKb+fvOWhqFs3qbFueRJwJKJkoxRqWKkcfclp+krzDIgFBsQcA2KeLmWFgiKZ0nRmKyZLJS+1nIGZgoZ1h7YEBLfsh9d0hWJrGLra8fYN0LhjP+HB3Rjd3SiGsRk0K5UKqdVlslMjlJYnsFMLuIU1RC2JZueoL7jLKEgcFBxUHFRqUqOEj5L0UpZeKtKi4tT9IMqOQtHVKaJRU0wczUDzWPgCXsIhL5YmKBQKFItFyuUyjlNfvtT9cevWlsDma7l30J56vzCMAtHoAtGGBcLhJVTVwXFUMukW0uttpNbbqBY9KHYNw66iCIHj9ZPTfSQdhaoDmgJBUcMqpdCq9VWQ5fXi8QcwPR4EEqdaw7Vr2JUKlWKBarmMY9dQHZu6MbVESLnhKSwRG+eQLig2Zc2lrDnUVAfdMAlaQSJaEJ80KVUKFEt5KqUibqWGVpN3tKs0NR8xfw8N1jZajA7Car2GPuVWuCRznDVsToc10i1hujsbGWoJsSvgZZffQ5/XxLiF4BynyuSlb3H51eeYv7BIJasiFEl0m0nfI4fYe/yvUq55GB4e5sKFC+TzebxeLzv6d9Ab78BbUzeD/GZ1TcmhUnapVtmsrqkKE1ep6zZlNgJ9RpFkFHcj8NcvS7fIYGtSEhcOcVXSbArafDrtEYvupgC9XVFaO2LogQA2DoVq4fbZ+pZZ+61pmVwtRyWTIzZaoWNCxaoqJANVrmzLMtVSwLlDJauu6JtB+rbgvnH9jgF/y3VLtd45sEsJtRJUC1DNbVwWoJqHSv7m25uXeWgZgkd+7l7+fe6bHF4CDgOngM2OLSnlV+9pNB8A7pUcxt+aZvWPZigpDkWjwpyV42KoynREJxXwkfN4KGoeKqqJK7b8WjYCgSrduqev7aAXKxj5MoF0lrb8Mq2VBC0yRbOSIk6aiMiTUxQSQiddMyjaFrKqo5YFVgW8VQWBgqvUj5qhYXtMpNeL4vWhWj4wTFxVqc+WazXsaqVuyuM4OFLe5vX7IOFKcIWCoihoqoZpaJi6hpQS27apVqvUNipQBOBVqvjdulGMhyqqL4oabEINt6GGWlE0497SDBWbxNjrZJMncP1XcIOLQH0zWSz1UJxvIjuhEJm+Rsv6DK5HQz20F45+iZdC/Tw7mWdirYCuwB4jQ+fSaVrTE1iWybb9h+g/fIRt+w9jbsyEpZQkEonNZrSRpWUutPVyua2HqqrxiKzwt/UKA0tnYO4tUqkRrlJlRPGwIEw0W8FTUQnmdQJFDU9VRZF3/x1JBEIxMRUPPtXCUEyEYpLWLVY8FskGP562KB2xBrqjYXqjEZrDYSxffe9F1W6uk7ftMpOXv8HlV59n4eIKlYwGiiTUohFr7CaiHaKSt1isrrOqpClq5bohVDmEWWpCqzbeUVBSIqlIm4IsURA2Oc0lpwrSukJKVUkqKsVbHmepgtaATnPYIB4xiAQkIZ+N31PBtAqg5inYt6dnbg30ZedWFYHbYarmZvCO5SzaRyWhyTK4IHuiWEf6CfZ2EjSDd57ZG4GbS4SlrHfYVwtQuSWQV/PvENhvDfBbblc2br/HymMTQgEjAIYPdnwZnv7Xd/e4W5/mPsnh+J3OSylfuafRfAC4V3L4ndde5j8uFsl4fORNLxXduHGnlPgrJUKlPKFSYePIEywVCJYKaO+RF7wbKI6DkBIhQFXqFQq6aaIaZt3i064g7CrCLqO6FVS3jE5lw2S0ioaDgrs5D0cKHHQcadQP16BaU6jaUKq45Ks1aq6DwKjLbus+fKEw/rZWssEo12yLMys1FrNVXBRCXoOD3Q082hvjaG+c/kY/hUKeiYkJxsfHmZiYoLRRg95iFOirjdAnJ2hnBbV1L2w7BtuehI4jYPrf49O4M5xijaU3h1maeJGa5yLV2AiOkQNXQU22U1lsJzfuxX9xgbbVaaQmKe3oJHbsM4Se+AIv20H+/NwSb07W3aJ7tBzb1obpzY4R9nvoPfgo/Y8cpXP3PhRNpZzLkU2uM31tjOlrYyzNztQ7bnWT4Z2HOd+zC1vVODjxNn/lyp+yh0mysTxv+Q1e8d5wRYuVTXorrXTZjQRdizUyzDrLrIkMZdPBthRaG3YT14fQi20k1wWry1kaslUGXJttbo24W8N1K5TdEgmlQkGrIjUbza0iKiXsQuGOHb5bIYSKZqh4mgooao1SUqOSMUBIrIhE0RuoFnaCDGNbUPEXqXryICR61SCUD9BQ9uJVBDVTIefRyVgmaV0noWqsIlixYbUsKd0yFF1zCXireDwlTCOPaqZBS+Koa1TFEkV3jZq8037RzfBonttm49dTLLeev9NsPaD5UZ0ak6df58x3n2P+2ji6obPrwC4OHBokEtBumY1vubwtsG+5vNsYIBQw/PVAvnkEbr5tbr3tv+XvN66bW85r1vuq0HvHoT2Uz7gzfu2F3+PX2UGgmq8ftSxWtYBRqyBqgprjx65p+Ct5YtUUjbUkjaRoJklUSZJTHdYdQb4sqJZ0lDwEMjbxlEu4UF9VCLee3y43eJHtTXi7t+Fv6cA0dWqiiJtfgPwiWnkFy1nHJ9MEyKHf5sqlkidMUYQpyQglJ0C+6iVX0siUqqwXq+Sd6/9oyobjWghd9eG1AkQbY2w7MEjfpw+RdDVOTq7z5uQ6b00mWUjXA3zUZ3CkJ8qRngYe3dZAf6Mf13WYnZ3dIINxVlbqZZg+tUavO0WfHKeXWXxNfTfIoPMoeML39F06xRpLJ0dZvXQK27iIHR+lFL5Wr/GuenCWuyhMR7DeTNE+M4vAJtkVRn/0EL2f/QnChx7jjbkcf352nhcuLVO2XRoo0pe6zGB+lCYPRFs78EeiKKpal1fIpCmkU5Ry2dtKclPBKKf2P8mlgf10lxf527PP8VjuTcbUVV7zmLzm9ZBXFHQUtof6aQ114QrJVGaKifQEEomUghZzN03qAdxqL4lskMV1h3yhRgcKh1A5JHQOSJXA9Qo5tUJOr9VlVuwKTtmhvNEMVbUVqtKggoGjqiArSFkBWa5fuhUUI40nfhUhlygmFCpps04IIRshFKpZHcdxcXWTWjhGNdhASfeStzVKxSqliiSHRdYIktMC5FQ/9i2ilCplTJFBU9NoahpFTyGNFNJM4njWcfQiPsN7x6B9W3C/npbR/fhVE79UCAA+V6LbldvTLO8VuDfur5ZKXFr1ci7ZQrrmIaCV2R9dZE94BUu9E7GKmwOzeadAfctt853u37jUPQ8kkH8QuN+VQ44bax0D0IGClPL2Xc4PCfdKDhdWJ/h/n36OlNbPSsaLL7XOjswEA6UZBmuzDCizNGhLrGguC2WTdE6nkjMxMgrRdfe20tCqpVJoieA0RlDDfnweDcOsoOoZTHcdr5siQBbrFhMdVwoKIkCRCGUR2Qj+IfJli1RRkMgVSFfSt2x26Qg1jFDCCCWEJnz4TYvGpgjtO7fRdrifSE8cIWAuWeLNDTJ4c3KdxUx9Gd7gM+pEsEEI/Y312X0ymWR8fJzx8XGmpyap2Q4Kkk6xRJ+coJcZmhqiKD0bZND1BPga3vfnD+AUqyy9Pkri7CSuGMVtvEYxfoGap96fIdNxKvNNKGeKtJ9eQnMdluMGud29BPcepmn7Iaq2zdWlLC8turyZschKA9Mp01+YYHt+lObKym3JNs00sfwBpKZTcSWlmoOrahg+Hy2dXSj9O/hBuIX1pWG+kHydffm3uOQmecXr4YJpIgWEVA9NgXZs6bCYX6ynN2yNeHk720p78OYaUTIaaq6Gx3bxuhASGq1WgGbLT9z04FHr+1VFV7JWk6zZLmu2pLr1q5Yuul1Ed8sYVNFVG11zUHUHxXTBdJFeFzuUpuYZobS2RH5GUE5agEQ0O6x1KJxvsFhzdcoFL958B2a5BdsObZR+GrjcnGiv7z7l8JMn6BYI2QVCdp5wJUeolMGs3Llz+TqEEJiWjmWomIaCqQssTWKqLqZqYyk1TFFfCVsUMWUB083Xb6s2mnIXE9dbA/HGZaZmcW7a5dJEnkrNpaU5yMGD/fTv6kOxAu8Q1H2gez+ygfyDwANdOQghvg48IqX8Jw9gbA8E90oOz59+k+S3/hX9zOLXl0goNssFk1xOx84aeNOCxnVJS+rm0tBCQKMQ9SBDOpYPIt4KAX+egJUhIIq3vU5ReimKMGUlSkWJUSFKwQmSLZmsZxxWchmqdgrkzaQhhBdFBEAJI7RonQjUEF5FoyGoE+8I0LSrjeYD2/BHb+TIZ5PFDSJI8ubkOksbZBDzGzy6rWFzddDX6EcIQblcZmpqionxccavjZDO1reWoiJLr5ykjxm6wwpmz+N1Muh+AgLvrdlzJ9jFKouvXSV5Zg6lmEI0TlKIX6AYvYLUqkhbpbIcpzKmolywqRY18qZKIWAiDQ+uy2Z3bUH1MurrZ9Q/QMKMoUiHruIs2/OjbFeSNLa20Nw3QENbJ55QCMsfIJnLM7e0wvjUFOl0GoCWlpbN3oOkJnnjzDcJTn+PYHGYs6bkFa+XlY3eg+ZSkJZECx2JVloy7WhusC6SKDw4qgdXu9nrQwUaNEF84whtaFjVXId0tUDWyZN1M5T1Ao5Zo2bWKHsqFD0l0p4i654cq54cKQrk7PxtpY4xzeWAI+he9FOYa2Y1Fyen+cmEPKwEgqSNKFUnSKXsw5W35PxFjYhVozVo0+6v0W5V6TZL9JpF+tQ8QZl71zSLWylQqckb/StuvYel7Kg3rm9cVhyNsjSouPrGbQXbffcgrKoKpmVieS1Mjxdzo7fF8gcxA2FMfwgrEMD01ntcTI+XTGKVqydeZurs2yBg4MgTHHz6a7T0D97T7/XjjgeeVhJCvCmlPHLfI3tAuFdyeOv7/4kLv/f/IZAStKxLGjM37nMF5EIKlbCC5ndo8JdpD+TxBKqoxo3PrCoN8iJEWYlS1WLUtCaqSoyCHSBdMllOlUnn1rHLKaSbhZvSRQqaFkAVPlTpRcogjtEMegyhhFARBLUiDQ0qsZ4IzUPdNG5vxrBuVEdJKZlZL26uCt6aSt5MBj0NHOlp4GhPlN54nQxc12V5ebmeKhq5zNzSCq4EgxrbmKWXafr8FaK9BzbI4BiE3595vGPblHJZsisrzL1+kfWRWZxcASWyCi3TqK0L6NF6qWk1p5OZ8ZOd9ZNf9CKdG0FM85gEY034w1F8oTBqIMzFWoRXVgSX8gYSQVN5he2Fa3y602LoyGF6Dx3BH4kCkMlkGT13ienzI6xNLUDZxXA1glYQj+ZDEwaGs4YIjOAGL7GmzPKa1+Qty6KqCAxHoyM9SEdqLx3pHfhqdVlmzS6hOEWEU0bKEjYVakoZW6sQ9OrEzSAtWowm0YSKSg2bK54JzvivMuwbYcKaw71Dd+1NpY6aF79q4VdNfJiIqh+74sMpCwoZl8S6xVo+QlqGyWu+m4smgJiSp0VJ46GCI1V0ARFRYL8Y4Slxmn4x+87lC7r39lm5eess/Q5pltty5xuXuve2cmC7WqVSLFAu5Kls9LFsXi/k69c3elkqxQLlfJ5KsX5/uZC/o0HOVlxfHd7UGOn1bTRM+uub9hv3bTZSen1Yfj+G5fmR+Th/mLjftNJPbrmpULcKPS6lvLd+7Q8A90oOF//wN5H//N+RD0tEyMYfqBL3Vwn7axgBG6ko5EWQoohS1RpwzWZcq5Wa3kTBCbJe0FlZT1NIJygXEji19G1SHEIxMD0RLN2P7hooVQ2nYlHVWqh4uxEbZbC6rBD2Vom1WDRub6Z5qJtIWwBVvfkHKqVkeoMM3tpYHSxnr5OBubkqONLTQG/8hthYPr+xkXz1AhOT05u68M2s0McMvVaGjp5BtN4NMoj23La8rlUrdbnjTF3yuLDl+vXzhXSK/Po61Y2Ug2o4BDryBDvzBDsKaB4H6UJp2Uf1moEc1VFWBGmfS7bZg3fvTrY/9iX29z2GLxhCUVRcV3Li6iL/5fsXObFUpYxKsFZkKL/EY9h0evwI1UutJqhUoVxTqEodWzGxVU99Q3ALFGyajRE6zVNkI2e44CvwitfDNaNekBAuW7QmmmhMh/GXTUpmnpwnT8YqkvYVSPlKVK/XLkhorzaxv7CdA4Xt7C0O4HU9uLgseZaZC8+zFl4iH1jBozgEXBe/6+J3HAJODV+tQqBWwayUyRdNEhWLhaqfeSfEvIwzL+MsyBjLRHFuSfv47DxRmaFDTbDDXKPXm6PNLNNk2mSkn6vFBqaLHkDSExYMtZrsaAuhe/y3B/WtaRbdC3ehSvphQkpJbn2N8y8+x6Uffp9iJo0/EqVzzxCxjq4N4snXmyc3CKdcvHG9UrxVKv8WCIHp9WJ6NzrtN4jE2ujKr9/233Tb2uzS96OZ5gPrRfggcb/k8HtbbtrANPAfpJSrD2yE94l7JYfE2ydwvvV3qWgxHKMRfK2IYBeur4OSaGAlZZNcXSa7tkwxk6BaWke6mdvSP6ruxxOI4w9F8VsWniqITJVKWiFXC5H3tVM1w5t/71VKREKSeFeIpj3tNO1owR+5849JSslUosBbU8nN1cFKtv768YC5QQR1QuiJ3SAD27aZm5tj4uoFxkevsryxmvBSpJcZ+vQ1ero60DsfpRjdS1EJb2rc3+p2dZ0A3kkdU9NNdGFiYuHTgnijDmbbGqJ1DiW2glAkVAz0ywLvORttzMeCz8dcUwCau4jGB4mrTSgVjXLBplJ2qdQEC1LjbcPkgqWRVQWGhMGqyq6qSruj3NQLoNpFVKeI4haRsohDAVstUlULFLU8mGk6PLO0W8tkfCXe8pq85rHIqCoCgSoCOE4Zy1YwXRWPo+KRAi8QAKKKJKZI4rJCY0WjsbCNUHknZm0PQtY9llWxjKWcw1SGMZWLqCK7Ob6K1FiUMeaVNhaUVuZFUz3wu1Hm7RDLtu+mMmQFSaNVIWJm8FTXMLM5POkKATtLR1TyyKF97HvyC4TatoGi1tOJs7MMDw9z+fJlqtUqkUiEoaEh9u3bRzh84/f34471hTnOPf9NLr/yEna1QufufRx85utsGzp417N913WoFktbCOR69/3WlcuWrvzrJLOxunkn45/rUFRtgzCur078W1YuvptWLlvlX64T0K0lyB8U7pccHpdSvv5e5z5M3Cs5rM0lOP2t10kvL5FPrlLKJXCqd07/GJ4I3lCcYLyZaEszUZ+Jv1SiOpciNV8imZJktRh5XxuOVpfiENIlaJZpiBvE+2M07+0g1hXG8r3zF3+dDK7vF7w5uc5qrv5DbNwgg0fvQAZQ30i+dnmYsfOnmV9cx67ZKHaFqJ0k6ObwmCboQYqOQbFYoZjN3FkdUwg8/sAdde91w6Iwm6I6U8DK6QTcIK5SoxAZodx8BbdjEiVQTxfZiQYqM9soLuygkO7HVv3YmhfEO89KK06JEb3KJUuwaOgIKemuZhioLNIqZ6npeQpmgaxVJOMpkvIVKHrKqCp4JARRCSoqYSHorJTYXcjgrVUZMTVOeDwMWyaOEGhYCGOQz+RT/MrSKVrc20sqHdUE3cJWvJTtfsq1Hdi1fUi7s/4HahEjvIqnuYZodFg2PCxUvcyXLeZLOgtFhfk8zGdtVvM3V8aoiqA5aN2s3x/SCWrXkOkfkr78OtlxlcJyfS8p0tbA9sc/y87HP0u4+YZ2fyaT4fz58wwPD5NMJtF1nV27drF//346Ozt/LGavdwMpJTMXhzn7nW8wNXwGVdfZ8cRTHHj6a8Q7u3/k43HsGpVi8Ub666bU1xYi2SLzUt5y7r1KkDXDvEEWt61cbr4damymaVvvPb2P+yWHs1LKA+917h4H9h+BLwOr1yU6hBBR4I+BbuqrlJ+WUqbe7XnuuUP6jXM89+v/c30sqonla8AfbSTU2EKsvZWm3k4iIT/GWpLC1WusXF0hsVQkXbLIeVspepuRG8tvDZuw3ybW5qNpVytN25uJtHjR9HdfnkspmUwUbtpAXttCBkd7G3ikI8i+uEpMrd1I4WQzZNcTrM3Pkl5ZoJgv4tZqCMe+Yx5ZUbW6xv0WUxNPMFSXTlBNlJpA1ASyLHAKLqVsiUKuRDFboZSrUqupOJg4qoWjepCBMv7WK/hbL+BtHEHRqri2QWFlB4WlPZTm+3FzJsItICniUqCmFKhqRcpakaJeoGAWKVtFqlaVZdHCcnUnqfJ2JCpRfY6d1lvst07RLNIEXInfdW+kZVyXgCvxuS464Co6tmZSRVJybC4ZKic9Jq96PSxs+FhYIkYycBSDPvYmy+xy8jTFovS2NLKzqYkmf4iymyCVvUhmZg57xsWT6MOT6aUsVZYUm9UYJBuCrHkMFms28+m6tHMif/NMUlcFLaEbrl1tYe+N6xEPzUELTVWw7RyJ9R8yP/U8k2fOkbxmUVjyAoJwawM7Hv8c2x/7FNHWts3nrtVqjIyMMDw8zMTEBABdXV3s37+fHTt2YJrv7Ofw44ZatcLVEz/k7HPPsj4/izcUZujzz7Dvc1/CGwp/2MO7J0gpsWvVTX2wG6mvDd2wwtZ9mPwtq5j6IbcUJQwePcaXf/l/uqex3BM5CCGOAo8Bvwz8my13BYGfkFLuu6fR3PwaTwJ54Pe3kMO/ApJSyn8phPh/AREp5bu+83slh2q5zOr0JNHWNiyPl9rsLKWrI6QuT7E2uU4y4ZAREfL+dsrWjVJNS60SjSrEt4Vp3tVObFuYUMyDUN57lialZHw1z8nRRc6OzjEytUg1l8HjlGjUqnR5XeJ6DZ9Twi3mKGbTVAp3zo9KoSA1DTQNj1ojZKpEAlGMYDOuFsGuCtyKwKko2GUVuyawaxqOq9cDveLFVr2bBHcnKE4Z1SkiZBajYQJPxyi+tmmsaJ2vywWT5FqQ5LpOquiCUUC1cvgU+7ZA7pf14O5Dw4fB5Vof/71ymBedg+SEjwayPO27xk91ZNjX6sFWPSTzFZbWc8yvpsiWHSoYhBpbMZuiLPtsziRThJfn2FWexjXnOOVROemxKCsKqqsg6SMXeYyybz8xI87Ptsf4uc44wQ3CKJcXWU++wdLYFRbGHFJrnaTyraxIjSVcVjSXZSB9i4OXoSqblo13snFsDFio7/B7qFaTJBI/YH76eabPXSY17iW/5AUpCDU3sOPxz7L9sadoaL9RBCClZGFhgeHhYS5evEilUiEUCm2mjaLR6Hv+9n6ckE8lOf/idzj/vecp5bLEO7s58MzX2f74cTT9R5Ny+ahCui7VcrmeEsvn0QzzpsnD+8G9ksNx4Cng7wG/teWuHPAtKeW1exrN7a/TDXx7CzmMAk9JKZeEEC3AD6WU71qHdq/kUJ6YYuq3/5D1+QLJnErO00Le346t+zb+QhK0akSbLJq2N9I42ESsPYA3aNz2XNJ1N83KC5setfUN2pWVBEsrCbLJJHYhh2kX0eWdl5Wmz4fh9aHqBoqqIR2oFSs4VYm0TRQ8qPhRZRChBHAVL67iw9a8yDtpPG1AcSqoTgHcIsgCriggRRFXySO1AlLLI/Q8ip5HM7PoZh6vN0sw5GKENAgq9Q4XV+Jdd4jMO1hrgvWaw1JAsBbx0hTrpyu2k974Xixv7KaKFVfzsDA9x+unLvHtkSwX1XYyeggdh8eaFP7Kse189kAv+VyWa9euMTo6ytTUVF2sT9MoN0a5qhlMlATxXIZPlUfo1c+y5lvlhNfD1Q3fZY/rJ+w7jC/+OCNKHylX5UjIx881NdCNykxinfGlUaYWlllchUQhwKptkbtlvWWqoh7so1tm/OE6AXREPMT8JspdTAY2f2vlJdYS32Nx5nlmhq+RnvSTW/DVCaGpge2Pf4btjx0n1tF10+NyuRwXLlxgeHiYtbU1NE1j586dDA0N0d3djfIxq6hZmZrg7HPPMvL6q7iuQ8+Bwxx8+ut07NrzsUmRfZRwv2mlLinlzAcyMu5IDmkpZXjL/SkpZeQOj/t56valdHZ2HpyZef9DnHnlCt/+w2UAFOESCUriHQEad7YQ7w4TbrKwK/mbTMqvd9QW0ymK1w3LN8zLXce57TUk4CoKUlFQhIYm9LphDh4U6UVIL0KEEEoYqUZw9CBSeeeZUT3IFxFuASELCAogCgglj1ALqHoJzShheCp4vDbekCQU1Al6PfiMAIatYa+UKa7aKGUPHiWOIoJILLI1m2QgTbVzGbdhjKpnDhSJkgfzsgLzPkZtgxOxApc7Ba3N/TzZ/iRPdTzF3the1FtWILVqhZnz5zj/1lu8cDXBRb2LJasFgWRvg8pfeqyPZw50kUuuMTo6ytjYGAtLKywYYRY8DawIi2xZQykIHnWvckw7TcB3iau+Kie8HpKqigB6vT0c6/oK7d7D/GBF5/vzKSqFGnFHEKi6JDNF8rdsKXiAJhSaFWgLGXS1RenqidLVEaIt7CHmN+47GBWLU6ytvcjC3AvMX5gmPRkkv+BDuoJgYwPbH/s02x97klhn902vZds2Y2NjnDt3jvHxcaSUdHR0MDQ0xK5du97Vb/nHEa7rMHHmFGefe5b5K5fQTYtdT32WA1/6CpGWe5sRP8Td4X7JIQ78P4FdwOavUkr56Qc0uG7ugRy24l5XDumlZc48+zxC5CiX18ln0xSyWcr5ApViFaf8LptGirph4WOgCAsFLwp+hBIANYyrRUENgvDcMcgIt4pmF+qGOLKAQgEhivVDKSHUMrpexOup0RD309TXTay1g2Aogtja0r/1umrcVH4qpWR9fo7Fk5fJXlrFyqpEjWYMpZ6TztaypLUCbt8iWvw8FeMMtlVPYWlzAmPcIlWK8LJW5FRbhWxY51DTIZ7qeIon25+kI3B770O5kGfy7GlG3zrJy6OrXLF6mPJ24wiVzoDCTz+yja8MtVJMLPDG5RG+P5ti3vGRcj0UqxpOUSIkRMlyXBtmyHuaijXFa2aYc0oTNTuKYcdpNLZjiU5KZS9L6cpmae51WLpLs1EkLiu02h7aq2FaUGlSob1Np3VnB56BGHqz767SgXcDKSX5/Ahray+wNP8ii1eWSU8EyM0HkC4EYg1sf/xTDB49RmN3z22/i6WlJc6dO8fFixcplUoEAgH27dvH0NAQsVjsgYzxo4RqqcilH36fc89/i/TKEoFYnP1f/Ap7Pv15LN+9aXE9xPvDu5HDO+chbuAPqG8Qf5l6iulngbUHN7zbsCKEaNmSVvrASmbP//C/MvzySxu3FIQwUDARBFEVH6oWQGohUIMIxQvCW7/kxqxSuLXNIC9kCUWU0dUqprWEz7eMJ2DgD3kJxiIEmhrwtcTRRJKFsWHGp2aYyCisy7rlY0gp0teg09u/n55Dn8OKtr6v9yNdl7WZKRbfvEru8gpWTqNBbyGq+oniJ6vmWKUAHTn01gvY8lXKvhmkLqlWwBzXEOkWrrgevu1fZabXIWIJjrV/kV9tP85jrY/hN27/p82nkky8/SZjb53kzPgiVzx9XAsMUmrYR9hU+Cv72+hsNHlzboY/uDrKvz0zQaWsQNkAmupj12CbZ5mdwTmEm2LKsfgecZ4t/wxuLgLyRiqvDGBpNIU9lC1BoUXgWCq7vEm+kh/l0XU/jek+1EIYKSRKM3gHWvAMxDG7ggjtwaVipHTJZodZXXuB5fkXWR5Nk54I1gnBacXfEOXgM08xePQYTT19txFCoVDYTButrKygqirbt29naGiI3t7ej13aCCCzusK5736Liy+9SLVUpGVgO0/85Z+l/5GjKOpHu7/ik4S7IYcGKeXvCiF+aUOJ9RUhxAepyPpN6gT0Lzcun/2gXihi9mOGekB4UKRAc4rolNFEFUNzMA0wvTrS0MkgWKjWGC0kWHAVkrqJGQtzsL+RI70xjvY00B65wypBSuTaKCsXXmJi9CXGX68w6zbioKERoDvocri7mb6DT9HQOfi+Uhmu47A6PcnCW1fIX17FyuvEjFZiapAYQXJanlWlhNJq4u2cxq6+QE25SDVaXx2oCYE1GiVZi/OiVuLVwCpOMENfOM5n25/hqY6n2BPbc1u6CCC1vMj4qZNcO32Sscl5Rn39XAvvItF8BFWBeIOFqdjkyg6///YcYnMRpoEGimZjeiWW45CvqtRslelcE9MbZCHUAgFPmR3NQfa0tLK9MU5bpJ7/z4skv7M4y7czfoSUfD65xN+8prItEwWOQsTBcyiGd7AZsyeM4rmbn/ndw3VrpNOnWF17keWFF0mMl0lPhsjN+nEdH/5olANfPMbg0Sdp7hu47Tt1HIdr164xPDzM2NgYruvS2trK008/ze7du9/TOOfHEVJKFkevcua5bzB+6s2H0hY/BribtNKbUsojQogXgN8AFoE/lVLeW2Htzc/9h9Q3vWPACvBPgW8AfwJ0ArPAX5BSJt/tee41rWQXK+RXM3ibIuiWtiEtIRlbzfHmRL209NR0kmShnrBuC3tuajrriN7hn1hKSE1RHP0hE5fPMrGcYdxuIk99xt1o1ehtb6Rv7xE6dxxAfx+VF45tszwxxtKpq+SurOEpGMTNNky1Po68XSCj1lDaGwj1gCx+k0zhdQoNS7g+CQ6YS17cUhtX1SB/pM+RII+maBxuOszxjuPvmC6SUrI6Pcn46ZOMnzrJ/MISw7EhroV2kd6wWEWpqxjfFArFxmdyy4ZvWCvhEatUjRRZM4Oip4hYJY509PPFHU/yZOejePX6+6rVMqTSb/L23FX+81oHJ/QeNFfyE/M2f226SrOwMfqC+AZbMfvCaOEHn5N3nDLJ5Gusrb3A8tJLpCYd0pMRsrN+XFviC4cZOFonhOt+0rdiZWVl0zinUCjg8/nYu3cvQ0NDNDU1PfAxfxTg2DZjb77G2eeeZXniGpbPz57PfpGhzz9DMBb/sIf3icf97jl8GTgBdAD/lnop6/8ipfzmgx7oveJeyQHAdSWjK7lN+eq3ptZJFeuNYe0Rz6YUxaPboncmA4DMPM7EqyxceZPxuRXGKxEWaQIElurQ2xSkd8deevceIRQK3fXY7GqVpWsjLL49Qv7qGt6iRdxsw1Lr1VQFu0hGtVE7GggPhjHyPyS18l2y5iiVjioooBQUrHQrabWd75kuLxdGsKVNxIxwrP0Yx98lXeS6DosjVzl9+hTPTawy4kZZU2KUbfN2ErgFpurQ7Bdsb42zzVejsXiFXPp1ppwxzvuLJIx6P/AefydPbvsSx7s/y2CkvnJynDKZzBmSiZPkx6cZXevgv/mP8Fo0hNeW/NR8hZ9F0NnXitUfRWt6cLaJN33+Gz0Ia2svsrbyCqkphcxUlOyMD6cm8YZCDBw5xuDRJ2gb3HlHQigWi1y6dInh4WEWFxdRFIWBgQH2799PX19f3cDoY4hSPseF73+X4Re+TT65TqSljQNPf41dT34a/WO2of7jjPvxkFaBX5RS/pt3/KOPAO6VHM7Opvhb/+k06Q0y6Ih6OLKtYbMLuT3yDmSQW4HpE6RHXmN8apqJoo9JOqhgIZC0hU36Bgbp2/MIrW1td503rpXLLI5eZenMCPmRBN6SRdxsx6PVA3fRKW2QQYzIrjiByiip8WdJVU5R7EjjbLRimOkgiuxl1NPIfy/PMJWrO7z2hfs43n78tnRR1XZZypSYWS9yejHFayPzTCaK5MrgOgIpbyWC+m9GUx2Cokpc5mjy2uzsauLx3ds52NeCd+kUc1f/nFfnX+WEKHPKY1ETAr/QeaxxP8f7vsoT7ceIWlGkdMjmLpFaf4Ps1AjOjMST2M5VdvF73T5OxTSCtuRnsfi57ibi28IPdN9gK673IKyuvUBi9Q2yczrZqTjpaS9O1cUTDDLw6BN1QtixC+UOKTfXdZmYmGB4eJiRkREcx6GpqYn9+/ezZ88efD7fHV7544HbpC32DHHw6a+9L2mLh/jR4X5XDi9LKT/1gYzsAeFeySFVqPIvnr/Ko9vegwyKSZg+QXX8BDPjVxnPqkzQRYJ6NA5aCn3dnfTuPkRPby8ej+fOz3MLKsUCCyOXWTo7SmFkHV/ZQ6PVgUcL1F/WKZNRbbSOOOF9TYTkAqVL3yex+hK5yBzVARdpgLAVfOVt5L39vKIKfrB8jmw1u5kueqz1OAP+I9jVIAvpEvOpIhPrRcYTeRaTJYrvVpXF9ZSQxKcVGFQSbGcdU5N0dXUxODDIwMAADaaDPfo8w6N/zqvJy7xiakxuuKJ1G1Ge7PwUx3ueZn/TfjShUSxOkky9TmbuPNXJAtZaL971nai1IK/HVH5vwOB8QCOmKPy99jh/o6sRv/bBzLKv9yCsrb7A+vppcvMectNNpKc82BUHKxBg4JHHGTj6BB0797zjpmkikWB4eJjz58+Ty+XweDybaaOWlpY7PubjgDtLW3yKA09/9UORtniIu8f9ksM/B0LUK5a2ekiffZCDvB/cT1rpjihnYOYN5OQJ1sbPML5eY5wuZmirbyQr0NUap2/nEL19/cTj8btKa5RyWeavXmL53CjFsSS+io9GqxPvBhmUnAoZ1UHriBHe10zEl6J29k3Wx18krVyivL2K3Vb/vvRKEI+5l0l/O99NLPP2wix2NYgl22gxd+ETnVTLPhYz1U05jq2Q9Xh/Y0UgJIZSQVWK1KTEtiOAQqNRpEeu0a0kiXh1+vv7GRwcpLenByt9jdTVZ3lt6nlOlJd5zeMhpypoCA6F+jje+xWe7PoMncFOypVlUsk3SC2fojyexFhpw5vciVGs+0K4PpfXd4X5nQaVy65Nm6nz9zsb+cstDXjUBz/jLBanWF17kbW1F0inzpNf8JGfbSc5YWCXbUyfn/5HjjJ49Bgdu/aianfe1C6Xy1y+fJlz584xPz+PEIL+/n6GhoYYGBhAe4fHfRzwcZS2+KThvlcOdzgtH1Sfw4PAfZNDtQCzJ2HqBMWJN5hczjBBJ+N0k9vYSI6H/fQO7qSvf4Curq672kgupFPMX73M0vBVSmMp/FU/jZ4ufFrdRK/sVMmoDkpHjMhQEw2NNexzp8ideZX19OuUtuUp73QpWQbrpQYKpd0six1cznm4liyRK5rIWhjpBG56XUURaIaCqwhqjgu2RDg3vmdVcwiRI15OECtPkvNXWA/uZLXQTc1RCag1trFGr7pOX1OAwcH66qC9OYaYOsHY1T/lxOIbvKLWuGAauELQoFg82fIoT/Z9jaNtj2Fgk0q/SWr1LQqT86iLEbzrO7Gy3XWDet1F3+bD6G/mhUaVf5dOc61Yocdj8g+7GvkfmiIYDzANsbUHYXXtBfK5MXILPgpzXSTHNWqlGqbXR9/hIwwePUbnnn3vqIzpui7T09OcO3eOq1evYts2sViM/fv3s3fvXgKBwB0f93HBbdIWXds4+MzXGXzsyU+8tMWPGx56SL8Tli/ifvv/wcLCAuOyjQm6WaAZicAyNHp6euntH6Cvr++uNpJz6wnmr1xk6fwopWspgnaIuNWBXw8DUHFrZBQHpb2B8L4mYr0G7vm3WX7jFNdmLzITdVhsjbDqi5AoR1kvxUlWYuSqtwipiRqWxybgt9BNH0VHIVepUSvbiKLDpoeMAqbXxss6zZl5BtfmaSwnqIWq5Hv6WA49wuWVEMkS6Dh0q0n69RSP9sTYPlh3RotoFcoj3+bU2Dd4JT3Cq5bO8sZseKenieNdn+fJ3qcZDPeSy54lmTxJbvIazBl4kzvxpAZQXAOpSLQ2He9AC1Z/BNnm409W0/zm7Cqz5So7fBa/1NXEVxrDqA9oc3lrD8La6osUi7PkF30U53tZvyaoFqsYHg+9h+qE0LV3/7sGt2QyuZk2ymQyWJbF7t27GRoaoq2t7WMv77AyNcHZ73yDkTdO4LoOvQcf4eDTX6N950Npix9X3O/KoQn434FWKeWXhBA7gaNSyt998EO9N9wrOcyNnOMP/vhPKct6QGhrbaFvgwxaW1vftZJESklmdYX5q5dYOj9CeTxNyA3TaHXi1+sN3RW3RlpxKLVGKW0LUIppLFybYnpygbn1HEuaxqoZpcDNex2G6hD21bC1NDmWcC1QrTCW3knNCVDIuZCzEcUbCqyqLvAFa2jWClrxAl2pRQZXSkSKKhLQ2qNE9h5kyb+fF68VmUw7CCStSoad3jyf29HE7h0D9Pb0YKZGWb78Z7w6/SKv1BK8ZZlUlLqq02PRnTzZ/zWe6DiO5aySTL5Oeu4izrSDJzGAL7kDtVafOYuYwDvQhNUfxewJoZgaBcfhvyyu83/NrrFcrbE/4OWXu5v4XEMQ5QEEmK09CGtrL1Ipr1JYDlJa6CMxJqnky+iWh96DjzB49Bjd+w6gGbdrZV1HpVLhypUrDA8Pc12ipbe3l6GhIbZv3/6+SpF/HLEpbfGdZ5m/Wpe22P2pz7H/i19+KG3xMcD9ksPzwO8Bvyql3CeE0IBzUso9D36o94Z7JYdSqcQLL7xAX18fPT0979p8JKUktbTA/JVLLF4YoTKRISyjxD2duHqYZSTzbo1pxWXNZ5LyqSSkw0KqSMG++TM2RYWYN0mDZ52YJ0NHNIQ/FGBCupwpr7NWDeBW26DUgMyBkqshqjdUQT0+hVCo3oVd4G0qjNCaqdCzGqBr1YdelghVoXnHDvoOPcmwE+XbV5NcWpe4CKKiwL5wla/saeaRvdtpjUeQU69w8cqf8MrKaV5VbcY2hOzaNT/HW5/gyf6vsyPYQD57mvTSGSqTGazVnvq+QamxPjC/xOpvwDMQx+oNo24RKMzaDr83n+Dfz6+SrDk8Fvbzy11NHIv473vWubUHYS3xA2q1DKWVMKWFAdbGbMrZEppp0ntggxD2H0Q33lnWWkrJzMzMpnFOrVYjGo1uKqC+n3LkH1dUS0Uuvfw9zn73W2RWlgnE4hz44lfY/VDa4mOF+yWH01LKw0KIc1LK/RvnhqWUQw9+qPeGB74hTV2KIjE/y9zli4xdGGd5rkpViVEy4qQ1i2Uki9JhRci6nMMW+BVJUy1HPLlITKwSaUgS7skSaVqmwUoS9kUpBY5wstTJ8ytNLKc8uAUPSs5G5GyEW/9OhCKIhjWioQpezzxZeY415xxCLaPZgv2FLvrWQlgzBWSlhm5abNt/iPZ9B7hc9fGtS2sMrwsqUsMrqhxocPn6UCufPbSDsFIie/UbvHHtm7ySHec1SyetqqjAAV8nT/Z8iaMdjxKozZFKvElpcgV9uQXf+i7MXGd938CQGD0BvANN9eaz+O0d4utVm/8wv8Z/XFgja7t8Jhrkl7ubOBy6v3LOrT0I6+s/xLaLVBIxSgsDrI5UKWUKaIZJz/5DDBw9Rs/+Q+9ZX59OpzeNc1KpFIZhbBrndHR0fCJSJ3Vpi29y8aXvUS0VaR3YwYGnv/ZQ2uJjivvVVioIIRrYKG4XQhwBMg9wfB8qXFeylq8wl8xzZWyW0cl5phfTJAoKWcVHUtGpiAHYMlnyC5sWv0l/a5RPeSGeXKJheoTQ+dNEk9fQBopUH7Eof7aGq1eRqCT13ZzNH+eVtZ3Mj8TrJFCop4UUwNDLtMZMWtodvNY8GS4xU3qLqiyyDETNKPv8OxlY/zze6SLZsWmcWg1PwKXn6HHiO/YwWRT8t0urnPtejpysoaEyFIOf2N/CTz62Ayt5lanLf8J//9Nf4lU7xbkNV7SIP8Cx2D4e73uanX6DavYcuanTFM+OQXIXgfQXCbk6KBKtw8J7pBmzL4zRHkCodw6Yy5Ua/9fsKr+/uE7ZdXk6HuKXuprYG7h3aYitPQjJ5Ou4bpVaqpnS/CFWR8oUUjlUPc+2oUMMHn2CnoOPYFjvXlZcrVY3jXMmJycB6O7u5qmnnmLHjh0Y75Jy+rhASsnC6BXOPvfszdIWz3yNlr6H0hafVNzNyuEA9c7o3cAlIA78lJTywgc/vLvDva4cXr80zc/+wSVseYu0A4JmBI1SEBWCxpCPrm1hdh9uoSukoJ4/S+HkmxROnqQyMU6tVZI6FqZ0QEP3ryCEJO8GGc7v5nxiN1cW+imXbqQxVLNKPOLQHxfEw3ky8jLj+VMkK+sAGIrBjoYd7IntYYe+Df90mbULV1m4ehkpXQKxOL2HjuDt6mU+V+G7l1e4mPOyKgOAZEdU5ScPtPMXH+nAXHiVt6/8Ma+unuMVXW66og0aUZ5oe4IDrdtpkksUFq7izmj41nfgTe1ErdVn9kqjWl8Z9Ecwu0Mo5rvPHmdKFf7d7Cp/tJTEQfITjRF+sauJAd+9dcWWy0usrb3I6toLpNOnkdLFyXZSmu9n5WqB/HoGVdPoHjrI4JEn6Dn4KOZ7aBNJKZmfn2d4eJhLly5RqVQIh8ObaaNI5F1FgD82cOwaYydf48xz32Rl8oa0xf4vfJlAw8dPBfYhbsd9Vytt7DMMUi+LH5VS3sF4+MPDvZLDqW+d5Y9fmaNL89OCIC4FHiHwtIYI7Gyg+XATpkdQOjdM4c2TFN84SWpklKn2FhKHg4g9Lg3BKUJqXfppptDB+dVdXFjdyXSmEykEwsqgWUu0R0p0xhQC/gxzxVGmMlPIjU7j7mA3e2J72BPfw56GPcSKXqbPnGb89ElWJscBaGjvpOvAYZR4KwvJNK+MrjFaCTHnhnFQaA+o/A8HO/jLuyyUuW9zYuLbvJKf4U1Lp6QoWAgeCfZwpP0w2wMGeuoatelyfRN5fRd6uR4MRACsgTie/ihmbxg1cHcz52uFMr8xu8Kfr6RQEfyllih/v7ORLs/7t6zc2oOQzZ6vSzMV+ynO9bJ8JUduLYmianTv28/AkSfoPfToXeXBs9nspgJqIpFA1/VN45yurq6PpQLqnVDKZW9IW6SSD6UtPsG43z0HC/gF4AnqqaUTwG9JKW9NtX9ouGc/h+kMc/9+GNkcqJPBI81YAZ3KyAj5k28yceESlxIpJhpbWOiO4G1N0+e5wk7rKoZSo2wbXE0Ocn5tF1dSOynrgpo6imLO4POnaYsoIGyWCkuUnfrHFTbDm0SwN7aX3bHdBPUAyxPXuLYhapdaWgCguW+Qpt1DOMEIMwtLXJhPMeHEmHYbKEmNkKXy9X3N/NWuNOWVZzmxcIJX3NymK1qLYvF4w072NHfRKddwp9NYq9vwJndh5TrrH4IpMXvDePpj9X2D2J39J94Jl3JFfm1mhe+sZbAUwV9vjfH3OuO0mHefjrm1B6FQGENKUCu7Kc5tY+lyhszKGoqq0rlniMEjT9B3+CiW/70JwbZtRkdHOXfuHBMTE0gp6ezs3DTO+Tj5Lb8X1hfmOPvcs1x59eUb0hbPfI1t+x5KW3xScb/k8CfUrUH/y8apv0zd1/kvPNBR3gfud0M6NTPL8JlhLs7Oc6VQ5Wq4hQV/jE4xyZB2jn3+C7T7lwBYLTYwmtnLqrOHhOtj0T5HSl5E6Cn8hg9XupTsEgC6orMjuqO+IojVyaA90F4Xl7Nt5q9c4trpk0ycPkk+lURRVVp37CHcv4OibjI1M8tSpsyEE2VGNLNe0zFUwdPbg/zFpjFymRd4NXmR1zRY11QUCXutGIfiPQwGdCIrKYyVFnzrO/Fk+hGuBqpE7/DVK4r6I+it/nfcN3g3nM4U+LXpFX6QzBJQFf5We5yfa48TM+6uI/jWHoRSeRZQ0Gv7Kcx1sXQpRWppGaEodO7ex8CRJ+h/5CieQPAunlveZJxTLpcJBoObxjkNDQ3v+RwfF0gpmblwjrPPPXuTtMXBp79K7KG0xSce90sO56WU+97r3IeJe95zePs8v3B5mQQ+RN4mUEqx17jA3obL7IldxacXcaRKsrYDx3iEpNrEucIwF5Nvba4EtqIz0HkTEQxGBzHUGzPoWqXM9PmzjJ86yeTZ05QLdXPwtj37sTq3kbEl0zMzFKsO8yLGvNbGZF5DAl/qqPFM7AyJ8uu8Vp7njGlgC0EAlSP+FnY1xOiplAkuRfAmd+JN7kS165uxarOOp78Rqz+C0R1EMe6t6kRKyWupPL82s8Lr6TxRXeXn2+P8zbYYIf29SeFGD8ILrK19j2p1FSF0TPcR8rMdLF5MkFxYQAiFjl27GThyjP5HH8MbvLvS0Xw+v5k2Wl1dRVVVduzYwdDQED09PZ+YtBFcl7Z4mbPPffOGtMUXnmHfZx9KWzzEDdxvtdI5IcQRKeWbG0/2KPD6gxzgh4W08BGYm+Hx+GWGWq6wLTSFIiSuCOMNfAbH18MriTlOJodZLv7RTY/1al72xPdwoPFAPU0U20PYCt/2GqV8jskzpxg/fZLp8+ewqxVMn5/mvQdRGptZyxa4tLyMe/UaWU8LC9YQF0uCiu3wufAcf33gLZaci7xOkX9crjdcbfOG+IlgjH6PSfeqj+DCTrwXd6OXowCIkIJnfxyrL4LZG0L131/FjZSS761n+bWZFc5mizQbOv9LXys/09qA7z3KG2/tQbDtDIriwRKPUZlvZf7iKonZWRAp2nfsYv8Xvkr/o4/hC9/dprDjOIyNjTE8PMy1a9dwXZe2tjaeeeYZdu/efdciiB8X3CZt0d3DF3/h//ZQ2uIh3jfuZuVwlfpm9OzGqU7gKuBS11ja+4GO8C5wryuHpdXXuHLpZwHw+nZQtQZ5O1fmpdUpFvKLOPKGL3HcE2eocYjj7ccZahyiM9D5jrn5XDLB+Ok3GT91krkrF5Guiy8aI7prCDsQZimxTi6XA8CIdzOntXJ6FYqFHE95zzIYO8O0MsObpkJeUTAkDBl+dvl8DJR8dKZ21/sN8humPBZYvRGs/gas/jBq1HogNfmOlHxrNc1vzKxwpVCmwzL4h52N/MWWKOa7zMJtO0ci8TJrie+xvv5DHKeIpgXxKsfIzTQzf36RtZlpANq272TgyDEGHn0Mf/Tu0z3Ly8ubxjnFYhG/37+pgNrY2Hi/b/3HDiuT45x97tkt0haPcvDprz6UtniId8X9rhy++IDH85FBxWjmqnqI7ydWmJibAWY274t5YuyP7+eZ3md4ou0JTPXdNy6Ti/NcO3WS8dMnWR4fAyDQ1knLsc9R0k0WV1ZZTqQxskUaO/vIt7XwxpJDbm6KR3x/zFcjlxlpSvGaoXNCCOIYPG56GBA+9mZ3EV3eiyfTh5AqqBKjK4D1RAyrL1zfN1AeXACouZI/XUnymzOrTJQq9HtNfmNHJz/RGEF/h9epVte39CC8gZRVDCNG0PwSuekmZodnWZ2aACZpGdjOU3/95xg48vj7KpksFotcvHiR4eFhlpaWUBSFwcFB9u/fT29v78fWOOedcJu0heVh3+e/xP4vfoVI8/vzH3+Ih7gVd1vKGqHuBLdJJh8Hye5vTXyLf/LaPwHAo3nYF9/HMz3P8Lmuz+HT372DV0rJ6tQE106d5NqpN0guzCGBcO92zI5usrZkbb3etxAOh9nWN8Cq3sLr8yUyk6/R638NglOcs2xWNQ0hJdsVjT2qwa5qH9uTj+BP7UKxLUCitVhYA3GsvjBmdxChP/hAWHZc/nA5yb+bXWG+XGO338MvdTXxdDx0RzG8cnmRtbXvbfYggItltRPQnyIz3cDsuSmWJ64B0Nw3wOCRJxg4+gTB2N3P7B3H2TTOGR0dxXEcmpubN41zPo5+y++FSrHI5R8+lLZ4iPvH/W5I/2/A3wAmuG4B9jGR7C5UC/zupd/leMdx9sT2oIh337B0HYeFkcv1ktPTb5JLrIGqERrchRJrZr1QolAsIoSgo6ODvv5+Ct4WXr+2xtq1/07I8xZJ3wrnLI2qIvBJyZBQ2e3GOJB7gtb1Q2iVMABKRMXq3yCD3jCq74PLFxdsh/+8uM5vza2yWrU5HPTxS91NfCYauC0lcWsPAoDP14/fOE52Osr0mWssXRsBoKmnj4Ejdde0UGPz+xrT2toa586d48KFC+Tzebxe72baqLn5/T3XxwWZ1WXOffdbN0lbHHzma/Qdfiht8RD3hvslh1Fgj5Sy+kEM7kHgg9BWug67WmXm4jmunTrJxJlTlHNZhMdHcGAnNX+YRCaL4ziYpklfXx8DAwOo4VZePzfM5LX/Sk2/wISvsOmK1uFK9rsme6v72Lf+Gfz5er+B8AisvihmfwSrN4zW8MFvpKZrNr87n+B35tdI2Q7HInUxvMfCN8Tw6j0IVze7lAuFesosGNiL33yS7HSYqTNXWRi5AkC8u4fBI08wePQY4eb3535WKpU2/ZYXFhYQQjAwMMDQ0BD9/f0fa+Ocd8KmtMV3nmX89JsIRTBw5AkOPP3Vh9IWD3HfuN89h0tAGFh9kIP6KKNSLDB59jTjp04yNXyGaqWMGo7h7d+Fqpmkc3myVUkUweHDhxkcHMQfifPKa8/yZz/8p6yp41zwumQbVTQp2eXo/M1yCwczn6Mndbi+b6CB2R2sy1n3RdBbfA903+DdsFat8dtza/zeQoK84/L5hiC/3NXEgQ0xPCld0pmzrK2+wOrai5TLc4BCOHyYzuZ/RGYqyMSJC8xffQmkJNbZzeM//TMMHD1GtPX9yTi7rsvk5OSm37Jt2zQ2NvL5z3+evXv34r+LRrePI+4kbXH4qz/J0ENpi4f4EeFuVg6HgGepk8Sm36SU8qsf7NDuHg9i5VBIp+oVRqdPMnvpAo500RpbMdq6yNqScrWKEILOzs5NZzS/pfDiy7/D27PPM64tcdnUcIUg5EgO2l4OlfZyeP3r+KshQKK3+bD6GzD7wphdQYT+o627XyxX+T/nVvmDxXXKruSrjWF+qauJnX7PO/YgRKOPEfAcJzPpY+L0WeYuX0JKl2hbB4NHjzF49BgN7R3veyzr6+ubxjnZbBbLstizZw9DQ0O0trZ+YitsbpO2aG3n4NNfZeexh9IWD/Hgcb9ppcvAvwcuUi9fBUBK+cqDHOT94J73HNIprpx4mfFTJ1m8NoKr6egtnYhYM5lKFdd1sSyL/v5+BgbqJkDkpnn+9d/mjeUTnNcLLG80f3VVVIaqzTyV/SID2f0oKKhRfaO8NFI3u/F+OHXm06UK/3ZmhT9ZTiGR/FRTlH/Q1cg2kzv2IDQ0HCfkPU5qymL8rdPMXjqPdF0iLW0MPlYnhFhH1/seR6VS4fLlywwPDzM7O4sQYtM4Z3Bw8GNvnPNuWJ/fkLY4UZe26Nq7nwNPf/WhtMVDfKC437RSQkr5Gw94TB8JZNcTvPRnf4LR1oW77yiFSn1bJebzc2R/3Sazo62Ftcnv88L5f8a/feMy5wxJWVGwLElPKcTx9G6eTn+ZRrsB4VWw+qJ1MugNo0U/3JneSKHEb8ys8o2VFLoi+KutDfy9Vi9W/jXWJl7kRPKVzR6EWOwzhHzHSU5oXPv2m8xe/ANcxyHc3MIjX/upOiF0dr/vGb3rupvGOVeuXKFWq9HQ0MBnPvMZ9u3bRzD43nIYH1dIKZk5f5Yzz3+T6YfSFg/xEcPdkMMZIcS/AL7JzWmlj0wp672iJFRK3dupKApdrW0MDNQJIewRXDj/e/zpq/+MNyprXNvQC2pQFQazzezIHuPrxccIqQZmTxjrkQhmXxi9+Ue3b/BuOJ8r8uvTKzyXyOBVFf5+q85Pei5QSX2fydM3ehCam79OyH+c9XHJ2LfeYPr87+I6NqHGJg5++ScYPHqMxu6ee0rxpFKpTeOcdDqNaZrs2bOH/fv3097e/olNG8GdpS0e++m/yr7PPX3XUiEP8RAfNO4mrfTyHU5/LEpZHcdhZGSE3t5eKulRXjnza7y2fIY3hU1KVVGlpL1sEcj10Z/7DF+t9tPREaxXFV3fN9A+Okv+N9N5fn1mhZeTObrVJH83eJmdzhvkM29zvQehMf4FQoHjJK5VGHvzdaaHz+DYNoFYfHMPoamn756Cd7Va5erVqwwPDzM1NQVAT0/Ppt/yJ8E4592QTyUZfuE7nP/+85Q3pC0OPv21h9IWD/Gh4b7SSlLKTz34IX00sLL0Oq9d/Kf86zeWGNY1HCEICElLIUY4t4+e/Kf4aqCJoR2NePojmD1hFM9Hq5xSSskPkzl+fWaF6fQ1jqun+B3jDJ7KFUiC9PXT3f0LRALHWR3Lc+XZE0wN/39xajX8DTGGvvAMg0efpLlv4J4IQUrJ3NzcpnFOtVolEonwqU99in379hEOhx/8m/4xw8rkOGeee5bRrdIWz3yN9h27P9ErqIf4aOM9I50Qogn434FWKeWXhBA7gaNSyt/9wEf3AWNs/AK/WUnQLk36kh2s5I/SVznIVzvjfOqzrfgHomjhj6bevyslL6yl+a9TJwkWXuEviFM0MwsOBL17ibf9I8LBp1gdS3DlGyeYPPfPsasVfJEoez/7RQaPPklr/+A9b3ZmMplNBdT19XV0XWfXrl2bxjmf9KDnug4Tb7/F2ee+eZO0xYEvfvV99388xEN8GLibafB/An4P+NWN22PAHwM/9uQQiv4E7vc9mHoXz/Q18tWf7CTaFfpIB7aa4/Dc7Akuzn+b3trr/A1WkSiEg4doavxZIqGnWLq6yKVvnGDi7K9iVyp4Q2F2f+pzDB59grbBnfdMCLVabdM4Z3JyEiklXV1dPPHEE+zcufMTZZzzTqgUi1x6+Xuc++43yayuEIw3cvyv/W32fPrzmN53l2R5iIf4KOEd9xyEEJqU0hZCnJZSHhZCnJNS7t+4b1hKOfSjHOi74V73HFzXZWG9REf8o/1P67o11pJvcmr2WzjplwiQwkHD9T/CrtZnaAg/yeLVWUZPnmDizClq5RKeYIiBRx+vE8KOXSjKvXs4LC4ucu7cOS5dukS5XCYUCm0a50Sj0Qf8bn88cUPa4kWqpRKtgzs5+PRXH0pbPMRHGve653AKOAAUhBANbOgqCSGOAJkHPsoPAYqifGSJoe6DcIKl1RdYXvsBqptFwWRWO0xvy5c43v55Fq+Mc+kbJxh/+5eplopYgSA7Hj/OwNEn6Ni5576CUi6X20wbra2toWkaO3bsYP/+/XR3d3+ijHPeCVJKFkYuc/a5bz6UtniIjx3ejRyu51Z+hXoZa68Q4nUgDvzUBz2wTyI2fRDWXiSx/gquW6SIj7c5TNZ3nC93fZYvLS4w9r3X+d23/0cqhQKWz8/AkccZPHqMjl17Ue9Df8i27ZuMc6SUtLe385WvfIVdu3ZhPezQBbZKWzzLyuT4Q2mLh/hY4t0iSVwI8Ssb1/878Bx1wqgAnwUufMBj+0TgTj4INbWBkzzJ6zxCY/gwf72cRpx7m5Hf/r8znM9hen30HT7C4NFjdO7Zh6rdXxnk0tLSpnFOqVQiEAjw+OOPs2/fPuLx+AN6pz/+KGYzXPzBCzdJW3z27/zCQ2mLh/hY4t3IQQX83FhBXMcnT0D/AaPug/Aiq2svbvog6GYbc/6f4L8Uh7hc28ZPFtf523MjpM79My7nshgeD32HjjBw9Bhde/ffd118oVDYNM5ZXl5GVVW2b9++6bf8STPOeTdsSlu8+hJ2rUrX3v18/u/+It37DjyUtniIjy3ejRyWpJT/649sJB9zFItTrK6+UPdByNUXXT5fP9H2v8tz1YP8h9UQjVPTfHHpGl8de5ZqNsOa5aH34CMMHj1G974DaPfZROY4DuPj45vGOa7r0traytNPP83u3bs/kcY574RNaYvnnmX6/FlUXWfnsU9x4EsPpS0e4pOBu9lz+FAghPgi8OvUVzC/I6X8lx/meN4vrvsg1FVOX6BQqDuiBQN76e35R5QDx/mtZQ8n3x5mYOJ1fmH6Cmo+i2aabDuwQQj7D6Ib918eurq6uqmAWigU8Pl8PProowwNDdHU1HTfz/9xQq1a4eqrL3PmuWdJLszhC0d4/Kd/hr2f+9JDaYuH+ETh3cjhMz+yUdwCIYQK/Dvgc8A8cFoI8U0p5ZUPa0x3AyldMtlzd/RBGOj/n4nHP89ENcS/eeMt1t7+cwYnL/HThRyqYdC7/zADR4/Rs//QA8lfXzfOOXfuHIuLiyiKcpNxzsO00c3IJ9cZfvE7nP/+dynnsjR29/Klv/8rDBw99lDa4iE+kXhHcpBSJn+UA7kFjwDjUspJACHEHwFfAz5y5OC6NVLpt+qy12vfo1pd2/BBeJxt3b9ALPYZdD3KD4fP85v/7Q+xLp+lM5+hQ9PoGjrInseepOfgIxjW/Tu/XTfOOXfuHCMjIziOQ1NTE1/4whfYu3cvPt9Hs2z3w8TK5DhnvvMNRk+ewHVd+g49yoGnH0pbPMRDfLSEgm6gDZjbcnseeHTrHwghfh74eYDOzs4f3ci40YOwuvYCicRLmz4IsYaniMc/Tyz2KVTVz/LENf709/8b06dex8ykaFBU1ME9HH/qU+x55CjmA8rxJxKJzbRRLpfD4/Fw8OBB9u/fT3Nz88Mgdwtc12Hi9Fucee5ZFkYub0hbPP1Q2uIhHmILPqrkcKdodlMrt5Tyt4HfhnqH9Ac9oJt7EH6I65Y2fRAa418gGj2GopisTk/yxp/8Gedff5VqYhVHUVnt7Kfniz/J3/jMp2kIPZi8dblc3jTOmZubQwhBX18fX/rSlxgYGPhE+i2/Fx5KWzzEQ9w9PqoRZB7Y6j3ZDiz+qAdxpx4Ew4jT0vKTxOOfJxJ+FCE0ErPTnPzBf2P05AnSy4u4isJ0Wy+rn32SLz71KX6xpwNLvf+SR9d1mZ6e3jTOsW2bWCzG5z73Ofbu3UsgEHgA7/rjh8zqMmef/xaXXr4hbfHkz/wt+g4deSht8RAP8Q74qJLDaaBfCLENWAD+EvBXfhQvfKceBMvqoKP9rxFv/AKh4H6EUEjMzXDy+3/C2MkTJBfnQVFY7ejl7PGvU9sxxN/dvo2faoqiPwDzn1QqxfDwMMPDw2QyGUzTZGhoiKGhIdra2h6mje6A69IWZ77zLBNvv7UpbXHw6a/R3DfwYQ/vIR7iI4+PJDlsCP79A+AF6qWs/1FKefmDer136kHo7v4FGuNfwO/fgRCC9YU53vzeHzN68gTr87MIoaD1DfL2p3+SNzsG2RZr4Bf//+3de3DV9ZnH8ffDTcBgIBgCBEgEwiUonEBUUBC0iFws2O46tbtqt1t12tGpOjo7dp3ZS7ed2dk/WreXvThbt67VOu5YIUpAQKHAFq3kwsVEICDQCCSEW4BwSU6e/eOchMgJkAvk5HfO5zXDJOeXHOZ5kuE8/L6/8/t8szL46pCB9OzkC/b58+cpKyujpKSEffv2ATBmzBjmzp3LhAkTknq/5csJN9SzY9NGipuiLVIGcOuSPyM0b5GiLUTa4Yo7wQVBR1NZa09up6zs+Qv3INwwhfQb55GePo/rrx8NwLGDX7Bj00Z2btrA4f17wYxhEyZxdEKI36Rls7d3X/IG9OfZ7AzuHXxDp/4X7+7s37+fkpISysrKOH/+PGlpaYRCIaZMmULqVbpekYjqak+wdc1KSlct53Q02mLawsXk3nUPva9TtIVIazq1E1wi63vdMPr0HkxmzjdJT7+Xvn2HA3C86hAfr/5fdm7aSPXe3QBkTshlxqOP8/HI8fyotp6j9WHuGJjCv2RlMGtQSqeGwokTJ5qXjY4dO0afPn2aN84ZNWqUlo0u40jlfooLC74UbXGfoi1EOi2pzxxaOlFdxc6PNrJj00aq9kTOJIaNm8D46bNIn3Y7b9Q5r3xxmNqGRr6SdgPPZGdwa2rH3+FSX1/fvN/ynj17AMjOziYUCpGbm5v0+y1fjruzd0sxxRdHWyxcwo0js+Jdnkhg6MzhEupqT1C2/kN2btrIwYodAAwdO47ZD/8142bMpG7AIP59fzX/s6Oas42NLEpP5emsDG4Z0LH7E9ydysrK5v2Wz507R2pqKrNnzyYUCjFo0KCr2V7CqT93lvIN6xRtIdIFkno4nKw5zO9f+xUZo8cy6y/+ivEzZpI6ZCj7zpzjR/ureXN7GWGcrw0ZxPezMhh3fcfWrmtra5s3zqmpqaFXr17k5uaSl5dHVlaWNs65gpNHa9iyqjAm2mL8HbM6HVcuIq1L6mUld+dEdRUDM4YCsPP0WX62r4p3qo/RE+OhYWk8OWoIWf3aH37X0NDAjh07KC0tpaKiAndn5MiR5OXlkZubq41z2qC1aItpCx8gc+IkXYcRuQq0rHQJZsbAjKFsO1nHv+6rYvnhE/Tt0YPHMtP57qh0hl3XvnV/d2/eOGfbtm3NG+fMnDmTUCjE4MGDr1EnieNCtMVSvvisjN59+xGat4i8BYubh7iIXHtJPRx2153l73Yd4IOjtQzo2YOnszJ4bEQ6N/Zp34/l1KlTbNu2jZKSEqqrq+nZsycTJ05s3jhHy0ZXFom2WEXxinepPVzFDekZzHn0MW6++15FW4jEQVIPh95mbDtVxws3DeXbmTeS2rvtP45wOMyuXbsoKSlh165dNDY2kpmZyaJFi7j55pvp16/zKavJ4HjVIUpWFLB93WrOnzlD5oRc5jzyHcbk365oC5E4SurhMKrfdRTPmESvdkRcVFVVUVJSwtatW6mrqyMlJYXp06cTCoUYMmTINaw2cbg7X5R/SlHhhWiL8TNmMXXhEoaOyYl3eSJCkg8HoE2Doa6urnm/5YMHD9KjRw/Gjx9PKBRi7Nix2jinjZqiLYqWL6X6890Xoi3uW8SANEVbiHQnST8cLiUcDrN79+7m/ZbD4TBDhw5l/vz53HLLLdo4px0ujrZIGz6CuY89Se5ddyvaQqSb0nC4yOHDh5s3zjl16hT9+/cnPz+/eeMcabsjlfspKlxG+fq1F6Itvvs02ZPzFG0h0s1pOBDZOGf79u2UlpZSWVmJmZGTk0NeXh45OTnaOKcdmqItipYvZd/WEnr17sPEu+5m6oLFirYQCZCkftU7cuQI69ato7y8nIaGBtLT05k3bx6TJ08mJSUl3uUFSv25s5StX0vxioJItMWgNO78xiNMnjtf0RYiAZTUw8HMqKioIC8vj1AoxPDhw3XnbTudPFpD6fvL2bpmJWdPnVS0hUiCSOrhkJaWxvPPP693G3XAod27KC5c1iLaYjrTFi5RtIVIgkjq4QBoMLRDY2OYik8+orhwmaItRBJc0g8HubJzdafZvna1oi1EkoiGg1zS8UMHKVn5bmy0xa2306OHzrhEEpmGg3zJhWiLpVRs/jhyN7iiLUSSjoaDANFoiz9soGj5Mqr3RqItbn/gQULzFpGSpqhxkWSj4ZDk6mpPsHX1iki0xfFjpGWO5N7Hn2LirDmKthBJYhoOSarmT/soXlHw5WiL7z2jaAsRATQckoo3NrJ3a4miLUTkijQckkBztEXhMo4eqFS0hYhckYZDAouJtrhpDAueeo7xM2Yq2kJELkvDIQEd2r2LouVL2fnRxgvRFouWkDlB0RYi0jYaDgmiKdqiaPkyDuwoo0+/foTuu5+8+V9VtIWItJuGQ8CdqzvNtg9XUbLyPWoPV5E6JIM5jz4ejbboH+/yRCSgNBwC6vihgxSvLGD72jXUnz1D5oRJirYQkatGwyFA3J3K8u0UFy67EG1xx11MW7iEjNFj412eiCQQDYcACDfU89n/rae4sEDRFiLSJTQcujFFW4hIvGg4dEM1+/dGoi02rKOh/jzZU6Yy/3vPkDVlqt6KKiJdIi7DwcweBP4BmAjc5u6bW3ztB8B3gDDwfXd/Px41djVvbGTvlmKKCpc1R1vk3nUPUxcuZvCIUfEuT0SSTLzOHLYDXwf+s+VBM8sFHgImAcOBNWY2zt3DXV9i14hEW3xIcWGBoi1EpNuIy3Bw93KgtSWSJcCb7n4O+NzMKoDbgE1dW+G1d/JoDaUr32PrB+8r2kJEup3uds0hE/ioxePK6LEYZvYE8ATAqFHBWXY5VLGTosJlirYQkW7tmg0HM1sDtJbb8KK7L7vU01o55q19o7u/DLwMkJ+f3+r3dBeN4TAVmxVtISLBcc2Gg7vP7cDTKoGRLR6PAA5cnYq63oVoi3epPVytaAsRCYzutqxUALxhZj8hckE6B/hjfEtqv1ajLR59jDH5irYQkWCI11tZvwb8HEgHlptZqbvf5+6fmtlbQBnQADwZlHcqNUVbFC1fxu4iRVuISLCZe7derm+T/Px837x585W/8RpoqK9nxx9aRFsMuIEpcxcQmrdQ0RYi0q2ZWZG757f2te62rBQYdbUn2LK6kC2rCjl9/BiDR4zi3ieeYuJMRVuISPBpOLRTzf69FBUWUL5xLeH6erJD05i/YLGiLUQkoWg4tIE3NvL5liKKCwsi0RZ9rmPS7K8wdYGiLUQkMWk4XEb92bN8uv5DilcUcCwabTHzoUeZPHc+/QbcEO/yRESuGQ2HVpw8UkPp+++xdc1Kzp4+RcbosSx86jnGKdpCRJKEhkMLLaMtvNEZe+t0pi5crGgLEUk6ST8cGsNhKj7ZFIm22FlOn379yJsfibZIHaJoCxFJTkk9HA5V7OTdl/5Z0RYiIhdJ6uEwcOhwBg3LVLSFiMhFkno49E1J4c9f/Kd4lyEi0u30iHcBIiLS/Wg4iIhIDA0HERGJoeEgIiIxNBxERCSGhoOIiMTQcBARkRgaDiIiEiMhtgk1s8PAvk78FTcCNVepnO5CPQVHIvaViD1B4vWV5e7prX0hIYZDZ5nZ5kvtoxpU6ik4ErGvROwJErev1mhZSUREYmg4iIhIDA2HiJfjXcA1oJ6CIxH7SsSeIHH7iqFrDiIiEkNnDiIiEkPDQUREYiT1cDCz+Wa2w8wqzOyFeNfTUWb2iplVm9n2FsfSzGy1me2KfhwUzxrby8xGmtlaMys3s0/N7Ono8cD2ZWZ9zeyPZrYl2tM/Ro8HtqcmZtbTzErM7L3o40Toaa+ZbTOzUjPbHD0W+L7aKmmHg5n1BH4JLABygW+aWW58q+qwXwPzLzr2AvCBu+cAH0QfB0kD8Jy7TwSmA09Gfz9B7usccI+7TwFCwHwzm06we2ryNFDe4nEi9ARwt7uHWtzbkCh9XVHSDgfgNqDC3fe4+3ngTWBJnGvqEHdfDxy96PAS4NXo568CD3RlTZ3l7gfdvTj6+UkiLzyZBLgvjzgVfdg7+scJcE8AZjYCWAT8V4vDge7pMhK1rxjJPBwygT+1eFwZPZYoMtz9IEReaIEhca6nw8wsG8gDPibgfUWXX0qBamC1uwe+J+Al4G+AxhbHgt4TRAb3KjMrMrMnoscSoa826RXvAuLIWjmm9/V2M2aWArwNPOPutWat/dqCw93DQMjMBgLvmNnNcS6pU8zsfqDa3YvMbE6cy7na7nT3A2Y2BFhtZp/Fu6CulMxnDpXAyBaPRwAH4lTLtVBlZsMAoh+r41xPu5lZbyKD4XV3/130cOD7AnD348A6IteKgtzTncBiM9tLZGn2HjP7DcHuCQB3PxD9WA28Q2QpOvB9tVUyD4dPgBwzu8nM+gAPAQVxrulqKgC+Ff38W8CyONbSbhY5RfgVUO7uP2nxpcD2ZWbp0TMGzKwfMBf4jAD35O4/cPcR7p5N5N/Qh+7+MAHuCcDMrjezAU2fA/OA7QS8r/ZI6jukzWwhkfXSnsAr7v7j+FbUMWb2W2AOkTjhKuDvgaXAW8AoYD/woLtffNG62zKzmcAGYBsX1rL/lsh1h0D2ZWaTiVzE7EnkP2ZvufsPzWwwAe2ppeiy0vPufn/QezKz0UTOFiCy/P6Gu/846H21R1IPBxERaV0yLyuJiMglaDiIiEgMDQcREYmh4SAiIjE0HEREJEYy3yEt0iFmFibyFtveRAICXwVecvfGyz5RJEA0HETa74y7hwCi0QpvAKlE7i8RSQhaVhLphGi0whPAUxaRbWYbzKw4+ucOADN7zcyaU3/N7HUzW2xmk6J7PJSa2VYzy4lXLyIt6SY4kXYys1PunnLRsWPABOAk0OjuZ6Mv9L9193wzmw086+4PmFkqUArkAD8FPnL316MxLj3d/UyXNiTSCi0riVwdTXGxvYFfmFkICAPjANz992b2y+gy1NeBt929wcw2AS9G90T4nbvvikPtIjG0rCTSSdEcnjCRhM5nieRbTQHygT4tvvU14C+BbwP/DeDubwCLgTPA+2Z2T9dVLnJpGg4inWBm6cB/AL/wyBptKnAw+s6lR4iE7DX5NfAMgLt/Gn3+aGCPu/+MSOLn5C4rXuQytKwk0n79oru5Nb2V9TWgKVb834C3zexBYC1wuulJ7l5lZuVEEnObfAN42MzqgUPAD6959SJtoAvSIl3EzPoTuT9iqrufiHc9IpejZSWRLmBmTRv7/FyDQYJAZw4iIhJDZw4iIhJDw0FERGJoOIiISAwNBxERiaHhICIiMf4fN4njRgLSzO0AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.ylabel(\"Temperature C°\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    plt.plot([0,NUMBER_DAYS],[getDataByFieldAndIndex(1,i).astype(np.float).flatten()[0],getDataByFieldAndIndex(1,i).astype(np.float).flatten()[NUMBER_DAYS-1]])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Mean and Median of Temperatures across all Tornados "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 253,
    "metadata": {},
    "outputs": [
     {
-     "ename": "TypeError",
-     "evalue": "Image data of dtype object cannot be converted to float",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-108-0500433780e9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgetAllDataByField\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36mimshow\u001b[1;34m(X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, filternorm, filterrad, resample, url, data, **kwargs)\u001b[0m\n\u001b[0;32m   2722\u001b[0m         \u001b[0mfilternorm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilterrad\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m4.0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresample\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2723\u001b[0m         data=None, **kwargs):\n\u001b[1;32m-> 2724\u001b[1;33m     __ret = gca().imshow(\n\u001b[0m\u001b[0;32m   2725\u001b[0m         \u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcmap\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcmap\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnorm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnorm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maspect\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maspect\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2726\u001b[0m         \u001b[0minterpolation\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minterpolation\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0malpha\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvmin\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvmin\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\__init__.py\u001b[0m in \u001b[0;36minner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1445\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1446\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1447\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1448\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1449\u001b[0m         \u001b[0mbound\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\axes\\_axes.py\u001b[0m in \u001b[0;36mimshow\u001b[1;34m(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, filternorm, filterrad, resample, url, **kwargs)\u001b[0m\n\u001b[0;32m   5521\u001b[0m                               resample=resample, **kwargs)\n\u001b[0;32m   5522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 5523\u001b[1;33m         \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5524\u001b[0m         \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_alpha\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0malpha\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5525\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_clip_path\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\image.py\u001b[0m in \u001b[0;36mset_data\u001b[1;34m(self, A)\u001b[0m\n\u001b[0;32m    700\u001b[0m         if (self._A.dtype != np.uint8 and\n\u001b[0;32m    701\u001b[0m                 not np.can_cast(self._A.dtype, float, \"same_kind\")):\n\u001b[1;32m--> 702\u001b[1;33m             raise TypeError(\"Image data of dtype {} cannot be converted to \"\n\u001b[0m\u001b[0;32m    703\u001b[0m                             \"float\".format(self._A.dtype))\n\u001b[0;32m    704\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: Image data of dtype object cannot be converted to float"
-     ]
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
     },
     {
      "data": {
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -134,48 +247,95 @@
     }
    ],
    "source": [
-    "plt.imshow(getAllDataByField(0))\n",
+    "#Reshape array into 2D\n",
+    "arr2d = np.reshape(getAllDataByField(1), (-1, NUMBER_DAYS)).astype(np.float)\n",
+    "\n",
+    "#Mean\n",
+    "arrmean = np.mean(arr2d,axis=0)\n",
+    "plt.plot(np.arange(NUMBER_DAYS),arrmean)\n",
+    "plt.title(\"Mean\")\n",
+    "plt.ylabel(\"Temperature (C°)\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "plt.show()\n",
+    "\n",
+    "#Median\n",
+    "arrmedian = np.median(arr2d,axis=0)\n",
+    "plt.plot(np.arange(NUMBER_DAYS),arrmedian)\n",
+    "plt.title(\"Median\")\n",
+    "plt.ylabel(\"Temperature (C°)\")\n",
+    "plt.xlabel(\"Days\")\n",
     "plt.show()"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "wooden-receptor",
    "metadata": {},
    "source": [
-    "## Histogram"
+    "### Net Positive Temperatures vs Net Negative Temperatures"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "id": "least-permit",
+   "execution_count": 254,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "(array([5.0000e+00, 2.6000e+01, 1.2400e+02, 4.7400e+02, 1.3770e+03,\n",
-       "        3.3890e+03, 6.5770e+03, 1.1149e+04, 1.5483e+04, 1.7187e+04,\n",
-       "        1.6161e+04, 1.2524e+04, 8.1070e+03, 4.4260e+03, 1.9920e+03,\n",
-       "        6.9700e+02, 2.3000e+02, 6.1000e+01, 1.0000e+01, 1.0000e+00]),\n",
-       " array([0.44937032, 0.91990838, 1.39044644, 1.8609845 , 2.33152256,\n",
-       "        2.80206062, 3.27259868, 3.74313675, 4.21367481, 4.68421287,\n",
-       "        5.15475093, 5.62528899, 6.09582705, 6.56636511, 7.03690317,\n",
-       "        7.50744123, 7.97797929, 8.44851735, 8.91905541, 9.38959347,\n",
-       "        9.86013153]),\n",
-       " <BarContainer object of 20 artists>)"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 4,
      "metadata": {},
-     "output_type": "execute_result"
-    },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "labels = ['Net Increase in temperature','Net Decrease in temperature']\n",
+    "sizes = [0,0]\n",
+    "explode = (.5,0)\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    \n",
+    "    #If temperature increased approaching day of Tornado\n",
+    "    if(getDataByFieldAndIndex(1,i).astype(np.float).flatten()[NUMBER_DAYS-1] - getDataByFieldAndIndex(1,i).astype(np.float).flatten()[0] > 0):\n",
+    "        sizes[0] += 1\n",
+    "    else:\n",
+    "        sizes[1] += 1\n",
+    "\n",
+    "fig1, ax1 = plt.subplots()\n",
+    "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
+    "        shadow=True, startangle=90)\n",
+    "plt.show()\n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Wind"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Linear graph of Wind speeds for all Tornados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 255,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
      "metadata": {
@@ -185,28 +345,152 @@
     }
    ],
    "source": [
-    "N_points = 100000\n",
-    "n_bins = 20\n",
+    "plt.ylabel(\"Wind speed (m/s)\")\n",
+    "plt.xlabel(\"Days\")\n",
     "\n",
-    "MAX_VAL = 100\n",
-    "# Generate a normal distribution, center at x=0 and y=5\n",
-    "x = np.random.randn(N_points)\n",
-    "y = MAX_VALUE\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(2,i).astype(np.float).flatten())\n",
+    "    \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Linear graph of Net speeds for all Tornados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 256,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.ylabel(\"Wind speed (m/s)\")\n",
+    "plt.xlabel(\"Days\")\n",
     "\n",
-    "fig, axs = plt.subplots(1, 2, sharey=True, tight_layout=True)\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    plt.plot([0,NUMBER_DAYS],[getDataByFieldAndIndex(2,i).astype(np.float).flatten()[0],getDataByFieldAndIndex(2,i).astype(np.float).flatten()[NUMBER_DAYS-1]])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Mean and Median of Wind Speeds across all Tornados "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 257,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Reshape array into 2D\n",
+    "arr2d = np.reshape(getAllDataByField(2), (-1, NUMBER_DAYS)).astype(np.float)\n",
     "\n",
-    "# We can set the number of bins with the `bins` kwarg\n",
-    "axs[0].hist(x, bins=n_bins)\n",
-    "axs[1].hist(y, bins=n_bins)"
+    "#Mean\n",
+    "arrmean = np.mean(arr2d,axis=0)\n",
+    "plt.plot(np.arange(NUMBER_DAYS),arrmean)\n",
+    "plt.title(\"Mean\")\n",
+    "plt.ylabel(\"Wind Speed (m/s)\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "plt.show()\n",
+    "\n",
+    "#Median\n",
+    "arrmedian = np.median(arr2d,axis=0)\n",
+    "plt.plot(np.arange(NUMBER_DAYS),arrmedian)\n",
+    "plt.title(\"Median\")\n",
+    "plt.ylabel(\"Wind Speed (m/s)\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Net Positive speeds vs Net Negative speeds"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "aquatic-dallas",
+   "execution_count": 258,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "labels = ['Net Increase in wind speed','Net Decrease in wind speed']\n",
+    "sizes = [0,0]\n",
+    "explode = (.5,0)\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    \n",
+    "    #If temperature increased approaching day of Tornado\n",
+    "    if(getDataByFieldAndIndex(2,i).astype(np.float).flatten()[NUMBER_DAYS-1] - getDataByFieldAndIndex(2,i).astype(np.float).flatten()[0] > 0):\n",
+    "        sizes[0] += 1\n",
+    "    else:\n",
+    "        sizes[1] += 1\n",
+    "\n",
+    "fig1, ax1 = plt.subplots()\n",
+    "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
+    "        shadow=True, startangle=90)\n",
+    "plt.show()"
+   ]
   }
  ],
  "metadata": {
@@ -225,7 +509,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.2"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

From c23a27cc9d8f13cd34a7379fbb20277896e2dd3a Mon Sep 17 00:00:00 2001
From: Alvaro Carrascosa <varocarras@gmail.com>
Date: Wed, 3 Mar 2021 03:42:35 -0500
Subject: [PATCH 30/38] Update Graphing.ipynb

Added comments and extra lines on Median/Mean graphs
---
 .../Deliverable_2/Graphing.ipynb              | 80 ++++++++++++-------
 1 file changed, 49 insertions(+), 31 deletions(-)

diff --git a/NaturalDisasterProject/Deliverable_2/Graphing.ipynb b/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
index 995a1e93..fdbd0eab 100644
--- a/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
+++ b/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
@@ -7,19 +7,23 @@
     "# Graphs"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 222,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib inline \n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "from matplotlib import colors\n",
-    "from matplotlib.ticker import PercentFormatter"
+    "import pandas as pd\n"
    ]
   },
   {
@@ -31,13 +35,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 239,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [],
    "source": [
-    "NUMBER_TORNADOS = 108 #Number of Tornados\n",
+    "NUMBER_TORNADOS = 108 #Number of Tornado Events\n",
     "NUMBER_DAYS = 57 #Number of days of data per Tornado\n",
-    "FILE_NAME = \"historical_data_fin.csv\""
+    "FILE_NAME = \"historical_data_fin.csv\" #CSV file that contains the data\n"
    ]
   },
   {
@@ -49,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 240,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -79,19 +83,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 241,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [],
    "source": [
+    "#Returns all elements of all Tornadoes for a specific field (0-8)\n",
     "def getAllDataByField(field): \n",
     "    \n",
     "    return numData[1:,field:field+1]\n",
     "\n",
-    "#Returns elements of a given field (0-8) for a particular event (0-107)\n",
+    "#Returns elements of a given field (0-8) for a particular Tornado (0-107)\n",
     "def getDataByFieldAndIndex(field, event):\n",
     "    \n",
-    "    return numData[1+(NUMBER_DAYS*event):(NUMBER_DAYS*(event+1)+1),field:field+1]\n",
-    "\n"
+    "    return numData[1+(NUMBER_DAYS*event):(NUMBER_DAYS*(event+1)+1),field:field+1]\n"
    ]
   },
   {
@@ -104,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 242,
+   "execution_count": 67,
    "metadata": {
     "scrolled": false
    },
@@ -146,7 +150,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 243,
+   "execution_count": 68,
    "metadata": {
     "scrolled": true
    },
@@ -170,7 +174,7 @@
     "\n",
     "for i in range(NUMBER_TORNADOS):\n",
     "    plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(1,i).astype(np.float).flatten())\n",
-    "plt.show()\n"
+    "plt.show()"
    ]
   },
   {
@@ -182,7 +186,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 244,
+   "execution_count": 69,
    "metadata": {
     "scrolled": false
    },
@@ -218,12 +222,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 253,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -235,7 +239,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -253,6 +257,8 @@
     "#Mean\n",
     "arrmean = np.mean(arr2d,axis=0)\n",
     "plt.plot(np.arange(NUMBER_DAYS),arrmean)\n",
+    "plt.plot([0,NUMBER_DAYS-1],[arrmean[0],arrmean[NUMBER_DAYS-1]])\n",
+    "\n",
     "plt.title(\"Mean\")\n",
     "plt.ylabel(\"Temperature (C°)\")\n",
     "plt.xlabel(\"Days\")\n",
@@ -261,6 +267,8 @@
     "#Median\n",
     "arrmedian = np.median(arr2d,axis=0)\n",
     "plt.plot(np.arange(NUMBER_DAYS),arrmedian)\n",
+    "plt.plot([0,NUMBER_DAYS-1],[arrmedian[0],arrmedian[NUMBER_DAYS-1]])\n",
+    "\n",
     "plt.title(\"Median\")\n",
     "plt.ylabel(\"Temperature (C°)\")\n",
     "plt.xlabel(\"Days\")\n",
@@ -276,7 +284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 254,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [
     {
@@ -306,15 +314,14 @@
     "fig1, ax1 = plt.subplots()\n",
     "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
     "        shadow=True, startangle=90)\n",
-    "plt.show()\n",
-    "        "
+    "plt.show()     "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Wind"
+    "## Wind Speed"
    ]
   },
   {
@@ -326,7 +333,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 255,
+   "execution_count": 72,
    "metadata": {
     "scrolled": true
    },
@@ -363,7 +370,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 256,
+   "execution_count": 73,
    "metadata": {
     "scrolled": true
    },
@@ -399,14 +406,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 257,
+   "execution_count": 74,
    "metadata": {
-    "scrolled": true
+    "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -418,7 +425,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -436,6 +443,8 @@
     "#Mean\n",
     "arrmean = np.mean(arr2d,axis=0)\n",
     "plt.plot(np.arange(NUMBER_DAYS),arrmean)\n",
+    "plt.plot([0,NUMBER_DAYS-1],[arrmean[0],arrmean[NUMBER_DAYS-1]])\n",
+    "\n",
     "plt.title(\"Mean\")\n",
     "plt.ylabel(\"Wind Speed (m/s)\")\n",
     "plt.xlabel(\"Days\")\n",
@@ -444,6 +453,8 @@
     "#Median\n",
     "arrmedian = np.median(arr2d,axis=0)\n",
     "plt.plot(np.arange(NUMBER_DAYS),arrmedian)\n",
+    "plt.plot([0,NUMBER_DAYS-1],[arrmedian[0],arrmedian[NUMBER_DAYS-1]])\n",
+    "\n",
     "plt.title(\"Median\")\n",
     "plt.ylabel(\"Wind Speed (m/s)\")\n",
     "plt.xlabel(\"Days\")\n",
@@ -459,7 +470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 258,
+   "execution_count": 75,
    "metadata": {},
    "outputs": [
     {
@@ -491,6 +502,13 @@
     "        shadow=True, startangle=90)\n",
     "plt.show()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

From e5fb831c2c219b647eb1eda544e2046e58b19adc Mon Sep 17 00:00:00 2001
From: Alvaro Carrascosa <varocarras@gmail.com>
Date: Wed, 3 Mar 2021 03:47:19 -0500
Subject: [PATCH 31/38] Delete .ipnyb checkpoints

---
 .../Graphing-checkpoint.ipynb                 | 233 ------------------
 1 file changed, 233 deletions(-)
 delete mode 100644 NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb

diff --git a/NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb b/NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb
deleted file mode 100644
index 71ec896e..00000000
--- a/NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb
+++ /dev/null
@@ -1,233 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "favorite-concept",
-   "metadata": {},
-   "source": [
-    "# Graphing function"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 103,
-   "id": "transparent-shoulder",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%matplotlib inline \n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "from matplotlib import colors\n",
-    "from matplotlib.ticker import PercentFormatter"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "african-reproduction",
-   "metadata": {},
-   "source": [
-    "## Global Values"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "killing-redhead",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "id": "miniature-timer",
-   "metadata": {},
-   "source": [
-    "## Loading Data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 104,
-   "id": "framed-dispatch",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Field 0: 'datatime'\n",
-    "#Field 1: 'temperature'\n",
-    "#Field 2: 'windspeed'\n",
-    "#Field 3: 'surface solar radiation'\n",
-    "#Field 4: 'relative humidity'\n",
-    "#Field 5: 'surface pressure'\n",
-    "#Field 6: 'total precipitation'\n",
-    "#Field 7: 'latitude'\n",
-    "#Field 8: 'longitude'\n",
-    "\n",
-    "\n",
-    "data = pd.read_csv (\"historical_data_fin.csv\",header=None)\n",
-    "\n",
-    "#Take data to numPy\n",
-    "numData = data.to_numpy()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "working-transsexual",
-   "metadata": {},
-   "source": [
-    "## Helper functions"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 105,
-   "id": "unnecessary-forest",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def getAllDataByField(field): \n",
-    "    return numData[1:,field:field+1]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "average-prime",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 108,
-   "id": "incorporate-cowboy",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "Image data of dtype object cannot be converted to float",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-108-0500433780e9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgetAllDataByField\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36mimshow\u001b[1;34m(X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, filternorm, filterrad, resample, url, data, **kwargs)\u001b[0m\n\u001b[0;32m   2722\u001b[0m         \u001b[0mfilternorm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilterrad\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m4.0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresample\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2723\u001b[0m         data=None, **kwargs):\n\u001b[1;32m-> 2724\u001b[1;33m     __ret = gca().imshow(\n\u001b[0m\u001b[0;32m   2725\u001b[0m         \u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcmap\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcmap\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnorm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnorm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maspect\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maspect\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2726\u001b[0m         \u001b[0minterpolation\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minterpolation\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0malpha\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvmin\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvmin\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\__init__.py\u001b[0m in \u001b[0;36minner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1445\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1446\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1447\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1448\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1449\u001b[0m         \u001b[0mbound\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\axes\\_axes.py\u001b[0m in \u001b[0;36mimshow\u001b[1;34m(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, filternorm, filterrad, resample, url, **kwargs)\u001b[0m\n\u001b[0;32m   5521\u001b[0m                               resample=resample, **kwargs)\n\u001b[0;32m   5522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 5523\u001b[1;33m         \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5524\u001b[0m         \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_alpha\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0malpha\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5525\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_clip_path\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mc:\\users\\alvar\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\matplotlib\\image.py\u001b[0m in \u001b[0;36mset_data\u001b[1;34m(self, A)\u001b[0m\n\u001b[0;32m    700\u001b[0m         if (self._A.dtype != np.uint8 and\n\u001b[0;32m    701\u001b[0m                 not np.can_cast(self._A.dtype, float, \"same_kind\")):\n\u001b[1;32m--> 702\u001b[1;33m             raise TypeError(\"Image data of dtype {} cannot be converted to \"\n\u001b[0m\u001b[0;32m    703\u001b[0m                             \"float\".format(self._A.dtype))\n\u001b[0;32m    704\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: Image data of dtype object cannot be converted to float"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.imshow(getAllDataByField(0))\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "wooden-receptor",
-   "metadata": {},
-   "source": [
-    "## Histogram"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "least-permit",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(array([5.0000e+00, 2.6000e+01, 1.2400e+02, 4.7400e+02, 1.3770e+03,\n",
-       "        3.3890e+03, 6.5770e+03, 1.1149e+04, 1.5483e+04, 1.7187e+04,\n",
-       "        1.6161e+04, 1.2524e+04, 8.1070e+03, 4.4260e+03, 1.9920e+03,\n",
-       "        6.9700e+02, 2.3000e+02, 6.1000e+01, 1.0000e+01, 1.0000e+00]),\n",
-       " array([0.44937032, 0.91990838, 1.39044644, 1.8609845 , 2.33152256,\n",
-       "        2.80206062, 3.27259868, 3.74313675, 4.21367481, 4.68421287,\n",
-       "        5.15475093, 5.62528899, 6.09582705, 6.56636511, 7.03690317,\n",
-       "        7.50744123, 7.97797929, 8.44851735, 8.91905541, 9.38959347,\n",
-       "        9.86013153]),\n",
-       " <BarContainer object of 20 artists>)"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEYCAYAAAAJeGK1AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAXI0lEQVR4nO3df6zldX3n8edrh2KN1TLILaUMdNAdTdTdHXGC7NYadqkwgnFw07hDsmVU4kiERNMm7lA3i7FLMra17ppYDOpESJUfFSkTHYsj6667yaIMiPxSyoBDmMnATMFKu25ose/943wuexjvzL3eczj3c+c8H8nJ/Z7399fnnvOded3P53zu96aqkCSpN/9kqRsgSdJcDChJUpcMKElSlwwoSVKXDChJUpeOWeoGLNYJJ5xQq1evXupmSAt25513/nVVzYzjWF7/Wm4Wc/0v24BavXo1u3btWupmSAuW5NFxHcvrX8vNYq5/h/gkSV0yoCRJXTKgJEldMqAkSV0yoCRJXTKgJEldMqAkSV0yoCRJXTKgJEldMqAkSV2a91ZHSbYBbwMOVNXrWu0G4NVtk+OAv6mqtUlWA98HHmzrbq+qS9o+bwA+D7wY2AF8oKoqyfHADcBqYA/wzqr60Ri+Ny3S6i1fPeL6PVvPn1BLJE2zhfSgPg+sHy5U1b+rqrVVtRa4Cfjy0OqHZ9fNhlNzFfBeYE17zB5zC3BbVa0BbmvPJUlTbt6AqqpvAU/NtS5JgHcC1x3pGElOAl5WVbdXVQHXAhe01RuAa9ryNUN1SdIUG/UzqN8Enqiqh4ZqpyX5bpL/keQ3W+1kYO/QNntbDeDEqtrflh8HThyxTZKko8Cof27jQp7fe9oPnFpVT7bPnP4iyWsXerD2mVQdbn2SzcBmgFNPPXWRTZaWJ69/TZtF96CSHAP8WwYTHACoqmeq6sm2fCfwMPAqYB+wamj3Va0G8EQbApwdCjxwuHNW1dVVta6q1s3MjOXvvknLhte/ps0oQ3y/Bfygqp4buksyk2RFW34Fg8kQj7QhvKeTnNk+t7oIuKXtth3Y1JY3DdUlSVNs3oBKch3wv4FXJ9mb5OK2aiM/OznizcA9Se4GvgRcUlWzEyzeD3wW2M2gZ/W1Vt8KvCXJQwxCb+vivx1J0tFi3s+gqurCw9TfNUftJgbTzufafhfwujnqTwJnz9cOSRoHf89v+fBOEpKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQujXonCS1D881ikqQe2IOSJHXJgJIkdcmAkiR1yYCSJHXJgJIkdcmAkiR1yWnmkjTkSL+G4Y1kJ8selCSpSwaUJKlLBpQkqUsGlCSpSwaUJKlLBpQkqUsGlCSpSwaUJKlLBpQkqUveSUI/N3/TXj3zD3IePexBSZK6ZEBJkro0b0Al2ZbkQJL7hmofSbIvyd3tcd7QusuT7E7yYJJzh+rrW213ki1D9dOSfLvVb0hy7Di/QUnS8rSQHtTngfVz1D9RVWvbYwdAktcAG4HXtn3+NMmKJCuATwFvBV4DXNi2BfhYO9Y/BX4EXDzKNyRJOjrMG1BV9S3gqQUebwNwfVU9U1U/BHYDZ7TH7qp6pKr+Hrge2JAkwL8BvtT2vwa44Of7FiRJR6NRPoO6LMk9bQhwZaudDDw2tM3eVjtc/eXA31TVs4fU55Rkc5JdSXYdPHhwhKZLy4/Xv6bNYgPqKuCVwFpgP/DxcTXoSKrq6qpaV1XrZmZmJnFKqRte/5o2i/o9qKp6YnY5yWeAr7Sn+4BThjZd1Wocpv4kcFySY1ovanh7SdIUW1QPKslJQ0/fAczO8NsObEzyoiSnAWuA7wB3AGvajL1jGUyk2F5VBXwT+O22/ybglsW0SZJ0dJm3B5XkOuAs4IQke4ErgLOSrAUK2AO8D6Cq7k9yI/AA8CxwaVX9tB3nMuBWYAWwrarub6f4D8D1Sf4z8F3gc+P65iRJy9e8AVVVF85RPmyIVNWVwJVz1HcAO+aoP8Jglp8kSc/xThKSpC4ZUJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQuGVCSpC4ds9QN0Pit3vLVpW6CJI3MHpQkqUvzBlSSbUkOJLlvqPZHSX6Q5J4kNyc5rtVXJ/m/Se5uj08P7fOGJPcm2Z3kk0nS6scn2ZnkofZ15QvwfUqSlpmF9KA+D6w/pLYTeF1V/XPgr4DLh9Y9XFVr2+OSofpVwHuBNe0xe8wtwG1VtQa4rT2XJE25eQOqqr4FPHVI7etV9Wx7ejuw6kjHSHIS8LKqur2qCrgWuKCt3gBc05avGapLkqbYOCZJvAe4Yej5aUm+CzwN/Meq+p/AycDeoW32thrAiVW1vy0/Dpx4uBMl2QxsBjj11FPH0HRp+fD6X3rzTUDas/X8CbVkOow0SSLJh4FngS+00n7g1Kp6PfC7wBeTvGyhx2u9qzrC+qural1VrZuZmRmh5dLy4/WvabPoHlSSdwFvA85uwUJVPQM805bvTPIw8CpgH88fBlzVagBPJDmpqva3ocADi22TJOnosageVJL1wIeAt1fVT4bqM0lWtOVXMJgM8Ugbwns6yZlt9t5FwC1tt+3Apra8aaguSZpi8/agklwHnAWckGQvcAWDWXsvAna22eK3txl7bwY+muQfgH8ELqmq2QkW72cwI/DFwNfaA2ArcGOSi4FHgXeO5TuTJC1r8wZUVV04R/lzh9n2JuCmw6zbBbxujvqTwNnztUOSNF28k4QkqUsGlCSpSwaUJKlLBpQkqUsGlCSpSwaUJKlLBpQkqUsGlCSpSwaUJKlLBpQkqUsGlCSpSwaUJKlLBpQkqUvj+JPvkjQx8/3ZdR097EFJkrpkQEmSumRASZK65GdQGqv5Ph/Ys/X8CbVE0nJnD0qS1CUDSpLUJQNKktQlA0qS1CUDSpLUJQNKktQlA0qS1KUFBVSSbUkOJLlvqHZ8kp1JHmpfV7Z6knwyye4k9yQ5fWifTW37h5JsGqq/Icm9bZ9PJsk4v0lJ0vKz0B7U54H1h9S2ALdV1RrgtvYc4K3AmvbYDFwFg0ADrgDeCJwBXDEbam2b9w7td+i5JElTZkEBVVXfAp46pLwBuKYtXwNcMFS/tgZuB45LchJwLrCzqp6qqh8BO4H1bd3Lqur2qirg2qFjSZKm1CifQZ1YVfvb8uPAiW35ZOCxoe32ttqR6nvnqP+MJJuT7Eqy6+DBgyM0XVp+vP41bcYySaL1fGocx5rnPFdX1bqqWjczM/NCn07qite/ps0oAfVEG56jfT3Q6vuAU4a2W9VqR6qvmqMuSZpiowTUdmB2Jt4m4Jah+kVtNt+ZwI/bUOCtwDlJVrbJEecAt7Z1Tyc5s83eu2joWJKkKbWgP7eR5DrgLOCEJHsZzMbbCtyY5GLgUeCdbfMdwHnAbuAnwLsBquqpJH8A3NG2+2hVzU68eD+DmYIvBr7WHpKkKbaggKqqCw+z6uw5ti3g0sMcZxuwbY76LuB1C2mLJGk6eCcJSVKXDChJUpcMKElSlwwoSVKXDChJUpcMKElSlwwoSVKXDChJUpcMKElSlwwoSVKXDChJUpcMKElSlwwoSVKXDChJUpcMKElSlwwoSVKXDChJUpcMKElSlxb0J9/Vl9VbvrrUTZCkF5wBJUljMt8Pj3u2nj+hlhwdHOKTJHXJgJIkdcmAkiR1yYCSJHVp0QGV5NVJ7h56PJ3kg0k+kmTfUP28oX0uT7I7yYNJzh2qr2+13Um2jPpNSZKWv0XP4quqB4G1AElWAPuAm4F3A5+oqj8e3j7Ja4CNwGuBXwO+keRVbfWngLcAe4E7kmyvqgcW2zZJ0vI3rmnmZwMPV9WjSQ63zQbg+qp6Bvhhkt3AGW3d7qp6BCDJ9W1bA0qSpti4PoPaCFw39PyyJPck2ZZkZaudDDw2tM3eVjtc/Wck2ZxkV5JdBw8eHFPTpeXB61/TZuSASnIs8Hbgz1vpKuCVDIb/9gMfH/Ucs6rq6qpaV1XrZmZmxnVYaVnw+te0GccQ31uBu6rqCYDZrwBJPgN8pT3dB5wytN+qVuMIdUnSlBrHEN+FDA3vJTlpaN07gPva8nZgY5IXJTkNWAN8B7gDWJPktNYb29i2lSRNsZF6UElewmD23fuGyn+YZC1QwJ7ZdVV1f5IbGUx+eBa4tKp+2o5zGXArsALYVlX3j9IuSdLyN1JAVdX/AV5+SO13jrD9lcCVc9R3ADtGaYsk6ejinSQkSV0yoCRJXTKgJEldMqAkSV0yoCRJXTKgJEldMqAkSV0a193MJWksVm/56lI3QZ2wByVJ6pIBJUnqkkN8mqj5hm/2bD1/Qi2R1Dt7UJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQuGVCSpC4ZUJKkLhlQkqQujRxQSfYkuTfJ3Ul2tdrxSXYmeah9XdnqSfLJJLuT3JPk9KHjbGrbP5Rk06jtkiQtb+PqQf3rqlpbVeva8y3AbVW1BritPQd4K7CmPTYDV8Eg0IArgDcCZwBXzIaaJGk6vVBDfBuAa9ryNcAFQ/Vra+B24LgkJwHnAjur6qmq+hGwE1j/ArVNkrQMjCOgCvh6kjuTbG61E6tqf1t+HDixLZ8MPDa0795WO1z9eZJsTrIrya6DBw+OoenS8uH1r2kzjoB6U1WdzmD47tIkbx5eWVXFIMRGVlVXV9W6qlo3MzMzjkNKy4bXv6bNyAFVVfva1wPAzQw+Q3qiDd3Rvh5om+8DThnafVWrHa4uSZpSIwVUkpckeensMnAOcB+wHZidibcJuKUtbwcuarP5zgR+3IYCbwXOSbKyTY44p9UkSVPqmBH3PxG4Ocnssb5YVX+Z5A7gxiQXA48C72zb7wDOA3YDPwHeDVBVTyX5A+COtt1Hq+qpEdsmSVrGRgqoqnoE+Bdz1J8Ezp6jXsClhznWNmDbKO2RJB09vJOEJKlLBpQkqUujfgYlSVqg1Vu+esT1e7aeP6GWLA8GVIfmu4glaRo4xCdJ6pIBJUnqkgElSeqSASVJ6pIBJUnqkgElSeqSASVJ6pIBJUnqkgElSeqSASVJ6pIBJUnqkvfikzRR3mtSC2UPSpLUJQNKktQlA0qS1CUDSpLUJSdJqCv+xVFJs+xBSZK6ZEBJkrpkQEmSurTogEpySpJvJnkgyf1JPtDqH0myL8nd7XHe0D6XJ9md5MEk5w7V17fa7iRbRvuWJElHg1EmSTwL/F5V3ZXkpcCdSXa2dZ+oqj8e3jjJa4CNwGuBXwO+keRVbfWngLcAe4E7kmyvqgdGaJskaZlbdEBV1X5gf1v+2yTfB04+wi4bgOur6hngh0l2A2e0dbur6hGAJNe3bQ0oSZpiY/kMKslq4PXAt1vpsiT3JNmWZGWrnQw8NrTb3lY7XH2u82xOsivJroMHD46j6dKy4fWvaTNyQCX5JeAm4INV9TRwFfBKYC2DHtbHRz3HrKq6uqrWVdW6mZmZcR1WWha8/jVtRvpF3SS/wCCcvlBVXwaoqieG1n8G+Ep7ug84ZWj3Va3GEeqSpCk1yiy+AJ8Dvl9VfzJUP2los3cA97Xl7cDGJC9KchqwBvgOcAewJslpSY5lMJFi+2LbJUk6OozSg/oN4HeAe5Pc3Wq/D1yYZC1QwB7gfQBVdX+SGxlMfngWuLSqfgqQ5DLgVmAFsK2q7h+hXZKko8Aos/j+F5A5Vu04wj5XAlfOUd9xpP0kSdPHO0lIkrrk3cwlqRPezf/57EFJkrpkD2oJzPdTkiTJHpQkqVMGlCSpSwaUJKlLBpQkqUsGlCSpS87ikzRWzlLVuNiDkiR1yYCSJHXJIT4tK94KRpoe9qAkSV0yoCRJXTKgJEldMqAkSV0yoCRJXXIWnyQtE9M2i9WAegH4m/SSNDqH+CRJXbIHJenn4giBJsUelCSpS/agdFSZtg+RpaOZPShJUpe66UElWQ/8V2AF8Nmq2rrETTosx+Al9ehoG0HoIqCSrAA+BbwF2AvckWR7VT2wtC3T0eZo+wf8QvAHMPWii4ACzgB2V9UjAEmuBzYASxJQ/gPV0c5rfDottx/Qegmok4HHhp7vBd546EZJNgOb29O/S/LgmM5/AvDXYzrWqGzL3CbSlnxsQZstti2/voh9nnPI9f9MkvtGOd6E9HQNHYntZMHX/0LM1c6f+/rvJaAWpKquBq4e93GT7KqqdeM+7mLYlrnZludf/z29HkdiO8dr2trZyyy+fcApQ89XtZokaUr1ElB3AGuSnJbkWGAjsH2J2yRJWkJdDPFV1bNJLgNuZTDNfFtV3T/BJox92HAEtmVutuX5emjDQtjO8ZqqdqaqxnEcSZLGqpchPkmSnseAkiR1yYAakuT3klSSE5a4HX+U5AdJ7klyc5LjJnz+9UkeTLI7yZZJnnuOtpyS5JtJHkhyf5IPLHF7ViT5bpKvTOh8R3wvkrwoyQ1t/beTrJ5Euw5pw7zvUZKzkvw4yd3t8Z8m3c7Wjj1J7m1t2DXH+iT5ZHs970ly+hK08dVDr9PdSZ5O8sFDtlmS1zPJtiQHhn8HL8nxSXYmeah9XXmYfTe1bR5KsmlBJ6wqH4PP4U5hMEnjUeCEJW7LOcAxbfljwMcmeO4VwMPAK4Bjge8Br1nC1+Ik4PS2/FLgr5a4Pb8LfBH4Sg/vBfB+4NNteSNwQ4/vEXDWJF6zBbR1z5H+fQPnAV8DApwJfHuJ27sCeBz49R5eT+DNwOnAfUO1PwS2tOUtc/1/BRwPPNK+rmzLK+c7nz2o/+8TwIeAJZ81UlVfr6pn29PbGfxe2KQ8d9upqvp7YPa2U0uiqvZX1V1t+W+B7zO488jEJVkFnA98dkKnXMh7sQG4pi1/CTg7SSbUPqCv92gMNgDX1sDtwHFJTlrC9pwNPFxVjy5hG55TVd8CnjqkPHwNXgNcMMeu5wI7q+qpqvoRsBNYP9/5DCggyQZgX1V9b6nbMof3MPiJblLmuu1UF//ZtOGr1wPfXqIm/BcGP8T844TOt5D34rlt2g81PwZePpHWzWGe9+hfJvlekq8lee1kW/acAr6e5M5266hD9Xb9bwSuO8y6Hl5PgBOran9bfhw4cY5tFvW6dvF7UJOQ5BvAr86x6sPA7zMYVuuiPVV1S9vmw8CzwBcm2bYeJfkl4Cbgg1X19BKc/23Agaq6M8lZkz7/cjDPe3QXg2Gqv0tyHvAXwJoJNxHgTVW1L8mvADuT/KD1CrrTblrwduDyOVb38no+T1VVkrGNQk1NQFXVb81VT/LPgNOA77WRkVXAXUnOqKrHJ92eoXa9C3gbcHa1QdwJ6e62U0l+gcF/fF+oqi8vUTN+A3h7+8/gF4GXJfmzqvr3L+A5F/JezG6zN8kxwC8DT76AbZrTfO/RcGBV1Y4kf5rkhKqa6A1aq2pf+3ogyc0MhlGHA6qn6/+twF1V9cShK3p5PZsnkpxUVfvbcOiBObbZx+Bzs1mrgP8+34Gnfoivqu6tql+pqtVVtZpB1/P0FzKc5pPBH2/8EPD2qvrJhE/f1W2n2ucpnwO+X1V/slTtqKrLq2pVu0Y2Av/tBQ4nWNh7sR2YnRH1261dE/0cdSHvUZJfnf1sLMkZDP7vmWiQJnlJkpfOLjMYNTn0jvDbgYvabL4zgR8PDV9N2oUcZnivh9dzyPA1uAm4ZY5tbgXOSbKyzfI7p9WObNKzQHp/MM8snwm1YTeD8dq72+PTEz7/eQxmYj3MYMhxKV+LNzH43OCeodfjvCVu01lMaAbVXO8F8FEGP7zAoDf35+2a+Q7wil7eI+AS4JK2zWXA/QxmIt4O/KslaOcr2vm/19oy+3oOtzMM/njqw8C9wLolusZewiBwfnmotuSvJ4PA3A/8A4Mf5i9m8JnnbcBDwDeA49u26xj8dfTZfd/TrtPdwLsXcj5vdSRJ6tLUD/FJkvpkQEmSumRASZK6ZEBJkrpkQEmSumRASZK6ZEBJkrr0/wDK12jio/Xq8QAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "N_points = 100000\n",
-    "n_bins = 20\n",
-    "\n",
-    "MAX_VAL = 100\n",
-    "# Generate a normal distribution, center at x=0 and y=5\n",
-    "x = np.random.randn(N_points)\n",
-    "y = MAX_VALUE\n",
-    "\n",
-    "fig, axs = plt.subplots(1, 2, sharey=True, tight_layout=True)\n",
-    "\n",
-    "# We can set the number of bins with the `bins` kwarg\n",
-    "axs[0].hist(x, bins=n_bins)\n",
-    "axs[1].hist(y, bins=n_bins)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "aquatic-dallas",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

From 8d23f88ecd648a8ae7bee4d817e8b123d7b7558e Mon Sep 17 00:00:00 2001
From: fhorn97 <fhorn97@gmail.com>
Date: Wed, 3 Mar 2021 12:56:49 -0500
Subject: [PATCH 32/38] added .DS_Store to FH branch

---
 .gitignore | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/.gitignore b/.gitignore
index e43b0f98..f2487e7c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,5 @@
 .DS_Store
+NaturalDisasterProject/.DS_Store
+NaturalDisasterProject/Datasets/.DS_Store
+NaturalDisasterProject/Deliverable_1/.DS_Store
+NaturalDisasterProject/Deliverable_2/.DS_Store

From 373897a856f700612451282d506773644d1d2e7e Mon Sep 17 00:00:00 2001
From: fhorn97 <fhorn97@gmail.com>
Date: Wed, 3 Mar 2021 15:41:37 -0500
Subject: [PATCH 33/38] alvaro's graphing stuff

graphing checkpoint from alvaro
---
 .../Graphing-checkpoint.ipynb                 | 535 ++++++++++++++++++
 1 file changed, 535 insertions(+)
 create mode 100644 NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb

diff --git a/NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb b/NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb
new file mode 100644
index 00000000..fdbd0eab
--- /dev/null
+++ b/NaturalDisasterProject/Deliverable_2/.ipynb_checkpoints/Graphing-checkpoint.ipynb
@@ -0,0 +1,535 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Graphs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline \n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Global Values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "NUMBER_TORNADOS = 108 #Number of Tornado Events\n",
+    "NUMBER_DAYS = 57 #Number of days of data per Tornado\n",
+    "FILE_NAME = \"historical_data_fin.csv\" #CSV file that contains the data\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Loading Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Field 0: 'datatime'\n",
+    "#Field 1: 'temperature'\n",
+    "#Field 2: 'windspeed'\n",
+    "#Field 3: 'surface solar radiation'\n",
+    "#Field 4: 'relative humidity'\n",
+    "#Field 5: 'surface pressure'\n",
+    "#Field 6: 'total precipitation'\n",
+    "#Field 7: 'latitude'\n",
+    "#Field 8: 'longitude'\n",
+    "\n",
+    "\n",
+    "data = pd.read_csv (FILE_NAME,header=None)\n",
+    "\n",
+    "#Take data to numPy\n",
+    "numData = data.to_numpy()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Helper functions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Returns all elements of all Tornadoes for a specific field (0-8)\n",
+    "def getAllDataByField(field): \n",
+    "    \n",
+    "    return numData[1:,field:field+1]\n",
+    "\n",
+    "#Returns elements of a given field (0-8) for a particular Tornado (0-107)\n",
+    "def getDataByFieldAndIndex(field, event):\n",
+    "    \n",
+    "    return numData[1+(NUMBER_DAYS*event):(NUMBER_DAYS*(event+1)+1),field:field+1]\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Sample Data Graph\n",
+    "##### Temperature leading to Tornado 0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.ylabel(\"Temperature C°\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(1,0).astype(np.float).flatten())\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Temperature"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Linear graph of Temperature for all Tornados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.ylabel(\"Temperature C°\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(1,i).astype(np.float).flatten())\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Linear graph of Net Temperatures for all Tornados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.ylabel(\"Temperature C°\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    plt.plot([0,NUMBER_DAYS],[getDataByFieldAndIndex(1,i).astype(np.float).flatten()[0],getDataByFieldAndIndex(1,i).astype(np.float).flatten()[NUMBER_DAYS-1]])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Mean and Median of Temperatures across all Tornados "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Reshape array into 2D\n",
+    "arr2d = np.reshape(getAllDataByField(1), (-1, NUMBER_DAYS)).astype(np.float)\n",
+    "\n",
+    "#Mean\n",
+    "arrmean = np.mean(arr2d,axis=0)\n",
+    "plt.plot(np.arange(NUMBER_DAYS),arrmean)\n",
+    "plt.plot([0,NUMBER_DAYS-1],[arrmean[0],arrmean[NUMBER_DAYS-1]])\n",
+    "\n",
+    "plt.title(\"Mean\")\n",
+    "plt.ylabel(\"Temperature (C°)\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "plt.show()\n",
+    "\n",
+    "#Median\n",
+    "arrmedian = np.median(arr2d,axis=0)\n",
+    "plt.plot(np.arange(NUMBER_DAYS),arrmedian)\n",
+    "plt.plot([0,NUMBER_DAYS-1],[arrmedian[0],arrmedian[NUMBER_DAYS-1]])\n",
+    "\n",
+    "plt.title(\"Median\")\n",
+    "plt.ylabel(\"Temperature (C°)\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Net Positive Temperatures vs Net Negative Temperatures"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "labels = ['Net Increase in temperature','Net Decrease in temperature']\n",
+    "sizes = [0,0]\n",
+    "explode = (.5,0)\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    \n",
+    "    #If temperature increased approaching day of Tornado\n",
+    "    if(getDataByFieldAndIndex(1,i).astype(np.float).flatten()[NUMBER_DAYS-1] - getDataByFieldAndIndex(1,i).astype(np.float).flatten()[0] > 0):\n",
+    "        sizes[0] += 1\n",
+    "    else:\n",
+    "        sizes[1] += 1\n",
+    "\n",
+    "fig1, ax1 = plt.subplots()\n",
+    "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
+    "        shadow=True, startangle=90)\n",
+    "plt.show()     "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Wind Speed"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Linear graph of Wind speeds for all Tornados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.ylabel(\"Wind speed (m/s)\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(2,i).astype(np.float).flatten())\n",
+    "    \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Linear graph of Net speeds for all Tornados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.ylabel(\"Wind speed (m/s)\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    plt.plot([0,NUMBER_DAYS],[getDataByFieldAndIndex(2,i).astype(np.float).flatten()[0],getDataByFieldAndIndex(2,i).astype(np.float).flatten()[NUMBER_DAYS-1]])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Mean and Median of Wind Speeds across all Tornados "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Reshape array into 2D\n",
+    "arr2d = np.reshape(getAllDataByField(2), (-1, NUMBER_DAYS)).astype(np.float)\n",
+    "\n",
+    "#Mean\n",
+    "arrmean = np.mean(arr2d,axis=0)\n",
+    "plt.plot(np.arange(NUMBER_DAYS),arrmean)\n",
+    "plt.plot([0,NUMBER_DAYS-1],[arrmean[0],arrmean[NUMBER_DAYS-1]])\n",
+    "\n",
+    "plt.title(\"Mean\")\n",
+    "plt.ylabel(\"Wind Speed (m/s)\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "plt.show()\n",
+    "\n",
+    "#Median\n",
+    "arrmedian = np.median(arr2d,axis=0)\n",
+    "plt.plot(np.arange(NUMBER_DAYS),arrmedian)\n",
+    "plt.plot([0,NUMBER_DAYS-1],[arrmedian[0],arrmedian[NUMBER_DAYS-1]])\n",
+    "\n",
+    "plt.title(\"Median\")\n",
+    "plt.ylabel(\"Wind Speed (m/s)\")\n",
+    "plt.xlabel(\"Days\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Net Positive speeds vs Net Negative speeds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "labels = ['Net Increase in wind speed','Net Decrease in wind speed']\n",
+    "sizes = [0,0]\n",
+    "explode = (.5,0)\n",
+    "\n",
+    "for i in range(NUMBER_TORNADOS):\n",
+    "    \n",
+    "    #If temperature increased approaching day of Tornado\n",
+    "    if(getDataByFieldAndIndex(2,i).astype(np.float).flatten()[NUMBER_DAYS-1] - getDataByFieldAndIndex(2,i).astype(np.float).flatten()[0] > 0):\n",
+    "        sizes[0] += 1\n",
+    "    else:\n",
+    "        sizes[1] += 1\n",
+    "\n",
+    "fig1, ax1 = plt.subplots()\n",
+    "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
+    "        shadow=True, startangle=90)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From e0e1588c116e4ff035577e82b129e053aa159e04 Mon Sep 17 00:00:00 2001
From: fhorn97 <fhorn97@gmail.com>
Date: Wed, 3 Mar 2021 16:12:57 -0500
Subject: [PATCH 34/38] gitignore for FHD1

added ds store to gitignore
---
 .gitignore                                      |   2 ++
 .../Project Proposal CS506-checkpoint.pdf       | Bin 0 -> 80979 bytes
 2 files changed, 2 insertions(+)
 create mode 100644 NaturalDisasterProject/.ipynb_checkpoints/Project Proposal CS506-checkpoint.pdf

diff --git a/.gitignore b/.gitignore
index f2487e7c..0be68e07 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,5 @@
+**/.DS_Store
+/.DS_Store
 .DS_Store
 NaturalDisasterProject/.DS_Store
 NaturalDisasterProject/Datasets/.DS_Store
diff --git a/NaturalDisasterProject/.ipynb_checkpoints/Project Proposal CS506-checkpoint.pdf b/NaturalDisasterProject/.ipynb_checkpoints/Project Proposal CS506-checkpoint.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..7e70746ed2d0d9d100503c1de8f58657991c7c0b
GIT binary patch
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From 2c893f93c94a48a6c7ce0378b299a5fa6427ceb6 Mon Sep 17 00:00:00 2001
From: varocarras <34591902+varocarras@users.noreply.github.com>
Date: Wed, 3 Mar 2021 16:42:12 -0500
Subject: [PATCH 35/38] Delete .DS_Store

---
 .DS_Store | Bin 6148 -> 0 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 .DS_Store

diff --git a/.DS_Store b/.DS_Store
deleted file mode 100644
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From 186ea8764dd0dcca86be8012d2ae530e987a3774 Mon Sep 17 00:00:00 2001
From: varocarras <34591902+varocarras@users.noreply.github.com>
Date: Wed, 3 Mar 2021 16:42:39 -0500
Subject: [PATCH 36/38] Delete .DS_Store

---
 NaturalDisasterProject/.DS_Store | Bin 8196 -> 0 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 NaturalDisasterProject/.DS_Store

diff --git a/NaturalDisasterProject/.DS_Store b/NaturalDisasterProject/.DS_Store
deleted file mode 100644
index a77882f1a7dbb8703213df72ff0be6a9145f291f..0000000000000000000000000000000000000000
GIT binary patch
literal 0
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From 9532952d8f6668d16215daec269783ed1991308d Mon Sep 17 00:00:00 2001
From: varocarras <34591902+varocarras@users.noreply.github.com>
Date: Wed, 3 Mar 2021 16:42:54 -0500
Subject: [PATCH 37/38] Delete .DS_Store

---
 NaturalDisasterProject/Datasets/.DS_Store | Bin 6148 -> 0 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 NaturalDisasterProject/Datasets/.DS_Store

diff --git a/NaturalDisasterProject/Datasets/.DS_Store b/NaturalDisasterProject/Datasets/.DS_Store
deleted file mode 100644
index 4f8c3e55f7e130c4a93bbd35b3ded3c8827111b7..0000000000000000000000000000000000000000
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From 97127d2b7eb62e3d66acac745fa298eb497ca860 Mon Sep 17 00:00:00 2001
From: fhorn97 <fhorn97@gmail.com>
Date: Wed, 3 Mar 2021 17:16:02 -0500
Subject: [PATCH 38/38] added graphing for solar radiation with alvaros
 template

---
 .../Deliverable_2/Graphing.ipynb              | 269 +++---------------
 1 file changed, 36 insertions(+), 233 deletions(-)

diff --git a/NaturalDisasterProject/Deliverable_2/Graphing.ipynb b/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
index fdbd0eab..d36e8740 100644
--- a/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
+++ b/NaturalDisasterProject/Deliverable_2/Graphing.ipynb
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -35,13 +35,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
     "NUMBER_TORNADOS = 108 #Number of Tornado Events\n",
     "NUMBER_DAYS = 57 #Number of days of data per Tornado\n",
-    "FILE_NAME = \"historical_data_fin.csv\" #CSV file that contains the data\n"
+    "FILE_NAME = \"/Users/frazierhorn/GithubProjects/CS506Spring2021Repository/NaturalDisasterProject/Deliverable_1/historical_data_fin.csv\" #CSV file that contains the data\n"
    ]
   },
   {
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -83,7 +83,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -103,19 +103,17 @@
    "metadata": {},
    "source": [
     "#### Sample Data Graph\n",
-    "##### Temperature leading to Tornado 0"
+    "##### Solar Radiation leading to Tornado 0"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
-   "metadata": {
-    "scrolled": false
-   },
+   "execution_count": 15,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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mivjyA+P45c/fj1t/ccTWMX763LT6u6g+McO+I/MArDWtafF4yFENpGeOL2HXSBwXblqt2SPkr0+ZyCuMzSSxtcVJZsGukTgOTa3g7oOnkCuW8Ybz9QsjL9iYwI7BKG5//Lhja0jliggHzVUeAbKn0K0lqf8J4JNE1DlTLFxcGmByKYO/+uFBvOSv7sGff/8ADs8k8aiySVvl3kMVo5C0YhQmFjAcl7ChJ2TreQFg+2DUufBRrohEaG0sXISPjIxCsVTG0fl0y8tRBbtH4kjmivjX+8d0Q0cCIsJ1l2zEYxMLGJ915j1M5UumG9eALk40M/P7IZeefr01y3FxaQ5LmQI++s0n8fLP3odbfjaGV+wcwHc+cCUu2NiD5az5DV0wn8rjiWOLOFvR8rdiFB6bWMCe0V7ToYZabOuP4NhC2pEQRDJbRDS4drxnbzgAv5cMw0fHFzIolLjlSWaBmK1wcHLZMHQkeOvFG+Ah4NsOeQvpnBw+MkvQ70WuWEa5A2duG3oAzPwXAH7UgrW4uDSNn78wg28/cQLv2LsR9//BVfinX7sEF2/uRVzy2Uo4/uz5GTADb7pQDlWYDR+dWMxgcsmaCF4ttg9GwQwcmWv8TDeZKyImrd3QPB7CYMy4LHVsVpSjtsconD0cg7AD11xgrqd2OCHhZTsH8O3HTziyMadyJUSshI8UJdVcC9RbrWIqLMTMX232QlxcmklacdU/8Kod2NRXqZBJhPxYsWEU7ntuGusiAVyhDGhfMWkURD5h7xbzctm1EBtwvSls333iBN7/tX2mjpXMFetuaGa6msdnZaG50XXtMQqS34ttA1EMxYPYY6Hv47pLNuDEYgYPjc81vAaRaDZLSKlS6sS8gulXQUQXABjVPoaZv92ENbm4OI6I31bLEMRDfixnrRmFUplx//MzuPqcQcRDctjFrKfw2MQCwgEvdo00NkJSyFPX6lVgZvz9PS/gyFwK5TIbhlPqhY8AYCgu4flT9WcWAMDEXAoxyYe+SMDk6p3nT67ZBQCWxoC+9txhxII+3P7YCVy5vb+h50/litZyCh08ktPUqyCiLwO4AMB+AMLfYQCuUXDpCsSXL1RtFCQ/ljIFMLPpGP+TxxawmC7g6nMG1WalpMm8xGMTC7hoU48lEbxahAJebOgJ1axAemhsXk2gJvNFxKXaGz4gT0vLl8o1w0eAbBQeeEF/psLEXBpb1oUbypE0ylVnD1p+jOT34poLRnDHUyfx59eea2lTr0ZONJsPH6nT1zrQKJj9ZF7BzHuZ+d3MfKNyuampK3NxcRDhKUi+ak/Bh0KJLckY33doBl4P4eU7BtSNxEyiOZkr4uDkcsP5BMG2gUjNCqRvPnq08pwGxkrcXq8TdyguYSVX1PWEJuZS2NKm0FGjXLdnI9L5En707FRDx0lZTDRLHTyn2axReJCIdjd1JS4uTSRTKEHye9aEFxJK+MdKCOneQ9PYs7kXibC/4imYMApPKiJ4VsZv6rF9IIqxmeQqYbzFdB4/eHZKLSddMTIKOSOjoF+WWiyVcXwhgy19re1kdoq9W3qxZV24oZ6FcpmRzpcQtliSCnS3p3ArZMPwHBE9TUTPENHTzVyYi4uTZPIl9YuoRYRWlk0mm6eWsjgwuYyrzpHDFV6PPFrRTPho38Q8iGA42N0s2wejSOVLq0pGv/vECeSLZfzmlVsBAMmc/usSRiNaJ3w0HNfvaj65mEWxzG1LMjcKEeFtF2/Eg2NzOGFRrkSQLgjdIzvhoy6tPoI8ge1dAF4H4E0A3qj8dHHpCjKFUk0FS5EoNluWev/zcsPaVecMqNdFJZ+qkqnHM8eXsHMwqhvjt0JFA0nOKzAzbnv0GC7YmMBlyqxgox4M4SnE6pzlDsb1u5pFSeyWdd3pKQDA2y7ZAGbgOza9hXTOmkIqUPEUOjHRbNYoHGXmO5h5nJknxKWpK3NxcZBMvlRTrMxq+OjeQ9MYSUhq0xogh16MwjQAMJ/OYzAmGd7PLEKmWhiFJ48t4tDUCt556SbElTN/w/CRgadgFD6aUI1Cd3oKALCpL4zLt/bh9sdP2JpRURnFaUXmonNLUs0ahUNE9J9EdAMRvU1cmroyFxcHyRRKayqPAKib53LGeFPPF8t44IVZvOrswVWVNtGgz1ROYTlTQLyGnIRdxDxk0avwzUePIeT34s0Xrlc3eaOwVspgjGRM8iMS8NYNH03MpSH5PRiMBe2+jI7g7Xs2Ynw2hX0TC5YfK3pg7CSaO3H6mlmjEAKQA/AayGEjEUKqCxFtIqL7iOggEe0nog8r13+KiE4Q0ZPK5Q2ax3yciA4ruYvX2ntJLi5rSeeLCPsbCx89emQeqXwJV5+zuvwxGvSZ6lNYyeqXh1qFiLB9IIIXZ5JI5oq446mTeNOFI4hJfsSU51kx8ICMcgqAXIFUP3yUxpa+iKX+gE7kmgtGEAv68I1HjhrfuYqKp2DDKHTg9DXdV0FENwD4CTPfaOPYRQC/z8yPE1EMwGNEdJdy2xeY+e+qnms3gOsBnAtgPYC7iegsZu68d82l68gUymqoSIuVRPN9h6YR8Hpw5fZ1q66PBH04vpA2fPxytlC3H8Au2weieGhsDv/91Emk8yW889LN8poCXhAZV0VVcgr1jdVgPFjXKByd795yVC3hgA9vvmg9bn/8OP70TefW/KzUI523bhRCXVySugXA/yWinytn+JeTyQ4VZp5k5seV31cAHASgN8HtWgC3MXOOmccBHAZwmZnncnExIpsvqdICWgI+D0J+r6mcwn3PTePybX1rvvwxE4nmfLGMbKHsqKcAyL0KJ5eyuPUXR3DWUBSXKJVNRGQq15HMGg+HGY5LOLWy1iiUy4yJuTRGuzjJrOX6SzcjWyjjjidPWHpcMifCR9arj7oup8DMf83MVwN4A4CnANwE4HElv/AbRDSk93gBEY0CuBjAw8pVv6OUtn6ZiEQnzwYAxzQPO44aRoSI3kdE+4ho38zMjJmnd3FBulCsWx0SDxmL4qVyRbw4k1K1jrREgsYlqSKM0wxPAYCSYN68KtcRl4wlPJK5IqJB/eEwcvgotyYJe2oli1yxfFp4CgBw/sYEzl0fx22PHjO+s4a0jfCR10MI+DzdW5LKzCvM/B1mfj8zXwzgLwAMADAUyiOiKIDbAXyEmZcB/AuA7QAuAjAJ4HPirrWeusZabla6q/cODAzUeIiLy1oy+bJ6dlZNXPIbJprnU3kAwEB0bUI1GvSrM3rrIUpD4xbCEmbYPigbhYDXg7ddvPocKib5TBiropp/qMdgXEK+WMZierWBmZiTQ2bdXI5azfWXbsL+k8t45viS6ceoOQULiWagc6evGY3j/B4R/QERvZSIVLUrZj7AzJ9jZt1kMBH5IRuE/xDiecx8iplLzFwGcAsqIaLjADZpHr4RwEnrL8nFZS3ZQmmNGJ4gYUIUbyEtG4XeGqJvMcmHfKmsO+C+4ik4axS2rAvD7yW87rzhNWszFT7KFQyHzatlqVUhJFGO2q2Na7W49uINkPwefONR8wlnUX1kZfIaoExf68Kcwi0AegF8BsAUEf2CiP6WiN5qFDpScg9fAnCQmT+vuV4reP5WyEN8AHn05/VEFCSirQB2AnjE2stxcVkLMyOdL9bsaAbMKaUKT6EvsnZTF7FkvbNy4YnEHQ4fBX1e3HrTZfjkm9aq0MQk41LZZK6oW3kE1O9qPjKXhs9DGEk413vRbuKSH9ecvx53PHlSTSAbkcoVEfB54Lcochjyd+ZITqOcwveZ+Y+Z+VWQw0UfAnAKwN/C+Cz+pZC7oK+uKj/9G41MxlUAfk95rv0AvgXgAOShPh90K49cnCBfKqPMaxVSBWYG7YjQSU94racQlYR8dus9BQC4cns/+muFtSS/YUmqLJtt5CkoRmFptadwdC6NTX3hhhVfO43rL9uEZK6I7z89aer+qbzxe1gLye/tyPCR4Sshon4AVyqXKwBIAO4G8KDe45j5AdTOE/xA5zGfgeyVuLg4RjYvJ/PqeQqJkPmcQl8to6CEDVZ0dIaEJ+Jk85oRMck4fLSSK2KjgZjdQKx2V/ORudRplU8Q7N3Si+0DEdz2yFH8yt5NhvdP5eqHJvWQutFTIKIXIJ+1nwvgxwDeyMxXMPNvM/OtrVhgN/GlB8ax9y/uxkduewL//dTJuiGJcplxfCFtaa7vmcRCKu/o7Np0QX6f63oKIfmMWu85F9J5eKh2olgMqNH3FJqTaNYjJvkMJ8Ils8W6ukcCye9Fb9i/KqfALJejdqs6qh5EhOsv3YzHjy4aDhgC5PCRHU8h1KWewpchewfXATgfwHlE9CCAJ9zQzloeHptDJl/E/c/P4LtPnoTPQ7h0tA8vP6sfyWwRYzMpjM+mMD6XQr5Yxst39uNr77m83cvuKJazBbz0s/fi09eeh+v2bHTkmCKZVzenIPlRZv2BNPOpPHrCAXhrdO4KzRs9RdLlTAFEQNRihUojxII+5ItyAjzoq/3azW5oQ3EJU0uVnMJ8Ko9krnjalKNW87ZLNuBvfnwItz1yrGa+RksqX7TlKYQCXkyvWB8F22x0Pw3M/FfidyI6C3II6bcAvJyIZpj5lU1eX1cxtZzFntE+fOU3L8UTRxdwz6Fp3HPwFP7mR8/B5yFsXhfGtv4IXnFWP/ZNLOCFU2unZp3pjM2kkM6Xak4Us4uoDqnvKQj9o0Jdo7CQzqM3XPs20XuQ1PEUlpXYfSvlIET+IpktIhhd+9pLZUYqXzJMNANyWeq0xlM4opSjjvaffp4CAKyLBvGa3cP49hPH8UevP7uuUQVkD9FO/4nk78w+BbPjOLdBLh29HLLnMABgrInr6kpOLmaxeyQOr4ewd7QPe0f78EevOwcLqTxikm9VQu5zP3kO/3TfYRRL5dMuUdcIosxxNllbgM0OwkXXyykASoVQnaFo86l83RnEInykW32UrW9wmkVMo5S6rkYi2kgMT8twPIjnppbVv8X/aXPf6ekpAHLC+c5nJvGT/afwpgvX171fKldUK7SsIPm7sCSViL5DRJOQk8OvBvAYgBuYeYCZdQXxzjTyxTJmkzkM1yjP640E1mz8I4kQygycWnFu82s1hVIZJQdj/wDU2cIzDr4vIplXz8VX9Y90KnUWUgX01kgyA+bCR3KTWOtCR0Bls6+XbDYaxallKC5hZiWHYkk+s52YS4MI2NQXcmi1ncdLt/fD5yEcnFzWvV86X7I137lbcwpfAfBbzKw/udtFrcxYnzD3JRnpkY3H5GIGG3q684t1078/ivWJED779gscO6bokp1x0FMQ4aO6Hc0mlFLn0/m6E9NEJ6tu+EgnNNUsVKXUOsZKHcVpMnxUZmAulcdQXMLEXArrEyHdsEq34/EQesJ+LBqUKydzRUuzFASdahSM4hbzegaBiOJEdJ7Da+pKJpUa7lqeQi2E8Ti5VFt9stNhZjxxdBGPH7WuP6+HmOTlpKegho90OpqB+kqpzIzFdL5mNzMgbx6RgL7+0Uq22NJyVGB1+KgWKxY8heGqCWxH5tKnZTlqNYmQH0tpfaOQzhdteQqiJNXOYJ9mYmQUrlO6mD9JRNcQ0WVE9AoiuomIvgbg+5BnLXQVjx6Zx3tv3YfJJXszWWshjrW+x5xR0HoK3chMModkroiJubSjIaQjsyKn4FxZqojbGoeP6oRZckUUSlyzR0EQlfRnKsiy2e3LKdRClc024SkIqYsp5STm6Hz6tK080tITDmAxk697e75YRqHElhRSBaGAF2WWmys7CaOO5t8DcA1k4bp3APg0gI9ClqD4N2Z+BTM/2vRVOsxcMo+7D55SG5KcoOIpmLORccmPaNCnPq7bGFemfeVLZZx0yLAtpQtYSBewoSeEUpkN3XazpA1KUkX4pF74aCElupnrb+pG09fk8FGrPQWRAK8TPlI9BWNjpXY1r+SwnC1gPpU/IzyFnpB/jRCglpQNhVRBZfpaZxkFw1fCzAuQNZBuaf5yWoMIIziZ+Z9czCAm+Sw1sYwkJMc21FYjEsIAMDabwiYHmphE6GjvaC9OPJnBzEqubsWPFUSiuV5OweshxIK+uuGj+bTQPdLxFIL1G8XKZUYyV2xp45pYE6DnKciv10xOoT8ahIeA6fnXFZEAACAASURBVOUsjopy1DPAKCTCfhyaqt/AJiq4rCqkApUZFtliCQm09rOhxxlZCynCCGknjcJS1nSSWTDSE2qJpzC9ksW+I/OOHnN8NgUhwT/uUE9BxSj0AXAur5AtlOAhIOir/3HXE8VbSNVXSBXohY9S+SLK7PwsBSMCPg+CPk9dD8ZKTsHrIQzEgphayqr/pzMhfNQbDmAxXT+iILrY7VYfAZ03fe2MNArin+G0UTCbZBasT0iO5jXq8aWfj+NXv/gw8kXn3NSx2RR2DEQRC/pWeQ2NICqP9myWmwVmks4YzHS+hJDfqztIJq6jf6SneySIBOrPLlAlLlqcUwDkEJJergQwZxQAZdjOSk79P20+DSUuqukJ+ZHKl+p+d4SnYFU2G9AYhQ6rQDojjYLwFJwsB5tcyppOMgtGEiHMJvO6OvxOsJDOI18s4/C0c13C47MpbBuIYOtABGMOGYUjsymMJCS19n12xZmcT6ZQQsjAvY9L9cNHerMUBFEdmerlJiqkGiGL4tXPKYQD3prSHbUYjEmYXs5iYi6FgVjQ1tlxtyHySPXyTSmLhlWL1IR9yAlMGwUiupKIflUZw/kbRPQbzVxYMxFjGZ3yFHLFkty4FrcaPpKNyFSTQ0hiszpg0IRjllKZMTGXwtb+KLb2RxzzFI7MpTC6LoJo0Iegz+NYr0ImX0IooP9R1xu0M5/Kw+sh3USxXqK5IobX+k1Ub6aCVcnn4UQQU8tZuRz1DPASACCheIdLdSqQRPjIlkqqr4s9BaX89O8AvAzApcplbxPX1VRCak7BGZXSaWX4yIhFT0HtVVhstlGQP3RGnZlmObGQQaHE2NYfwdb+CE4sZhw525mYS2O0PwwiOX7tVE4ho4SP9JDDR/U8BbmbWS/8FA3KOYVaNefiuO3wFPSmr62YmKWgZSgmYTFdwAunVs6IfAIgh48A+TNQi0Y8hVCHegpmX8leALu507osbOJ0gkdUEFmdQKV6CsvNzSuIksQDJ50xCmOzchhq60AEQb8HzHLd+llDMdvHXM4WMJfKq6MdHTUKpsJHfp2S1HzNiWtaopIPxTIjV1w7C7qSU2iPpzA3m655m5mpa1pEWepCunBGVB4BUKVN6pWlihPLsI3qo8o+1FklqWbDR88CGG7mQlpJwOeBz0NIO2Shp5QuzxGL1Uet8hSEi3twatmR7kkRLtraH8G2fnlw/NhMYyGkiVkxBF4xCtGgY6J4sqdgHD5K5Uuqto+W+XS+ru6RQK/8s705hfrT18xMXdMypDnp2XyGGAWRU6hXgZRUq4/sJ5o7zVMwaxT6ARwgoh8T0R3i0syFNRsnh2aLTd2qpxAKeNET9je9AimZK8JD8tmOEyWw47MpxCQf1kUCqnRyo3mFcTEEXjlev9OegmH4qP6mvpAybxRqlaWKY7a6JBXQDx8lLQ6HEV3NAFSP7nQnYZBoTueLIKrfGKmH6FPotJyC2U/Ep5q5iHYQdtAoTC1lEJd8tqoxRhIhTDY9p1DErpE49p9cxsHJZaxvUIBvfDaFbf0REBFikh/90SDGZxurbJpQjMqWvoqnMJ/Oo1AqWx6IXk2mUDJ070W56FKmsKbKaEFH90gg/ve1krrLmQKCPk/d5rlmEpd8SOaLKJd5zSyHlazF8FGsctJzphiFWNAHr4fqho+SuSIiAZ9uvqkeXV19xMz3AzgEIKZcDirXdS3hgM+x8NHJpazl0JFgfUJqqigeMyOVK2LvFrn234m8wthMClv7K5vCNgcqkI7MpTEcl9Tk20AsCGY4IkWSyZcMN2TRbVxdgVQuMxbSBcOcQkzPKGSLbQkdAXL4iLlST68lmTMexamlJ+xHwOdBIuRXz6BPd4gIiZBfLUuuJp0r2QodAV0ePiKiXwHwCGT9o18B8DARvb2ZC2s2Ib8XGYeqj6aWspYrjwQjPc1tYMsVyyiWGYNxCVvWhXFwqjGjkC2UcHIpg61KLgGAI2Wp1UPgxbB4J0JIcqLZOKcAYE0D20q2iFKZDcNHqqdQJ6fQjnJUoCJhUW2smNlyopmIMBQPnjFJZoGefHYyX7QlcQEAfq8HXg91bfjoTwBcyszTAEBEAwDuBvBfzVpYswkFvI71KUwuZXDehritx44kQlhMF5RaeufDC1olzN0j8YY9hYm5NJjlyiPB1oEIZvflsZQpqJur9eOm8Eu7htS/VaPgQLI5nS8ah4/ESM4qT8GM7hFQ2XxrnZEvZ1qvkCrQKqWOJCrXZwvygCQzYnhafmXPJl1hwNORHh357HTOnmy2QD457c7qI48wCApzFh7bkYQdMgpy41refvhI8TBONslbEGeukYAPu0bimJhP66p5GiFyB9s04SMRSjpi01tYyRYwm8yvqn0fiDrjKZTLjGxhbZloNdqcghYz3cxAJXxUK6m7ki22pRwV0AzaqTJ2KxbE8LT87qt34l0vGXVkbd2Cnnx2Kley1bgmEDMVOgmzG/uPlMqj3ySi3wRwJ+QRnV2LU1OPTi3Jm5ZV3SOBMCbNSjZrp2vtHomDGatm7VpFSFqMVuUUAPsVSEJLZ6tmCHy/Q0Yhp2jWGH1x6w3aWTChewQYJJrbMJ9ZUK9UVpwsWMkpnKnoyWdb7QqvJhTwINdhRsHUq2HmPyCi6wC8FAABuJmZv9PUlTUZpzwFdbiO7USzmMDWJE9B03EpNvIDkyvYs6XP1vHGZ1IYjAVXfRE2rwuDCLY1kGqpboYCXsSCvoaNgmguMioZFBpAa8JHKXPho3DAC6L6JantyinE6wzaEb0rjWxoZwqJsI5RyBURbuA9lHyd5ymYfjXMfDuA25u4lpYSCvgcMgrWxnBWM5SQz4j1PIW/v/sFbB+M4I0XrLd8fG0b/vqEhETI31BeYXx2deURAAR9XmzsDdn2FETYqXpoy0Cs8QY28YUzMgpEsraR3fARESEaqN0T0M6cQr1EswgfnQmido3SEwoo0/fWlken8iVEbVYfAUq/VIcZBd3wERE9oPxcIaJlzWWFiJzRTGgTTlUfCaNgtXFNEPR50R8N1q1AyhVL+KefHsadT0/aOr7YDCJBuZZ610isIQ0koY5azdb+qO1ehSNzaQzFg2uSwf3RxhvYjOYza6klnz2fKsDvJVPjFmvNVMgVS8gVyx2XU0i2saGu2+iN1G9gS+WMixj0kBwKYzuJ0TjOlyk/Y8wc11xizGyv3KZDCAe8SDswNHuygcY1wfqe+r0Kz55YQr5YRsqmV1M9h3f3SAKHppZtzVVeSsv6RNWeAqD0KsykbL2fR2ZTNQXWBmLBhquPjEZxaqmllCq6mc00J9VSSq0opLbHU4goYa01OYUGhNzONES+qTqEVC4z0vlSQ999OdHchdVHikqq4XXdRCjgBXMlEWkXeY5CYx3CIwkJk3XGcu47sgBALn2zg1p9pHxwd43EkC2U1Ti+FYQUhbZHQbC1P4JUvmTrzP7IXLpm7bsToniia92UpyCtVUqdT+dNjwSN6BiFdp2RE1FNqQttAYKLPj115LNF86sZL7IeIb8H2S6dvHau9g8i8gHY4/xyWkfYoTnNk0sZ2/kEwUii/ljORxWjYNdTEOGMsHKmvHu97ODZySuI8FAtT0FcZzXZnMwVMZvMrapmEgzEgljJFhtyrzOWwkc1cgomdI8EtWYXCCPTruoj8dzVRsHKKM4zHVU+O7X6s5HOrT7hskOo20pSiejjRLQC4AJtPgHAKQDfa8kKm4Q6p7nBf8hUAxIXgvU9EpK54prQBTPj8aOKp2Az/5HMlRAN+lTdmx2DUfg8ZCuvMD6Tgodqj2HcarMsVSSZa2np9EflzbiRZHPGcvho9fu8YMVTqDGSs+IptM8oyMaqKqeQK8LvJd251S4yqlJqZu17CNhTSBWEAt2XU/grZo4B+NuqfMI6Zv54i9bYFIS+fiPJ5krjWuOeArC2AmlsNoX5VB6S32O7UiqZK6z60AZ9XuwYjNqawjY2m8KmvjACNTaS9T0hBHwey0ZB9CjUMgpOSF2IszAzDUa1wkcL6YKaaDSiVqJZGPp2laQCtZVShWy2HSG3M40edaZCVfgoL8JH9v+3wQ4sSTUriPdxIuolosuI6BXiovcYItpERPcR0UEi2k9EH1au7yOiu4joBeVnr3I9EdE/ENFhInqaiC5p/OXVR5w5NlKWKhrXGjUK9bqaH1NCR5dvXWc7p5BSPAUtu0fi9jyFGuWoAq+HMLoubHmuQqVHoUZOISq/L40YBSuJ5njIj1yxrJ65lcqMxXTesHFNEA36sLImp9C+WQoCeU7z2pyCm08wRyzog4fWVh8lnQgfdZunICCi9wL4GYAfA/gz5eenDB5WBPD7zLwLwBUAPkhEuwF8DMA9zLwTwD3K3wDwegA7lcv7APyLpVdiETV81IBREJt4o+Gjep7Cvol5JEJ+XLAxgXShhLKNiqGVGpr5u9fHcWo5hzkLYRlm1jUKgBDGs1aWemS2/hB44SnMJu0rpYovnGTKU1itf7ScKaDMxj0KglojOUWJa7tKUgEgKvlrJsCt6h6dqXg8slJqdfWRCOk2mlMolLjmcKd2YTag+GHIc5knmPkqABcDmNF7ADNPMvPjyu8rAA4C2ADgWgC3Kne7FcBblN+vBfBVlnkIQA8RjVh5MVYIOZBoFr0FdhVSBYOxIDyENb0K+yYWsGdLLyJBH5iBbNH6WlM1zgh3jcjJ5oOTK6aPM72SQzpfWqV5VM3W/iiOzqctfcAn5tLYWkebf52SU2gofGTRUwAqG7lZMTxBVPKhzKuHpixnCyBqLMTQKLKnUH2WW3AlLiwg6x9Vv4dOVB8p8tkNVkE6iVmjkGXmLAAQUZCZDwE42+yTENEoZEPyMIAhZp4EZMMBYFC52wYAxzQPO65cV32s9xHRPiLaNzOja5d0UauPGnDdGm1cE/i8HgzFpVVjOedTeYzNpGSjoKxVSBNYIZldK+0rjMKBySXTxxFhoVrlqIJt/REUSowTdcprazFeJZmtxe/1oDfsx0zSvi5UulCC30umBvVUz1QQukc9JsNHteSzV7LyzILqATetJCb51iTQU7mSGz6ygOwpVOUUHAgfqdPXOqgs1axROE5EPQC+C+AuIvoegJNmHkhEUcjyGB9hZr1Adq1vzZp4CTPfzMx7mXnvwMCAmSXUJOyX/5GNhI8mF7NIhPwNdTQKRhKr5yo8NiHnE/Zu6VWPb+eDUyt23BcJYDguWfIU1LnMNbqZBeI2s2WpqVwRMyu1y1EFjfYqmBmwI6hWSp03KYYnqDVoZzlTaFvjmiAW9CFfLCOn8TSTDUo+n2n01tA/SjmQaJY6cNCO2UTzW5l5kZk/BeATAL6EStinLkTkh2wQ/oOZv61cfUqEhZSfQpL7OIBNmodvhEnDY4dK+Mh+9dHkUrZhL0Ew0rO6V2HfxDz8XsKFm3rU6qFaWv1G1JvDu3u9tdkK47NJBH0ejMTrv161LNVkslkkmfVGOzZqFLIF89LG1UqpYhMwW31USym1nVPXBOL5qz0Yt0fBPLXks9UeoAZLUoEuMgpEFFd+9okLgGcAPACgfhxBfgxBNh4HmfnzmpvuAPBu5fd3o9LvcAeA31CqkK4AsCTCTM0g5ECieXIp45hRWJ+QcHIxoyYpHzuygHPXJyD5vWr5rNVeBTGKs9aXf9dIDC/OJE1/GEWSWS8Msi4SQEzymS5LFeWo9cJHgDxXoZFEczpfMj1UvTJox2ZOoaZRKLQ1yQxUuqm160rmCq7ukQVqJZpT+SICPk9DM8QlX+NhbKcxejX/qfx8DMA+5edjmr/1eCmAdwG4moieVC5vAPDXAH6ZiF4A8MvK34A8n2EMwGEAtwD4gMXXYgknSlLlMZyNVR4JRhIh5IplLKQLyBVLePrEkjpX2W5OQYzirBUm2D2SQLHMODxtrlpozKDyCJAlFazMa1Y9BZ3jClE8uxpVmYL18JHwFBZSeQR9HtNGRd18q3MKbfYUqmcqFEplZAtl11OwQE9Y7grXFlHUO+GyghMFL06j+4qY+Y3Kz61WD8zMD6B2ngAAXl3j/gzgg1afxy5ej9zNaddCZwslzKXyuuEUK6i9CosZ5Iol5Itl7B2VjULYpqdQLYan5ZyRGADg0NQKztuQWHO7lmKpjKNzabzu3GHD59zaH1GlOYw4tZRFTPLpfrEGYkFkCiVFotj6F9BK+EjyexH0eVSjMJ+Su5nNNngJ46sN8y1nCtilvNftQhglkUDXyqm7mENIXSxlClinDIBKNzh1DdDkFDqo+kj3U2HUQCZKTruVcMBr20KfWlYqjxz0FAA5TzE2I5+9i0E4Iqdg1avRjuKsRgz3Ea9Dj+MLGRTLbOgpAHJ10nefPImsiTP0mWQOg0ovQj20Xc12NrG0xdnXcY1S6kLavO4RoAkfrfIU2jd1TVDtwai6R274yDSiV2VRYxSSubWVfVYRXmjXeAoAPqf8lADsBfAU5LP/CyCXl76seUtrPuEGBu2I8lHnEs3ycSaXMtg3sYAt68Lqhig8BauieHodl1Ymmx1bkGP/tTSPqhH5geMLaewY1D9DnlnJqa+xHpUGtpwpo1RNJl+ytLFrB+0IT8EsaphGed/LZcZKrn3zmQXCKAhjoHqQrqdgmlry2bJsdqOeghzB75pEMzNfpTSrTQC4RCkF3QO55+BwKxbYTOSpR/aqj6aWRTezM0ahPxKE30s4sZjB40rTmkDtvrYodZHSCR8B5ucVTC/L9xkyESobjAdXPUYP2SjoH7PRWc2Zgg1PQWlek3WPzBsFye+B10Pq+57KF8HcXokLQFN9lFttFFxPwTy15LOdKOsNOdAv5TRm0+bnMPMz4g9mfhbARc1ZUusI+e3Paa54Cs6EjzwewnBCwkMvzmEulcdezQxl4WI66SkA5iebCcNhdFYPAIPKJj9t5rgrOQxEzYeP7JDJlxDym68O0Q7amU/l0Rc2v6ETyRPaRJhGVDG1UwwP0Caa5deVdGWzLdNT01NwLnzUNZ6ChoNE9EUiehURvZKIboEsW9HVhAL2jcLUUhY9Yb+ls1AjRhIhPHVc7jIWSWZANhjhgNeyp2A0XWsgFsSsic12ejmHSMBr6qxI9RRW9HMVqVwRqXzJ0ND0hgPweqghT8FKc6FQSi2WyljOFkx3Mwtikl+VPxCbcLtzCgGfB0GfRw0frRh4kC5rEfLZCxqjkMqVGupRACqJ5m70FG4EsB+yBtJHABxQrutqwg0oFE4uZTDsUOWRYL0SiopLPuwYWN0GEg74LM9+MGMUzISPZpLGsX9BLOiD5PfglEH4aNak9+H1ENZFArZnKljpaAYqg3aWMgUwm+9REMgjOYWgXvtnKQhikl81BtXT+FyMiUt+EAFLGqmLVL7xktSgzwMidNT0NVOvSNE9+oJyOW0IB7w4vmDXKDQ+hrMaUcm0Z0vvmiaxSNC6p5AyiB1rJ5vpbZzTy1k1LGQEEWEwJhmGj8SZvxljYzbMVU2xVEa+VDbdZwBUBu0IiQsrOQVA/j8JY6xOXWtz+AhYLZ/tlqRaR1VKzWg9hWLDEjdEBKnDZiqYlc7eSUT/RUQHiGhMXJq9uGYT8vtsl4JNLmUbHsNZjfAU9o72rbkt5PdazylkV4/irKbfpAqpFU8BkFVfpw1KXYXRMMopAOY9mmpE7beVWvK45EepzDiuiPqZ1T0SRLXho1z7ZykIYpIPSSWcJTyGdiq3diM9mq7mfLGMQokRbTB8BIiZCp3Tp2A2fPQVyPMNigCuAvBVAF9r1qJaRTjgtTXmMlcsYd7BxjWBUCC9YttaoxAJ+mw0r60exVmNmsQ12HBnlq0ZhaG4ZGxoLHgKdvWPxPtlZpaCQIjXiTGhZnWPBNGgV918O2GWgkA7fU1MXWuncms3ktDIZ6u6Rw4YVqmBJtpmYNYohJj5HgDEzBOKMN7VzVtWa7CbaF5ShdKsnUUa8dId63Dnh16mNq1pCdtYa/UozmrEZDO9ZHMmX8JKrmjJKAzEgqbCRx4yF7MfiAUxm7QudZHNK56ClZyCclYvdJns5BRSVYnmTvEUKn0KBTd0ZIMejXy26Fp34n2UAl0YPgKQJSIPgBeI6HeI6K2ozEHoWkJ+L3LFMkoWJ5qJCgQrTVFmICKcu7625EQk4EPaovZRrVGcWsx4CiLBa9R5rGUwHkQyV9T1bGZWclgXDcJr4mx1IBpEocRrxiEaIb5oVirERJOS0GWy+j+OBH2VnEK2CMnvqTnTutXENNPX3FGc9ujRyGcLw99o9RGg7EN1jMLzp1bw+996ylZEwy5mP60fARAG8CEAeyAL3b1b9xFdQNimbK04W+ixUMPeKOGg17J0dq1RnFrMTDYTpaXWcgpKr4JOBZIZiQtBv81eBfFFspJoFknhibk0wgGvpcolQK6+SuWLcjdzB0hcCKJBn9p/4cpm26M3HFjjKThRwRXy1/cU7jk4jdsfP45/uKd1vcJm5yk8ysxJZj7OzDcy89sANE3WulXYndMsPIWWGgUb4aNaozi1qJPNdDZbK7F/gdjs9XSVzEhcCAZsdjXb8RTEJn5sPm3LE4xK8ujUdKGE5UyxY3oB4pLswTAzkrnOWVc3ISrTSmVWcwpOJOslf30NNvEd+uLPx/DCKfNDsRrB0CgQ0UuI6O1ENKj8fQER/SfkmQpdTcjmRDPR6m61sakRIgGf+kE0S61RnNWIeH09RG7AbEkqoG1g0zc2ZiqPxBoB44R4NVbmMwtE+KhYZstJZmD1SM7lbPunrglikh/Mcld80vUUbCFOApczBTV81Kj2EaAYhTrVR1NLWQzHJUSCPnzie8/alpC3gtGQnb8F8GUA1wG4k4j+FMBdkMXwdjZ9dU1G9RQs6h+JuGJPC7/w4YDPcv7DTOzYqLLHSkJYMGQgdVEuM2YtlLnalbqw4yloz6BteQqaQTudMHVNEFVF8Qp1p/G56FPpas476imEAvVzClPLWewYjOIPX3c2Hhqbxx1PNW0YpYqRp3ANgIuZ+QYArwHwMQAvY+a/Vxrauhq7g3YW0gUEvJ6GtdStUJHPNm/AzHRcDkT1ewCml3PoN5kQFvSE/Qh4PXWlLhYzBRTLbNooxCUfAl5PSzwFn9ejDjWyWnkErDYKKx0wdU2glc9OZt1Esx16QhX57LSjOYX6JamnlrMYiku4/tLNuHBjAp/+/kE1N9QsjIxCRmz+zLwA4DlmfqGpK2ohdqceLWXySIT9poevOEFl0I65tTKzHD4y+NAaTTaz2rgGyFVUA7EgZuokmq3mKdTjtcBTACohpEY8hVSuqOQUOsRTCIpRowUkHZBnOBMRnsJSuqA2KDoXPlr7vS6VGdMrOYwkJHg9hL94y/mYS+Xw+Z883/Bz6mH0ydhORHdo/h7V/s3Mb27OslpD2KZRWEwX0NvCJDNQWavZvIIYxWnoKcSCyBbKdSebzayYrxKqPm698NGMhW5mQb8do2DDUwDkBraTS1l7noJmdoGcU+iMzVcYp1PLOTC7Ehd2EDnExUwe6XwRRNY/W7UI+WtrsM0mcyiVGUOK0sH5GxP49cu34KsPHsHb92w0nJhoF6NPxrVVf3+u5r26lEpOwWr4KK+6kq3CaqWUkRiewGiy2fRK1tY4ycFYUK31r3VM7XObYSAaxAlFesIsqqdg1SgoG6id5kTxHs6n8sgXyx1TkirCWJNL8nvvho+so5XPFlPXnIgWSH5Z5qJc5lVd5lPK/0orvPm/XnM2fvjsJD7xvWdx+29f2ZSudKMhO/frXRxfTYupVB9ZTzQnWuwpiDCQWaNgVvRML4krJ4TzlsNHgFyBZOgpWGyIMzM6VEsmX0LQ57H8xRFn91Z1j4DK+z25JBuwTskpCCMwqRhW11OwTlxjFNK5xqeuCUQvTK5qTvPU8lqjkAj78fHX78ITRxfxrX3HHHn+atrfatlGwjYTzW0NH5k0YCsm5ZH1JpvNp/MoldlSOapgMCZhMV2o6RbPrOQg+T2WNqaRuIT5VN5So6E8S8H6F1d8+RspSRVDmDqpJBUAJpWNxu1TsI7XQ4hLPiym80g6MGBHIIZAVecVxEnQUGL1ydPbLtmA15077OgsFy1n9CcjZLN5bTGTb2mPAqDxFExKXRiN4hRoZyBXY+eMXjAUrxibTVWznUXy2orrLRRpp5dz2LzOeFY0IKau2TAKygZqJ6cQ9Hng95LqKXTK5hsJeEGk9RQ6w1h1G70RWRQv7cAoTkGojrLC1FIWPg+hP7L6+0dE+Nd37XHkuWthpnnNq/QrnHaIARdWEs3ZQgnZQrml3cyAdiSnOU/BaBSnQG+yWaVxzUb4SKdXQU5eW/M+xNhTsdmaIV0oWVJIFcQbqD4iIkSCPjV23yk5BSJCVLMuN3xkDyGfncrb80JrUW/62tRSFoOxYMvVbA2NAjOXAOyhVtZftggiQlhHd6QWlca1dnkK1oyC0ZdfTDarZRQa8RQquYq1eQAr3cwC4SlMWcgrZG1+cfdu6cWlo71YZ1MFNxr04eSi8BQ6wygAsoESRrpTPJhuQ8hnpxxsAFSNQtXJ6dSy8zNbzGD2VT0B4HtE9H8BqCUlzPztpqyqhYQCPkvho8VM68XwAOuVUmaNAqD0KjgcPtKTuphJ5nDFtnWWjie+HOJM1wxpm+GjV5w1gFecNWD5cYJo0IfjC0qiuUNKUgF5XaIj3vUU7NET8uPoXEo+oXQqfKQmmtcahXOGrVf+NYrZV9UHYA6rZygwgK43CuGA11L10UKq9WJ4gBzq8nrIck7BTOlhPf2j6ZUsokGfrUEi6yJBeGitUmquWMJiumDZ0ESDPsQkn1qmZ4ZModSWM2LthttJnoL2vXDnM9ujJ+yXFQ18lc73Rqk00a6uPjq1lMUrGzg5sYvZGc03Nnsh7cKq+qgqhtfi8BERIRwwL59tNIpTy0AsiOdrKDDabVwD5LBUfzS4RupiLplXn9MqIwnJUk4hWyipCe9W9uo91AAAHB1JREFUIgyxh+DYxuEEwigEfZ0x46Eb6QkHsJwtIOjzOGZYJd/anMJKVs5bDDs83dEMpl4VEUkA3gPgXADqKpn5piatq2XUazGvx2IbZLMF4YDXtKdgNIpTi/AUqptnpldy6iwDOwzFJZyq8hTsdDMLhhMhS56C3fBRo4jNIia1VgrFiKjitbihI/v0hGS12Wyh7KCnsLYkVZSjtiOnYPZ04WsAhgG8FsD9ADYCaI24d5ORw0fmjUKzpq6ZIRLwmfYUUrmi6eaaepPNZi3MPKjFYA2pi0byFCNxyVJOIVMoqQ2KrSSmbLqdlE8AKp6C281sH+3JoGOegn9tSerUkvw9GWqDp2DWKOxg5k8ASDHzrZDVU89v3rJah9Xw0WImj4DPA8nfevc7HDRvwJIW6qjVyWZVeYXpBsJHgJxsrq4+mm7AKAwnJMwkcyiUamvPV5Ntk6cgzsQ7pRxVoBoF11OwjdYoOJ1o1hoFESYd6WBPQZxCLhLReQASAEabsqIWEwr4rIWPUnI3czvCAmELnkIyV1TPWI0QoZxZzVl9Ol9EMldsyFMYiEmYS+VR1GziwlMQo0CtMJKQwKw/vEfAzEgXSqpr3koq4aPO2nzF58E1CvZJaHKJUYdlLrQnfGo3cwd7CjcTUS+ATwC4A8ABAH+j9wAi+jIRTRPRs5rrPkVEJ4joSeXyBs1tHyeiw0T0HBG91sZrsUXY77U0o2Ax03oxPIEVr8aKp1BrstnsipwQtiNxIRiMBcEMzCrJZfk5sugJ+xH0Wf9Cqb0KJpLNhRKjVGZblVONIoxB53kKfuWnaxTsopW3ceqzVQkfVU6eppbl74nVGeFOYLb66IvKr/cD2Gby2P8O4P8A+GrV9V9g5r/TXkFEuwFcDzmRvR7A3UR0ltI411RCVsNHbRDDE0QCPhybT5u6bypXxLqIOTmIWqJ4dpRMqxGhp+mVShOOncY1QaWr2TivIM662vGl0iaaO4mo6yk0jFbexqn30eshBHyrB+1MLeXaUnkEGBgFIvqo3u3M/Hmd235GRKMm13EtgNuYOQdgnIgOA7gMwIMmH2+bkMVE82K6gNF+c5ut01jxFFYszOFVJ5tpjMJMAxIXgsF4Ra9Ie9xBm2WiagPbogmjYFM22wmibqL5tEWreuvk5MXqmQpi4lo7MAofxQwudvgdInpaCS/1KtdtAKDVgT2uXNd0wn4vimU2nbxsZ/goEjTffZ3Kmx+5qE42S2o9BfsJYYHoETilSTbPJO17CnHJh3DAa85TUL5grRyZKoh2qKcQU0tSO2td3YTP62lKwl7ye1adnE4tZzvTU2DmP3P4+f4FwKchd0N/GvLQnpsA1Mra1pwPSUTvA/A+ANi8eXPDC9IqpSZC+jaSmbGQLqDHhqSyE8iegnH+w+woTi3Vk81mVnLwesjWTAH1mNEgSNPVzMxy+MimoSEiDCckTC0b5xTE+9SO8FFUzSl01hm52MzcnEJj9IT9WMkWHas+AhRPQZG5KJTKmE3m2tKjAJhMNBPRRiL6jpI4PkVEtxPRRqtPxsynmLnEzGUAt0AOEQGyZ7BJc9eNAE7WOcbNzLyXmfcODDTeAh5WB+0Yn4FnC2Xki+W2JpoLJUa+qO/VmB3FqWUgGlyTU+iPBhpSaPR7PegLB1SvI5krIlsoN+R9yF3Nxp5CtgM8hc5LNLs5BScQ3/+og0UMkr8Sxp5ekUemdrRRAPAVyFVH6yGHdf5buc4SRDSi+fOtAERl0h0ArieiIBFtBbATwCNWj2+HyphL4zPwdonhCYQBM1qrFTE8wUAssEr/qJEz+tXHrfQqNNK4JhiOm+tqFjoyzRpEosfW/gjeevEGXLnDmuhfs9nQE8I79mzEy3b2t3spXY34/ocdKkkFVisr1BrD2UrM7hoDzKw1Av9ORB/RewARfQPAqwD0E9FxAH8K4FVEdBHk0NARAO8HAGbeT0TfglzqWgTwwVZUHgGV8IKZWL0Qw2v11DWB6FBO5Uvo0cl1mx3FqWUgGsR8Sp605vUQpldyjiS6BuOS6ilUJC7sH3ckIR+vWCrD561/TiMMZzsSzZLfiy+886KWP68RPq8Hf/uOC9u9jK6nJxxAwOeBX+fzZ5WQ34ucUpLazh4FwLxRmCWiXwfwDeXvGyCrptaFmW+ocfWXdO7/GQCfMbkexxCegpkGNuEpJNoWPjI3U9rsKE4tA7EgygzMpeQBODMrOZy3PmF/sQqDsSCen5IVUZxIXg8nJJSU2dF67rVafdRBgnQupwdb+sLY0BNy9JihgFc9aVI9hQ4PH90E4FcATCmXtyvXdT2qUTDhKSwJ3aM2JZpVT8FAFM/sKE4t2l6FUpkxl8rbLh3VMhSXq5rKZXYkfDSizlXQTzZn21iS6nJ68ztX78B3PnClo8cMacJHp5azCPg8bYtImG1eOwrgzU1eS1uwMqd5oU1T1wQhv/zvMpK6ELdbqj6KVozCYEwOIzmRUxiMSaqRmUnm4PMQehoYZl/patbPK4j/p2sUXJxG8nsdr2oLakpSRTlquxR2dT0FIvotItqp/E5Kb8GS0mdwSWuW2FzUkEyh8xPNwlMwks8W4SNriWZF/yiZb0jeuhptV/PMSg790cZmzprtanbDRy7dRMjvVSevTS61r0cBMA4ffRhyQhiQ8wgXQpa5+CiAv2/eslpH2IKnsJguQPJ72lL7DlQMmKGnoBgNK0ZB6ykIiQsnwkfasZxOVDT1hv0I+jyGs5oz+RKI5IEyLi6dTkhTknpqOYuhNuUTAGOjUGRmoZD6RgBfZeY5Zr4bQKS5S2sN9YZm12Ix3b5uZqDiKRitNZkrrLq/uWP7EFGSXU5UCQmEoN7Mcq6hSW4CIjLVq5BRZLM7aciNi0s9QgE5p8DMmFrKYrgNEwMFRkahTEQjyuS1VwO4W3Obs+n3NmHVU2hX6AjQegpGRkG+PWKxuaZfkbpwokpIMKANHyWd6X0YTkiGSqmZQqktjWsuLnaQ/F6UWZaByRXLbStHBYyNwicB7IMcQrqDmfcDABG9EsBYc5fWGvxeD/xeMleS2najIHIKBs1r2SIiAa/l2P1ANIhZxVOIBX2OxOMlvxdxyYfJpSzmHDIKI4mQKU+hXWE+FxeriM/qkVlZBbld5aiAsfbR94loC4AYMy9obtoH4J1NXVkL0cbz9FjM5LGtP9qCFdXG7/Ug4PUYegqpnHkxPC0DsSBemE6iLxnAgIPu61BcwnNTKyizM97HcELCqeXsmpnSWlxPwaWbCKlGIQWgPRPXBIZZOGYuVhkEMHOKmZPNW1ZrCQd8pmQuFtKFtvUoCMJBY1E8KwN2tAwoongzy/aVTGsxGA/iwOSy/BwOHHckIaFQkstc65EptGcUp4uLHcR43/E52Sh0cvjojMDMnAJmxlK60LZuZkEkYCyfbWUUp5aBaBBLmQJOLGbUWQhOMBiT1DU74inEjXsV0m74yKWLqPYUGpl42CiuUcBqhcJ6ZAol5EvltuYUAHPy2XY9hX5lwz6xmHHWU9AYAqdyCoB+V3PWDR+5dBGS8lkdn02hPyprK7ULs9LZRES/TkSfVP7eTESXGT2uWwgHvIaJZtHN3K7Wc0E44DUlc2FHHllrCJzYvGsdq98BY6N2Nev0KmTyJbdxzaVrEJ7CxFy6raEjwLyn8M8AXgK5gQ0AVgD8U1NW1AbMzGleTLdXDE9gJv9hZRSnFu3m3Wg/gRYRiooEvLY8mGrWRQLwe0m3AskNH7l0E2q/VKHU1m5mwLxRuJyZPwggCwBK4rm9u6ODhE3MaV7sEE8hEjThKVgYxallwOEwj2BIOZZTx/R4CENxSTen4IaPXLoJbVFEO8tRAfNGoUBEXigjMoloAIC5ocZdQDjgQ9pA+0gYhZ4GxlM6QTjg0w11MTNSNnMK66KV1+aExEXlWPKH3ElDI3c1188ppPNu9ZFL97DKKHSJp/APAL4DYJCIPgPgAQB/2bRVtZiQGU+hzWJ4AtlTqG/AcsUyCiVrozgFQZ8XCUXBtBmJZicrKoYT9SewMbNckurguEQXl2YiBSpbcTt1jwDz0tn/QUSPQZa6IABvYeaDTV1ZCwn5zeQUZE8h0YDssxOE/PolqXamrmkZiAWRyhXR66BHFAn60B8NYlOfzrg4i4wkJPxkfxbMvEbfKKfMsHY9BZduQeogT8HUzkFEVwDYz8z/pPwdI6LLmfnhpq6uRYQ1YlT1BNQW03mEmqCjbpVI0ItUvlh3rWI+s92E7kA0iGS22JC8dS2+/f9dib6oc4ZmOC4hVyxjMV1Ab2T1cSuzFNyKa5fuoBtzCv8CQNvBnFKuOy0IBbxgrpxh1mIhXWh7khmQcwrMQLZQe63JBj2Fq84ZwGvPHbK9vnpsXhe2vaZaVCawrQ0hiZxL2A0fuXQJfq8HPuVErN0lqWa/NcTMLP5g5jIRnTbfuLC/opRazxNYTBeQaHOSGdAM2skXa9bhJ20M2NHyvldst7+4FlLpVchg9/r4qttEfkhyq49cugjJ70WpzIjbqBx0ErOewhgRfYiI/MrlwzhNVFKByhmlXv3/Uibf0BhJp6istXZeQQzgsVOS2k2IruaTizU8BXcUp0sXIvm9GEm0bwynwKxR+G0AVwI4AeA4gMsBvK9Zi2o14oxbrwKpE8TwgIp8dr3pa5VRnKf3hjgQC8LroZoVSJXw0en9HricXoQCnraHjgDz1UfTAK5v8lraRkgTPqrHYgeI4QEao1Cnga0yirP9BqyZeD2EwVhQN6fQ7qIAFxcr7N3Sh2397R9oabb6SALwHgDnAlBNGTPf1KR1tRSx0dZrCmNmLGXyHZFoFlVF9UJddkZxdivDCQlTy2sb2DLKe+OGj1y6iS+886J2LwGA+fDR1wAMA3gtgPsBbISsf3RaYBQ+SuVLKJS47Y1rgPH4ULujOLuRerOa3fCRi4t9zBqFHcz8CQApZr4VwDUAzm/eslqLUfJWiOH1dED4KGKQFLc7irMbGY7LXc2awjgAmj4F1yi4uFjGtPaR8nORiM4DkAAw2pQVtYHK2Xftjbaie9Q5nkL9nII9MbxuZCQhD+9Zzq7+v2Vco+DiYhuzRuFmIuoF8L8B3AHgAIDPNm1VLSZkkFPoFDE8AAgb5RTy9sTwuhG1V6EqhJQtuCWpLi520TUKSj8CABxk5gVm/hkzb2PmQWb+txasryUYVR91ihgeUFlrPU8hmbU3irMbWd8jG4UHX5xddX06X4LPQ/B7XZkLFxerGH1rblR+/mOzF9JOxEZbL9G80EHhI6+HEPLXnxRnVza7G7lwYw+u3L4Of/79A/jhM5Pq9bJCqusluLjYwcgoHCSiIwDOIaKnNZdniOjpFqyvJXg8BMnvqbvRLnVQohnQl89O2hzF2Y34vB7c8ht7cdGmHnzotidw36FpAHL4yA0dubjYQ9coMPMNAK4A8AKAN2kub1R+njbojblcSBcQCXjbOkxbi9740DPJKABy38ZXbrwMZw/H8Ntffwy/eHFWHrDjegouLrYws8vNAHiGmSeqL3oPIqIvE9E0ET2rua6PiO4ioheUn73K9URE/0BEhxVP5JLGXpZ19GYqLKYLHZFkFkQCPl1P4UwJHwkSIT++etPl2NwXxntv3YdnTiy5noKLi00MjQIzlwD0E5HVXfHfAbyu6rqPAbiHmXcCuEf5GwBeD2Cncnkf2iDLrTd9bSmTb/twHS3hOp5CqcxyovkMKUnV0hcJ4D/eezkGY0GMzaRcT8HFxSZm4yETAP6HiD5BRB8VF70HMPPPAMxXXX0tgFuV328F8BbN9V9lmYcA9BDRiMm1OYIYtFOLThHDE0SCtUNd47MpFMuMbQPRNqyq/QzGJfzHb12BDT0hdQSoi4uLNcyeUp5ULh4AsQaeb4iZJwGAmSeJaFC5fgOAY5r7HVeum6x6PIjofVAUWjdv3tzAUlajHz7K45zheM3b2kE44MXMSm7N9QcmlwEAu0c6Z62tZkNPCD/+vVfgDGjodnFpCmZVUv+syeuo9RXmGteBmW8GcDMA7N27t+Z97BAOeDGbzNe8Tc4pdI6nEA74akpnH5xcht9L2DF4ZnoKgjMp0e7i4jRmVVLv+3/t3W+MXFUZx/Hvr9Mu7W5LoS0tC60U7CKtCVQthEDFUkiDSApRCBrQajBEBQMoMagviCQk+kaIAkGCCDalSChIY0yEAEJjEKVQBLpIC2JpdmmptN2W3f7Z3ccX984wbme7687u3rmzv0/S7NyzM+lz0uk8c55zzzlU+JCOiKX/59+3TVJzOkpoBran7VuBOWXPm00yMhk1yd1HnYe0RwS7umotKRTorLB4bWNbB/NmTqmZu6TMLH8G+5XqxrLHE4EvAf0fU9a/tcAK4Kfpz8fL2q+V9BDJAT67i2Wm0dLfRPPe/d309EbNrFGAZE6hv5HC4pYZGURkZvVisOWj9X2a/iLp2cO9RtJqYAnJnUtbgZtJksHDkq4CtgCXpU//I3AhsBno5KOV1KNm0oQCnRUmmmtpM7yixoYC+w720tMbFNLi+Y69+9m+Z/+Ynk8ws+oNtnw0rexyHPAZkvMV+pUufKvkvArPDeCawcQyUhr7GSnU0mZ4RcXts7sO9pTq562eZDazYTDY8tF6kjkFkZSN/kVyElvdmNRQYH/3/377BtiZbnFRC6euFRXvwe8sW728sS1JCvOdFMysCoMtH5040oFkrfxIzvK7V3Z11V75qHjU5odlI5vW9g6ap07k6KbaGdGYWf4MtHX26ZKOLbv+mqTH0y0pph3utXkzqZ8TzYqb4U2toYnm4klx5VtdbGzvcOnIzKo20L2LvwIOAEg6h2Si+LfAbtK1AvWisZ/ts9dt2sHUSRNqqnxUPqcAya6gb73/oUtHZla1gcpHhYgoblVxOXBPRKwB1kjaMLKhja5Snb4sKby5bQ9PbNzGdee1ML6GDmxpLJaP0pHCpm176ekNFhznpGBm1Rnok64gqZg4zgOeLvtdXS0brXQk513PbKaxocDXz5qbUVSVNfZJYMU7jzxSMLNqDfTBvhp4VtIOoAtYByBpHkkJqW70LR9t+U8na19p46rFJ9bc5G1TnzmFje0dNDYUOGFaY5ZhmVkdOGxSiIhbJT0FNANPpOsJIBlhfHekgxtNjaWJ5iQp3P3cW4wfN45vfvakLMOqqO9IYWN7B6ccO4Vx3gXOzKo0YAko3cq6b9ubIxNOdj6aU+hmW8c+HnlxK5cums2sIydmHNmhiofodB7oISJobe/g4oXHZRyVmdWD2pk9zVhpncKBHu5d9zY9EXzrnI9nHFVlR4wfxzglCWzrzi727OtmQfPUrMMyszrgpJAqHt/Ytnsfq17YwvLTjuNj02uzRi8p2T57f0/pDIX5zdUcc2FmlnBSSBXLRyuff4fOAz18e0ltjhKKkiM5u2lt72CcqKlDgMwsv5wUUsWSzM7OgyxbMIuTZ9X2N+9k++weNrZ1MHdGk88kNrNh4aSQKpZkAL5z7ryMoxlYsqtrN63veXsLMxs+Tgpljm6awOJ5M1g456isQxlQU8N43uvYx7sfdHnRmpkNm7palVyt+1aczvTJR2QdxqBMaiiwfstOAG9vYWbDxkmhTEuNzyOUazqiQE9vspbQ5SMzGy4uH+VUcf5jelMDM6fkY3RjZrXPSSGnmtK7jeY3H4nk7S3MbHg4KeRUY7rVhecTzGw4OSnkVHFXV69kNrPh5KSQU6WRgvc8MrNh5LuPcmrZglns7jxAy8zJWYdiZnXESSGn5kxr5HvLPpF1GGZWZ1w+MjOzEicFMzMrcVIwM7MSJwUzMytxUjAzsxInBTMzK3FSMDOzEicFMzMrUURkHcOQSXof+PcQXz4D2DGM4dSSeu2b+5U/9dq3vPfrhIg4ptIvcp0UqiHpxYhYlHUcI6Fe++Z+5U+99q1e+wUuH5mZWRknBTMzKxnLSeGerAMYQfXaN/crf+q1b/Xar7E7p2BmZocayyMFMzPrw0nBzMxKxmRSkHSBpH9K2izppqzjqYak+yRtl/RaWds0SU9K2pT+PDrLGIdC0hxJz0hqlfS6pOvS9lz3TdJESX+T9Erar5+k7SdKeiHt1+8kNWQd61BIKkh6WdIf0ut66dc7kl6VtEHSi2lbrt+L/RlzSUFSAbgT+DywAPiKpAXZRlWV+4EL+rTdBDwVES3AU+l13nQD34+I+cCZwDXpv1Pe+7YfWBoRpwELgQsknQn8DLgt7ddO4KoMY6zGdUBr2XW99Avg3IhYWLY+Ie/vxYrGXFIAzgA2R8TbEXEAeAi4OOOYhiwingM+6NN8MfBA+vgB4JJRDWoYRER7RLyUPt5D8kFzPDnvWyT2ppcT0j8BLAUeSdtz1y8ASbOBLwD3pteiDvp1GLl+L/ZnLCaF44F3y663pm31ZFZEtEPy4QrMzDieqkiaC3wKeIE66FtaYtkAbAeeBN4CdkVEd/qUvL4nbwd+APSm19Opj35BkrifkLRe0tVpW+7fi5WMzzqADKhCm+/LrVGSJgNrgOsjoiP58plvEdEDLJR0FPAYML/S00Y3qupIugjYHhHrJS0pNld4aq76VebsiGiTNBN4UtIbWQc0UsbiSGErMKfsejbQllEsI2WbpGaA9Of2jOMZEkkTSBLCqoh4NG2ui74BRMQu4M8kcyZHSSp+Scvje/JsYLmkd0hKsktJRg557xcAEdGW/txOksjPoI7ei+XGYlL4O9CS3hXRAHwZWJtxTMNtLbAifbwCeDzDWIYkrUf/GmiNiJ+X/SrXfZN0TDpCQNIk4HyS+ZJngEvTp+WuXxHxw4iYHRFzSf5PPR0RV5DzfgFIapI0pfgYWAa8Rs7fi/0ZkyuaJV1I8i2mANwXEbdmHNKQSVoNLCHZyncbcDPwe+Bh4GPAFuCyiOg7GV3TJC0G1gGv8lGN+kck8wq57ZukU0kmJQskX8oejohbJJ1E8g17GvAycGVE7M8u0qFLy0c3RsRF9dCvtA+PpZfjgQcj4lZJ08nxe7E/YzIpmJlZZWOxfGRmZv1wUjAzsxInBTMzK3FSMDOzEicFMzMrGYsrms2GRFIPyS2yE0g27HsAuD0ieg/7QrMccVIwG7yuiFgIkG538CAwlWRtiFldcPnIbAjS7Q6uBq5VYq6kdZJeSv+cBSBppaTSLrySVklaLumT6bkKGyT9Q1JLVn0xK+fFa2aDJGlvREzu07YTOAXYA/RGxL70A351RCyS9Dnghoi4RNJUYAPQAtwG/DUiVqXbrRQiomt0e2R2KJePzKpT3Al0AnCHpIVAD3AyQEQ8K+nOtNz0RWBNRHRLeh74cXoGwaMRsSmL4M36cvnIbIjSPXF6SHbHvIFk76nTgEVA+bGTK4ErgG8AvwGIiAeB5UAX8CdJS0cvcrP+OSmYDYGkY4C7gTsiqcFOBdrTO5G+SrLhXdH9wPUAEfF6+vqTgLcj4hcku22eOnrRm/XP5SOzwZuUnphWvCV1JVDc1vsuYI2ky0i2i/6w+KKI2CaplWT32qLLgSslHQTeA24ZhfjNBuSJZrMRJqmRZH3DpyNid9bxmB2Oy0dmI0jS+cAbwC+dECwPPFIwM7MSjxTMzKzEScHMzEqcFMzMrMRJwczMSpwUzMys5L+MuGFejEunCwAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -127,9 +125,9 @@
     }
    ],
    "source": [
-    "plt.ylabel(\"Temperature C°\")\n",
+    "plt.ylabel(\"Surface Solar Radiation (W/m^2)\")\n",
     "plt.xlabel(\"Days\")\n",
-    "plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(1,0).astype(np.float).flatten())\n",
+    "plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(3,0).astype(np.float).flatten())\n",
     "\n",
     "plt.show()"
    ]
@@ -138,62 +136,26 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Temperature"
+    "## Solar Radiation"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Linear graph of Temperature for all Tornados"
+    "### Linear graph of Solar Radiation for all Tornados"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 16,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.ylabel(\"Temperature C°\")\n",
-    "plt.xlabel(\"Days\")\n",
-    "\n",
-    "for i in range(NUMBER_TORNADOS):\n",
-    "    plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(1,i).astype(np.float).flatten())\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Linear graph of Net Temperatures for all Tornados"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 69,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -205,11 +167,11 @@
     }
    ],
    "source": [
-    "plt.ylabel(\"Temperature C°\")\n",
+    "plt.ylabel(\"Surface Solar Radiation (W/m^2)\")\n",
     "plt.xlabel(\"Days\")\n",
     "\n",
     "for i in range(NUMBER_TORNADOS):\n",
-    "    plt.plot([0,NUMBER_DAYS],[getDataByFieldAndIndex(1,i).astype(np.float).flatten()[0],getDataByFieldAndIndex(1,i).astype(np.float).flatten()[NUMBER_DAYS-1]])\n",
+    "    plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(3,i).astype(np.float).flatten())\n",
     "plt.show()"
    ]
   },
@@ -217,29 +179,17 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Mean and Median of Temperatures across all Tornados "
+    "### Linear graph of Net Solar Radiation for all Tornados"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -251,113 +201,11 @@
     }
    ],
    "source": [
-    "#Reshape array into 2D\n",
-    "arr2d = np.reshape(getAllDataByField(1), (-1, NUMBER_DAYS)).astype(np.float)\n",
-    "\n",
-    "#Mean\n",
-    "arrmean = np.mean(arr2d,axis=0)\n",
-    "plt.plot(np.arange(NUMBER_DAYS),arrmean)\n",
-    "plt.plot([0,NUMBER_DAYS-1],[arrmean[0],arrmean[NUMBER_DAYS-1]])\n",
-    "\n",
-    "plt.title(\"Mean\")\n",
-    "plt.ylabel(\"Temperature (C°)\")\n",
-    "plt.xlabel(\"Days\")\n",
-    "plt.show()\n",
-    "\n",
-    "#Median\n",
-    "arrmedian = np.median(arr2d,axis=0)\n",
-    "plt.plot(np.arange(NUMBER_DAYS),arrmedian)\n",
-    "plt.plot([0,NUMBER_DAYS-1],[arrmedian[0],arrmedian[NUMBER_DAYS-1]])\n",
-    "\n",
-    "plt.title(\"Median\")\n",
-    "plt.ylabel(\"Temperature (C°)\")\n",
+    "plt.ylabel(\"Surface Solar Radiation (W/m^2)\")\n",
     "plt.xlabel(\"Days\")\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Net Positive Temperatures vs Net Negative Temperatures"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 71,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "labels = ['Net Increase in temperature','Net Decrease in temperature']\n",
-    "sizes = [0,0]\n",
-    "explode = (.5,0)\n",
     "\n",
     "for i in range(NUMBER_TORNADOS):\n",
-    "    \n",
-    "    #If temperature increased approaching day of Tornado\n",
-    "    if(getDataByFieldAndIndex(1,i).astype(np.float).flatten()[NUMBER_DAYS-1] - getDataByFieldAndIndex(1,i).astype(np.float).flatten()[0] > 0):\n",
-    "        sizes[0] += 1\n",
-    "    else:\n",
-    "        sizes[1] += 1\n",
-    "\n",
-    "fig1, ax1 = plt.subplots()\n",
-    "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
-    "        shadow=True, startangle=90)\n",
-    "plt.show()     "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Wind Speed"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Linear graph of Wind speeds for all Tornados"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 72,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.ylabel(\"Wind speed (m/s)\")\n",
-    "plt.xlabel(\"Days\")\n",
-    "\n",
-    "for i in range(NUMBER_TORNADOS):\n",
-    "    plt.plot(np.arange(NUMBER_DAYS),getDataByFieldAndIndex(2,i).astype(np.float).flatten())\n",
-    "    \n",
+    "    plt.plot([0,NUMBER_DAYS],[getDataByFieldAndIndex(3,i).astype(np.float).flatten()[0],getDataByFieldAndIndex(3,i).astype(np.float).flatten()[NUMBER_DAYS-1]])\n",
     "plt.show()"
    ]
   },
@@ -365,55 +213,17 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Linear graph of Net speeds for all Tornados"
+    "### Mean and Median of Solar Radiation across all Tornados "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.ylabel(\"Wind speed (m/s)\")\n",
-    "plt.xlabel(\"Days\")\n",
-    "\n",
-    "for i in range(NUMBER_TORNADOS):\n",
-    "    plt.plot([0,NUMBER_DAYS],[getDataByFieldAndIndex(2,i).astype(np.float).flatten()[0],getDataByFieldAndIndex(2,i).astype(np.float).flatten()[NUMBER_DAYS-1]])\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 18,
    "metadata": {},
-   "source": [
-    "### Mean and Median of Wind Speeds across all Tornados "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 74,
-   "metadata": {
-    "scrolled": false
-   },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -425,7 +235,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -438,7 +248,7 @@
    ],
    "source": [
     "#Reshape array into 2D\n",
-    "arr2d = np.reshape(getAllDataByField(2), (-1, NUMBER_DAYS)).astype(np.float)\n",
+    "arr2d = np.reshape(getAllDataByField(3), (-1, NUMBER_DAYS)).astype(np.float)\n",
     "\n",
     "#Mean\n",
     "arrmean = np.mean(arr2d,axis=0)\n",
@@ -446,7 +256,7 @@
     "plt.plot([0,NUMBER_DAYS-1],[arrmean[0],arrmean[NUMBER_DAYS-1]])\n",
     "\n",
     "plt.title(\"Mean\")\n",
-    "plt.ylabel(\"Wind Speed (m/s)\")\n",
+    "plt.ylabel(\"Surface Solar Radiation (W/m^2)\")\n",
     "plt.xlabel(\"Days\")\n",
     "plt.show()\n",
     "\n",
@@ -456,7 +266,7 @@
     "plt.plot([0,NUMBER_DAYS-1],[arrmedian[0],arrmedian[NUMBER_DAYS-1]])\n",
     "\n",
     "plt.title(\"Median\")\n",
-    "plt.ylabel(\"Wind Speed (m/s)\")\n",
+    "plt.ylabel(\"Surface Solar Radiation (W/m^2)\")\n",
     "plt.xlabel(\"Days\")\n",
     "plt.show()"
    ]
@@ -465,17 +275,17 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Net Positive speeds vs Net Negative speeds"
+    "### Net Positive Solar Radiation vs Net Negative Solar Radiation"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -485,14 +295,14 @@
     }
    ],
    "source": [
-    "labels = ['Net Increase in wind speed','Net Decrease in wind speed']\n",
+    "labels = ['Net Increase in Solar Radiation','Net Decrease in Solar Radiation']\n",
     "sizes = [0,0]\n",
     "explode = (.5,0)\n",
     "\n",
     "for i in range(NUMBER_TORNADOS):\n",
     "    \n",
     "    #If temperature increased approaching day of Tornado\n",
-    "    if(getDataByFieldAndIndex(2,i).astype(np.float).flatten()[NUMBER_DAYS-1] - getDataByFieldAndIndex(2,i).astype(np.float).flatten()[0] > 0):\n",
+    "    if(getDataByFieldAndIndex(3,i).astype(np.float).flatten()[NUMBER_DAYS-1] - getDataByFieldAndIndex(3,i).astype(np.float).flatten()[0] > 0):\n",
     "        sizes[0] += 1\n",
     "    else:\n",
     "        sizes[1] += 1\n",
@@ -500,15 +310,8 @@
     "fig1, ax1 = plt.subplots()\n",
     "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
     "        shadow=True, startangle=90)\n",
-    "plt.show()"
+    "plt.show()     "
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -527,7 +330,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,