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Diff for: ‎datasets/Labour Data.csv

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Country,Annual Income,Average Family members,Birth Rate
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Lithuania,22949,2,10.1
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Latvia,22389,4,9.7
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Hungary,22911,4,9.8
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Luxembourg,62636,3,3.85
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United States,60154,3,3.9
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Switzerland,60124,4,4.3
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Denmark,52580,3,7.7
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Australia,52063,3,5.2
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Ireland,51681,4,8.5
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Belgium,49587,2,8.7
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Canada,48403,3,8.8
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Austria,48295,3,6.8
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Germany,46389,3,8.6
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France,42992,4,5.9
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United Kingdom,42835,4,4.9
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Sweden,42816,3,6.8
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New Zealand,39397,2,5.4
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Japan,39113,2,7.7
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Spain,37333,3,7.2
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Italy,35397,4,8.6
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Slovenia,34965,3,8.2
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Israel,34023,3,7.6
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South Korea,32399,3,8.3
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Estonia,28621,4,7.6
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Chile,28434,3,9.1
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Poland,25921,2,9.5
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Greece,25124,2,8.4
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Portugal,24529,4,9
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Czech Republic,23722,3,9.3
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Slovak Republic,23508,3,9.7
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Mexico,19311,4,13.5
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India,16580,5,19
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Pakistan,15800,5,16.3
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Bangladesh,12940,5,13.8
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Iceland,55984,3,5.4
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Norway,53643,3,4.5
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Netherlands,52833,4,6.4
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Finland,42127,3,5.9

Diff for: ‎datasets/PoliceKillingsUS.csv

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Diff for: ‎datasets/Score Book.csv

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Student ID,Analysis,Machine Learning,Artificial Intelligence
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1,2.393412671,3.324129347,0.039631096
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2,3.228434178,3.109298649,5.621414891
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3,6.611171616,3.603703815,4.830770027
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4,4.55351888,5.030113742,4.84697594
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5,4.151165323,6.555816091,4.126257144
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6,9.077035502,7.478125262,3.321003992
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7,7.039631096,8.201300407,2.667565198
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8,3.021068686,8.306264399,1.976072963
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9,5.011522874,6.622167472,1.220086585
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10,2.006190799,4.272699487,0.656404386
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11,3.324129347,2.393412671,0.32202138
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12,3.109298649,1.228434178,2.15599814
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13,3.603703815,0.611171616,0.076945636
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14,5.030113742,0.30351888,0.039381467
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15,6.555816091,0.151165323,0.021178522
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16,7.478125262,3.077035502,8.733030097
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17,8.201300407,0.039631096,0.006440428
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18,8.306264399,2.021068686,0.003664553
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19,6.622167472,0.011522874,3.002106869
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20,4.272699487,0.006190799,0.001308056
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21,2.006190799,4.272699487,0.656404386
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22,3.324129347,2.393412671,0.32202138
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23,4.109298649,5.228434178,2.15599814
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24,3.603703815,2.611171616,0.076945636
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25,6.892500004,5.85721035,6.100588246

Diff for: ‎datasets/University.csv

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university_name,total_students,students_enrolled,gender_dominance,education_level,time
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Harvard,1582568,12587,Male,High School,Day and Night
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Oxford,1568291,54682,Female,Graduate,Night
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Luke,1822565,54808,Female,Graduate,Day and Night
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Cambridge,785269,24865,Male,Post-Graduate,Day
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MIT,64154651,258745,Female,High School,Day and Night
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Xavier's,6611852,5698,Male,High School,Day
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Cornell,5455131,98547,Male,Graduate,Night
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Harvard,785280,42530,Female,Post-Graduate,Day
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Oxford,2534156,22897,Male,Post-Graduate,Day and Night
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Luke,5425,89,Female,Ph.D,Night
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Cambridge,41154894,134981,Male,Graduate,Day and Night
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MIT,18547802,254856,Female,Graduate,Day
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Xavier's,8527025,21530,Female,High School,Day and Night
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Cornell,89652710,72080,Female,Post-Graduate,Day
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Harvard,23746520,43250,Male,High School,Day
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Oxford,24167204,21560,Female,Graduate,Day and Night
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Luke,1822565,54269,Male,High School,Night
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Cambridge,585555,56810,Male,Post-Graduate,Day and Night
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MIT,9856921,64730,Female,Graduate,Day
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Xavier's,12345678,548925,Female,High School,Night
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Cornell,9802,152,Male,Ph.D,Day
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Harvard,2525560,23541,Male,Post-Graduate,Day
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Oxford,1568291,85788,Female,Graduate,Night
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Luke,7999952,989012,Female,Diploma,Day and Night
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Cambridge,24573045,54256,Male,Graduate,Night
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MIT,1822565,78046,Female,Post-Graduate,Day
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Xavier's,9078202,11135,Female,Post-Graduate,Day and Night
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Cornell,4562082,136542,Male,Graduate,Night
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Harvard,1582568,18256,Male,High School,Day and Night
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Oxford,4560825,14305,Female,High School,Day and Night
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Luke,9805412,58460,Male,Diploma,Day
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Cambridge,8552449,49610,Male,Post-Graduate,Night
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MIT,4608792,34950,Female,Diploma,Day
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Xavier's,24587259,35142,Female,High School,Day and Night
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Cornell,1822565,19872,Female,Diploma,Night
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Harvard,1582568,14235,Male,Graduate,Day and Night
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Oxford,5234,320,Male,Ph.D,Day
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Luke,4560872,14811,Male,Diploma,Day
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Cambridge,9167890,87587,Female,High School,Night
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MIT,8552449,89046,Male,Graduate,Night
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Xavier's,4658904,75802,Male,High School,Day
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Cornell,1582560,65810,Male,Post-Graduate,Day and Night
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Harvard,8629,87,Male,Ph.D,Day and Night
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Oxford,1568291,64735,Female,Graduate,Night
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Luke,1582568,24585,Male,Post-Graduate,Day
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Cambridge,99999990,7777852,Female,Graduate,Day
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MIT,8552449,254013,Male,High School,Day and Night
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Xavier's,24592580,45267,Female,Post-Graduate,Day and Night
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Cornell,1822565,98052,Male,Graduate,Day

Diff for: ‎datasets/anscombe.csv

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dataset,x,y
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I,10.0,8.04
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I,8.0,6.95
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I,13.0,7.58
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I,9.0,8.81
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I,11.0,8.33
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I,14.0,9.96
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I,6.0,7.24
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I,4.0,4.26
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I,12.0,10.84
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I,7.0,4.82
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I,5.0,5.68
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II,10.0,9.14
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II,8.0,8.14
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II,13.0,8.74
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II,9.0,8.77
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II,11.0,9.26
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II,14.0,8.1
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II,6.0,6.13
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II,4.0,3.1
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II,12.0,9.13
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II,7.0,7.26
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II,5.0,4.74
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III,10.0,7.46
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III,8.0,6.77
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III,13.0,12.74
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III,9.0,7.11
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III,11.0,7.81
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III,14.0,8.84
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III,6.0,6.08
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III,4.0,5.39
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III,12.0,8.15
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III,7.0,6.42
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III,5.0,5.73
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IV,8.0,6.58
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IV,8.0,5.76
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IV,8.0,7.71
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IV,8.0,8.84
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IV,8.0,8.47
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IV,8.0,7.04
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IV,8.0,5.25
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IV,19.0,12.5
43+
IV,8.0,5.56
44+
IV,8.0,7.91
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IV,8.0,6.89

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