seaborn.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Seaborn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**seaborn** est une librairie de visualisation de données statistiques.\n",
    "\n",
    "* Elle s'appuie sur **matplotlib**, **scipy** et **statsmodels**\n",
    "* Des plots plus avec de \"meilleures\" couleurs par défaut que **matplotlib** \n",
    "* Plots adaptés à l'analyse statistique\n",
    "* Supporte les arrays (**numpy**) et les DataFrame (**pandas**)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe src=http://stanford.edu/~mwaskom/software/seaborn/index.html width=900 height=500></iframe>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import HTML\n",
    "HTML(\"<iframe src=http://stanford.edu/~mwaskom/software/seaborn/index.html width=900 height=500></iframe>\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = np.linspace(-2*np.pi, 2*np.pi, num=100)\n",
    "y = np.sin(x)\n",
    "np.random.seed(9221999)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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vpgCrgEW+A8mBJv0G06Tfu+wNUff+/Ez2RtcZPF1ym+hMBu5K4/Al3/H0a8Bg7hQdzG0e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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113bda790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* seaborn utilise matplotlib et apporte des styles par défaut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JXxVlDrAl1W3dZUn/916jaIfsF+s7vEYxvH2Bt9GCrh3QpK+KU9l+fff0cTDw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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114474a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "plt.plot(x, y);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Seaborn fournit des styles par défaut qui utilisent les propriétées de plots de matplotlib:\n",
    "\n",
    "    * darkgrid\n",
    "    * whitegrid\n",
    "    * dark\n",
    "    * white\n",
    "    * ticks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'legend.numpoints': 1, 'axes.axisbelow': True, 'font.sans-serif': ['Arial', 'Liberation Sans', 'Bitstream Vera Sans', 'sans-serif'], 'axes.labelcolor': '.15', 'ytick.major.size': 0, 'axes.grid': True, 'ytick.minor.size': 0, 'legend.scatterpoints': 1, 'axes.edgecolor': '.8', 'grid.color': '.8', 'axes.linewidth': 1, 'ytick.color': '.15', 'legend.frameon': False, 'xtick.color': '.15', 'xtick.minor.size': 0, 'font.family': ['sans-serif'], 'xtick.direction': 'out', 'lines.solid_capstyle': 'round', 'grid.linestyle': '-', 'image.cmap': 'Greys', 'axes.facecolor': 'white', 'text.color': '.15', 'ytick.direction': 'out', 'xtick.major.size': 0}\n"
     ]
    },
    {
     "data": {
      "image/png": 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oDk+6M+gPuawVhwR9cSzb67NdeKMnkwYjUzEaa0socPia7HwoKQpRV1nE0FTM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\nL4QQHvL/AybfZYbh1LPAAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11433b8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print sns.axes_style(\"whitegrid\")\n",
    "sns.set_style(\"dark\")\n",
    "plt.plot(x, y);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Les autres propriétés des plots comme la taille sont définis pas `set_context` et `plotting_context`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x11380c310>]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VocSRKzuclHAW5qC9rgjqjBueLb/scIgMIzM/feltLsSW/o0+7fpWFEXBuZ4q+ANhXB5b\nkR0OZanzw8vQANzVnZnlxLgznRXQAFxQea8RHRQTrgwX0TRcHFlBQZ4Vor5YdjgpdS72IccdVCTL\nG4NLMCkKTovMLCfGnRIVUMCyItGdYMKV4cbnPfBsBXCivQwWc2b/ddeU5aO61I6ByXWWFSntlt07\nmFzcQFeTE458m+xwUspZmIP2+mKMzrrh2mRZkeggMvsTmHBhOLrkfyrDn7jjTolyBEIRXJtckx0K\nZZk3BzO7Wf5m8bLiRe5WJDoQJlwZTNM0XBxZRl6OBd0ZujvxZic7on1ql0bYW0LpdX54GRazglMd\nmdsreaNTopxlRaI7wIQrg00ubmJ9w4/jbZlfToxrrCxEqSMHV8bWEApzCCqlx4p7B7PLW+huKoE9\n1yo7nLQoLshBR30xRuc8LCsSHUB2fApnqfjuxNOd2fHEDUR3K57oKMeOP4ThGQ5BpfS4PLoKADje\nXiY5kvQ6EyufXuAqF9FtMeHKUJqm4aK6jBybGb3NJbLDSat4SecSt6xTmlweWYEC4ERbdiVcpzrK\noSgsKxIdBBOuDDWztIUVtw/HWkthtZhlh5NW7XXFKLRbcWl0FZGIJjscynBbO0GMzLnRUuNAUUGO\n7HDSqqggBx11xbHd0CwrEt0KE64MtVtOzJLdiTcymRScaC/DxnYA4wse2eFQhrs6tgpNA05kSbP8\nzY63l0EDcHWcO4OJboUJVwbSNA0X1BXYLCYcaSmVHY4U3K1I6RLv3zqRZf1bccdjZdQrsZ8DEe2N\nCVcGWljdxtK6F0daSpFjy65yYlxXYwlybWZcGlmBprGsSKkRCIZxbXINVSV2VJfmyw5HisoSO6pL\n7RicWkcgyIHDRPthwpWB4kv7Jzqy84kbAKwWE462lmLF7cPs8pbscChDDU65EAhGsnZ1K+54exkC\noQgGp7kzmGg/TLgy0NWxVShA1pYT41hWpFS7NBr9t5Wt/VtxLCsS3R4TrgyztRPE2LwHrbVFKLRn\n9nlut3OkpRQWs4kJF6VEJKLh6tgqHPk2tNQ4ZIcjVWtNEQryrLg6tooIS/hEe2LClWH6J9agacCx\ntuxe3QKwe6TR3Mo2Vt07ssOhDDM278GmN4jjbWUwKYrscKQymRQcayuFZzuA6eubssMh0iUmXBnm\n6lh0Sf9Ya3b3lMQdi5U6+ia4ZZ2S60qW70682fG2aFn1MsuKRHtiwpVBQuEIrk2so9SRi9ry7Nwx\ndbOjsT62Ps4IoiTSNA2XRleQYzVnzcHwt9PT7ITFrLCPi2gfTLgyyPi8B15/CMfaSqFkeYkjrrQo\nmnwOTbvg55Z1SpKFNS+WXTvobSnJupMc9pNrs6CrsQRzK1tY9bCET3QzJlwZ5OpYdBXnWJad53Y7\nR1tLEQxFoPIwa0qSvvHYYdW8194mfnh3/L2IiN6ScMIlhHhMCDEshBgVQvyHPf73dwshPEKIy7H/\n+z8TvSbt7er4KmxWEzobimWHoivxsiKPHqFk6Y/9W+rN8tErNzvWGv15XBnlzmCim1kS+cNCCDOA\nPwfwMIB5AOeFEE+qqjp000tfUFX1g4lci25tyeXF4poXJ9rLWOK4SVtdEew5FvSNrUF7RGO5lRKy\n4w9hdM6DxqpCFOVn9+iVm5U4ctFYVYjhGTe8vhDsuQl9xBBllERXuM4CGFNVdUpV1SCAbwP40B6v\n4ydcivWxnLgvs8mE3pYSrG34sLDmlR0OGdzQtAvhiJb1g4X3c7ytDOGIhoGpddmhEOlKoglXLYDZ\nG76ei/3ejTQA9wghrgohnhJCdCd4TdrDldg4CH4I7O3I7m5F7qCixMR3vB5t5b22l/jPpZ+jWIje\nJtGE6yAjhS8BqFdV9RiAPwPwgwSvSTfZ8YcwMutGY1UhnIU5ssPRpSMtpVDw1kog0WFomob+iTXk\n51rQUp3d0+X301hViII8K65NrPHgeKIbJJpwzQOov+HrekRXuXapqrqpqqo39uunAViFECUJXpdu\nMDC5jnBE446pW3Dk29BU7cDonAdeX0h2OGRQ86vbcG360dNcApOJnRJ7MSkKeltK4N4KYH5lW3Y4\nRLqRaMJ1AUC7EKJJCGED8EkAT974AiFEpRBCif36LABFVVUW95PoaqxMxhLHrR1rLUVEY28JHV68\nTMZ77daONMfKipNcUSaKSyjhUlU1BOCLAJ4BMAjgO6qqDgkhPi+E+HzsZR8D0C+EuALgjwF8KpFr\n0ttpmoaByXUU2q1orCqUHY6uHY2dL9k3xj4uOpzdcRDNTLhupac5WsS4NsGHG6K4hPfsxsqET9/0\ne399w6//AsBfJHod2tv8yjbcWwGc667M+gN0b6ehshCOfBv6J9YQ0TT+vOiOxMdBNFVF/x3R/hz5\nNjRWFWJk1g1fIIRcG8dDEHHSvMFdm4w+QcafKGl/JkXB0ZZSbHiDmL6+KTscMpjBqeg4CJYTD+ZI\nSwnCEQ3D027ZoRDpAhMug7s2GS9xMOE6iPiHJQ+zpjsV79/i6JWD6WUfF9HbMOEyMH8wjJFZD+or\nClBUwHEQB9Hd5ISigI3zdEfi4yAK8qxo5jiIA2mtdSAvx4L+cY6HIAKYcBmaOuNGKBzh6tYdsOda\n0VLtwMT8Bnb8HA9BBzO/Eh0H0ctxEAdmNpnQ3eTEqseHZdeO7HCIpGPCZWAsJx5OT3MJIpqG4WmX\n7FDIIFhOPJz4z4tT54mYcBnawOQ6bFYT2uqKZYdiKLtb1llWpAPqn1iDAqCnhQ83dyL+MBjf3EOU\nzZhwGdSax4fFNS86G5ywWvjXeCeaqx3IyzFjgB8CdAD+YBhj857oWBE7x0HciRJHLmrL8jE87UIw\nFJYdDpFU/KQ2KJYTD89iNqGzwYll1w6W3ewtoVsbmXUjFNbQ3eyUHYoh9baUIBCKYGTWIzsUIqmY\ncBlUfIm+lz0lhxJPVAe5ykW3EV8J7W7iw81h9LKPiwgAEy5DCkciGJxyoawoF5XOPNnhGFK8j4tl\nRbqdwal1WC0mdNQVyQ7FkDrqimGzmtjHRVmPCZcBTS5uYscfQm9zCRQeT3MoFU47yopyMTjtQjgS\nkR0O6ZRny4+5lW101BXBajHLDseQrBYTOuqLsbC6DfeWX3Y4RNIw4TKga7GleR7nk5je5hLs+EOY\nXOQxP7S3wano6JBu3msJ6W6M/vyGpjiKhbIXEy4DGphch0lR0NXID4FEsKxItxM/kaCH/VsJ6W6K\nbjjgCQ+UzZhwGcy2L4iJxQ201Dpgz7XIDsfQuhp5zA/tT9M0DEyto9BuRV1FgexwDK2uogCFdisG\np9Z5zA9lLSZcBjM87Yam8Yk7Gey5VrTURI/58fp4zA+93cLqNjxbAXQ3lcDEXsmERFfknXBvBbC4\n5pUdDpEUTLgMZmg6uhrT1ciZQMnQ0xQ75meGvSX0dgPx/q0m3mvJEH9IHOSKMmUpJlwGMzTtQo7V\njJYah+xQMkJvc3RGEPu46GaD7N9Kqu7dhIsPN5SdmHAZiGvTj8U1L0RDMSxm/tUlQ3NNIY/5oXcI\nhSNQZ9yoLrWjxJErO5yMUBqbGzg8w1EslJ34qW0g8SdulhOTx2wyQdQ7sezewaqHx/xQ1Pi8B/5g\nmNPlk6y7qQS+QBiTCxzFQtmHCZeBDE3He0r4IZBMXbEeHc4IojiOg0iNeD8c+7goGzHhMghN0zAY\n26JeW54vO5yM0h1bMRxi4zzFDEy6YDYpEA3FskPJKJ2xUSxMuCgbMeEyiOvrXri3AuhqdHKLepLV\nlOXDkW/D0JSLM4IIXl8QU9c30FLjQF4OZ90lU36uFU1VDowvbMAX4CgWyi5MuAxi94gRljiSTonN\nCPJsB7DAGUFZb3gmOuuO91pqdDc5EY5oGJl1yw6FKK2YcBkEG+ZTK/5zHWKpI+vFeyV5r6UGx0NQ\ntmLCZQCRiIbhGTfKi3NRXpwnO5yMtNvHNc0PgWw3PO2CzWLirLsUaat1wGYx8UgtyjpMuAxg6vom\ndvwhHladQmXFeSgryoU640Ykwj6ubOXZDmB+dRvt9Zx1lypWixnt9cWYX9mGZ8svOxyitOE7igHE\nj/PhESOp1d3khNcfwvQSZwRlq2GWE9Mi/l7GncGUTZhwGUC816GTHwIpFV9B5Jb17MWzStOjsyH6\n8x1mCZ+yCBMunQsEwxid86C+ogAOu012OBktntDyQyB7DU27kJdjQWNloexQMlpjZSHyciwYnuZO\nRcoeTLh0bmzeg1A4wnJiGhTl21Bbno/ROQ+CIZ71lm1W3TtYcfvQ2VAMk4mz7lLJZFLQ2VDMI7Uo\nqzDh0rm3tqizYT4duhqdCIQiGJ/3yA6F0izeT8TSfXq8VVbkKhdlByZcOjc87YJJUdBeVyQ7lKzQ\nHe/jYlkx67BhPr26OIqFsgwTLh3b8YcwubiJ5ppCHjGSJqKhGCZF2W2epuygaRqGpl1w2K2oLeNZ\npelQU56PQrsVwzM8UouyAxMuHRud8yCiabtL75R6eTkWNFUXYnIhOvuMskP8rNLo4crs30oHk6JA\nNDjh2vRj2cU+Lsp8TLh0bJg9JVJ0NToR0XjWWzbhcT5ysKxI2YQJl44NTbtgNiloq2X/Vjrtjofg\nUMaswYRLji7ea5RFmHDplNcXxMzSJlprHMixmmWHk1XaaotgNikYnuEKVzaIaBqGp10odeTwrNI0\nq3TmobjAhqFp9nFR5mPCpVPqrBuaxnKiDDlWM1prHJhZ2oTXF5QdDqXY3PIWtn0h9m9JoCgKuhqd\n2PQGMb+6LTscopRiwqVT8dk0LHHI0dnohKZFE1/KbPFyYjdn3UnBEx4oWzDh0qmhaResFhNaati/\nJQOHMmaP+Ae9aCiWHEl26mpg4zxlByZcOrTpDWBuZQtttUWwWvhXJENrrQMWs4nNvBkuHIlgZM6N\nSmceShy5ssPJSmXFeSgryoU640Ykwj4uylz8NNchNdaszf4teawWM9pqHZhd3sLWDvu4MtXM0hZ2\n/GEIzrqTqqvRCa8/hNnlLdmhEKUMEy4diq+qdPFDQKp4WVHlbsWM9dasO5YTZerkPC7KAky4dGho\n2oUcqxlN1YWyQ8lqnMeV+eI9ejzNQa5O9nFRFmDCpTOeLT8W17xoryuCxcy/Hpmaqx2wWdjHlani\n/VtVJXYUF+TIDierOQtzUFlix+icG+FIRHY4RCnBT3SdGWb/lm5YLSa01RVhfmUbG96A7HAoyaau\nb8IfCKOTuxN1oauhGL5AGNPX2cdFmYkJl87s9m8x4dIF9nFlLm5O0Rexe69xRZkyExMunRmediEv\nx4yGygLZoRA4lDGT7c7fqucKlx7E56DxSC3KVEy4dMS16ceSawcddcUwm/hXowdNVYXIsZrZx5Vh\nQuEIRuc8qC61o4j9W7pQXJCD6lI7RubcCIXZx0WZh5/qOhL/UOdMIP2wmE1oryvC4poXni2/7HAo\nSaaub8IfDLOcqDOiwQl/IIzppU3ZoRAlHRMuHVE5E0iX3hoPwVJHpti91/hwoyvxDQzsmaRMxIRL\nR4Zn3NH+rQrO39KT3XMVWVbMGOzf0ifRwJ5JylxMuHRifcOH5Vj/lsmkyA6HbtBYVYBcm5krXBki\nFI5gdN6D2rJ8OPJtssOhGxTl21BdasfonId9XJRxmHDphDrLLep6ZTaZ0FFfjKV1L1yb7OMyusnF\nDQSCEZYTdaqzwQl/MIzp6+zjoszChEsn2FOib/Et6+osSx1Gt1tO5MBTXeKRWpSpmHDpxPC0G3k5\nFtRXcP6WHnEAauaIl4aZcOlTvK+OJXzKNEy4dGB9w4dl9w5EPfu39KqhsgB5OezjMrpgKILxeQ/q\nyvNRaGf/lh458m2oKcvHKOdxUYZhwqUDKp+4dc9sMqG9jn1cRje5uIFAiP1betfZUIxAMIIp9nFR\nBmHCpQPD7N8yhE6e9WZ4KocLG0Inx0NQBmLCpQPqjBt29m/pHs96Mz72bxlDx+4AVCZclDmYcEkW\n79/qYP+W7sX7uPghYEzBUARj8x7UlRegIM8qOxy6BYfdhtryfIzOcx4XZQ5Lot9ACPEYgD8GYAbw\nZVVV/9ser/lTAO8D4AXwq6qqXk70upnirXIin7j1Lt7H1Te+BtemH85CHnpsJJOLGwiGIrzXDKKz\n3on5lW0gQsPPAAAgAElEQVRMLW6ira5IdjhECUtohUsIYQbw5wAeA9AN4BeFEF03veZxAG2qqrYD\n+A0Af5XINTPNWyUO9pQYAfu4jIuHwxtLvOw7xHuNMkSiJcWzAMZUVZ1SVTUI4NsAPnTTaz4I4GsA\noKrqGwCKhRCVCV43Y6gzLvZvGQj7uIyLu4GNhX1clGkSTbhqAcze8PVc7Pdu95q6BK+bEdY8Pqy4\nfezfMhD2cRkT+7eMJ97HNcZzFQ3npb4FjM97ZIehO4kmXNoBX3dzNnHQP5fRdgIhKABOtJfJDoUO\naHcel2uH87gMhP1bxtRZ70QgFMHk4obsUOiA1jd8+OpTw3j+4pzsUHQn0YRrHkD9DV/XI7qCdavX\n1MV+L+vVlRfgj750H+47Wi07FLoD7OMyHvZvGRNL+MYTv9eaqgolR6I/iSZcFwC0CyGahBA2AJ8E\n8ORNr3kSwGcAQAhxDoBbVdWlBK+bMRx2GxSF5UQjeetDgAmXUbB/y5jYx2U83Ai2v4QSLlVVQwC+\nCOAZAIMAvqOq6pAQ4vNCiM/HXvMUgAkhxBiAvwbwhQRjJpKK5yoaC/u3jIt9XMYzPM2NYPtJeA6X\nqqpPA3j6pt/765u+/mKi1yHSixvnca1v+FDiyJUdEt0C+7eMLT6Pa3JxA+11/DvUs1XPDlY9Phxv\nK+NGsD1w0jzRIez2cc1ylUvv4ufxscRhTJ2N7OMyinjpvrOR99pemHARHcLuhwAP19W9txrmuTpi\nRB31vNeMYjfh4r22JyZcRIfQUFGIvBzL7hsM6VMwFMb4wgb7twys0G5DXXk+xuc9CIbYx6VnwzMu\n5OdaUMf+rT0x4SI6BJNJgagvxrJ7B+sbPtnh0D4mFti/lQlEA+dx6V28f6ujvhgm7rzfExMuokPi\neAj9U7lFPSN0cjyE7vFeuz0mXESHFG+cZzOvfg3PuKCA/VtGt9vHxXtNt+IPnlxN3h8TLqJDqq8o\ngD3HwqdunQqGwhib30BdBfu3jI59XPqnzrjZv3UbTLiIDslkUtBRX4wVtw9rHvZx6c34/AZC4cju\nSiQZG/u49GvVzf6tg2DCRZSATvZx6dZuiaORJY5MwHtNv+LzCPlwc2tMuIgSEB/wx/EQ+jM844aC\nt/p/yNg4j0u/OOvuYJhwESWgrqIA+bkWPnXrTCAYxsSCBw2VhcjPZf9WJoj2cRVgfGEDwVBYdjh0\nA/ZvHQwTLqIEmJRoH9eqx4dV947scChmfN6DUFjjE3eG6WwsRjAUwcQC+7j0It6/JRqc7N+6DSZc\nRAniuYr6M8Qz3TJSV+xeG2JZUTeGd+dv8eHmdphwESWIA1D1R51xQVGAjjp+CGSSjoZiKOA8Lj15\na/4WH25uhwkXUYJ2+7im+SGgB/5gGBMLG2isLIQ91yI7HEqi/FwrGioLMbHgQSDIPi7ZNE3D8IwL\nBXlW1Jbnyw5H95hwESXIpCgQDU6sbbCPSw/G5j0IRzSWEzNUZ2MxQmEN4/Me2aFkvehZsn50NnD+\n1kEw4SJKgrfKilzlki0+NoBHjGSm+Fl9Q7zXpNu91/hwcyBMuIiSgM28+jE844JJUdDO/q2M1FFX\nDEVhz6QexB8w2b91MEy4iJKgpjwfBXlWDM+4oGma7HCyli8QwtTiJhqrCpGXw/6tTGTPtaCpqhCT\nCxvwB9jHJYumaRiedqEo34bqUrvscAyBCRdREpgUBZ2NTrg2/Vh2sY9LlrG5eP8WV7cyWWeDE+GI\nhtF5lhVlub7uhWc7ANFQDIX9WwfChIsoSboa470lLHXIEi9xdLHEkdF4pJZ88faJLvZvHRgTLqIk\n2T1cl31c0gzPuGA2KWirK5IdCqVQe10RzCaF95pEbJi/c0y4iJKkqsSO4gIbhqfZxyWD1xfC5OIG\nmqsdyLWxfyuT5dosaKouxOTiJnb8IdnhZJ2IpmF4xg1nYQ4qivNkh2MYTLiIkkSJ9XFteINYWN2W\nHU7WGZlzQ9P4xJ0tOhuciGgaRuc4jyvdFla2sbUTRGeDk/1bd4AJF1EScTyEPMPsKckq8cSa4yHS\nb2i3nMjNKXeCCRdREu02zjPhSruhaRcsZhPaah2yQ6E0aKtlH5cs8SSXDzd3hgkXURKVFeehrCgX\nI7NuRCLs40qXDW8As8tbaK8rgtVilh0OpUGO1YzWGgemlzbh9QVlh5M1IhEN6owbZUW5KCti/9ad\nYMJFlGSdjU5s+0KYXd6SHUrWiI8H4BN3dulqKoGmcTxEOs0ub8HrD7FX8hCYcBElGfu40o8zgbJT\n/O97kPda2uzea5x1d8eYcBElGZt5029o2oVcmxlN1YWyQ6E0aqlxwGY18eEmjeLva1zhunNMuIiS\nzFmYg6oSO9RZN0LhiOxwMt76hg9L61501BfDbOJbWjaxmE3oqC/Gwuo23Ft+2eFkvFA4gpFZNyqd\neXAW5sgOx3D47kSUAp2NTvgDYUxd35QdSsbjjqnsFv97527F1Jta3IQvEEZ3U4nsUAyJCRdRCvBD\nIH2GpphwZbPuxuiHP/u4Um9weh0A77XDYsJFlAIidq4ie0tSS9M0DM24kJ9rQV1FgexwSIL6ygLk\n51owNMUjtVJtcMoFBezfOiwmXEQp4LDbUFeej7F5D4KhsOxwMtayewfrG350Njph4hEjWcmkKOhs\ncGJtw4cV947scDKWPxDG+LwHDVWFKMizyg7HkJhwEaVIV2MJgqEIxnjWW8rEVxC7+cSd1bqaOIol\n1Ubm3AhHNHQ38V47LCZcRCnS08wZQak2PM0t6sQjtdIh3isZ75mjO8eEiyhFomMKFAxOrcsOJSNp\nmoahaReKC2yoKrHLDockqiqxo7jAhqFpFyLs40qJwal1WMwK2uqKZIdiWEy4iFIk12ZBa40DU4ub\n2OZZb0k3v7KNTW8QXY1OKOzfymqKoqCrsQSb3iDmV7Zlh5NxNr0BzCxvoa22CDlWnlV6WEy4iFKo\nu6kEGjgeIhUGpuJb1FniIOz2Fg1xRTnpdo/z4fythDDhIkqh+IDAwSkmXMkWT7h6mvkhQOzjSqXd\nzSlsmE8IEy6iFGqqLkSuzbybHFByBEMRjMy4UV1q5xEjBAAoceSi0pkHddaNcIRHaiXT0JQLeTlm\nNFXxrNJEMOEiSiGL2YTOBieWXTtY5YygpBmf9yAQiqCHJQ66QVdTCXyBMCYXeaRWsqy6d7Ds3kFn\ng5NnlSaIPz2iFIsvw3M8RPLEVwy7WU6kG8TnsQ1OckU5WeLvWzzOJ3FMuIhS7K0+Ln4IJMvg1DrM\nJgWivlh2KKQjXU1OKApYwk+i+PsWG+YTx4SLKMWqSzkjKJm2doKYWtxEa40DeTkW2eGQjuTnWtFS\n7cD4/AZ2/CHZ4RheJDbrrqjAhppSzrpLFBMuohRTFAXdTdEZQXPLW7LDMbzhaRc0sJxIe+tuKkFE\n0ziKJQnis+66OesuKZhwEaXBbh8Xx0MkbHccBEsctIf4mJBrLCsmbCDWC9fNey0pmHARpcFuH9c0\nPwQSNTC5jrwcC5qquUWd3qmlxhEdxcLG+YQNTK4B4Ky7ZGHCRZQGxQU5qC3Lx8isG8EQZwQd1rLL\ni1WPD12N3KJOe7OYTehqjI5iWeYolkPzB8NQZz2oKy9AcQFn3SUD37GI0qSryYlAMILxeY/sUAxr\nIFaS7eHEa7qF+IoMx0Mc3sisG6FwBL0tXN1KFiZcRGkSLytyy/rhxT9A2TBPtxJPuFhWPLxrE9Gf\nXS/vtaRhwkWUJp0NxbCYFfRPrMkOxZAikegW9bKiXFQU58kOh3SsojgPZUW5GJx28ZifQ7o2uQab\nxYT2uiLZoWQMJlxEaZJrs6C9rhgzS1vwbPllh2M4k9c34PWH0N1Uwi3qdEuKoqC3uQQ7/hCP+TmE\n9Q0fFte8EA1OWC1m2eFkDCZcRGl0pKUUAHCNpY47Fi8ncscUHQTLiocXf39iOTG5mHARpVG8AZUJ\n1527NrkOBTzTjQ6mqzF2zA/vtTu2m3CxYT6pmHARpVFtWT6chTkYmFxHJMJjfg7K6wtifH4DLTUO\nFORZZYdDBmCPHfMzsbABry8oOxzDiEQ0DE2to9SRg6oSHueTTEy4iNJIURQcaSmJngd4nb0lBzUw\nFT2HMl6SJTqInuaS2HmAbtmhGMbk4ga2fSH0NJeyVzLJmHARpVlvc6yPi7sVD6xvfBUAcKSVCRcd\n3Ft9XLzXDor9W6nDhIsozbqbnDApCvr5IXAgEU3DtYl1OOxWNFbxOB86uJYaB/JyLLg2uQ5NYwn/\nIK5NrsGkKLvnv1LyWA77B4UQJQC+A6ARwBSAT6iq+o51WyHEFIANAGEAQVVVzx72mkSZwJ5rRWut\nA2PzHmztBNmTdBuzS1vwbAdwd08VTCxx0B0wm0zoaS7BheFlLKx5UVuWLzskXdv2BTGxsIHWmiLY\nc/m+lGyJrHD9DoBnVVXtAPB87Ou9aADerarqCSZbRFG9LaXQNGCQU+dvqy9Wej3KciIdwtFY31+8\nLE37G5pyQdNYTkyVRBKuDwL4WuzXXwPw4Vu8lo+lRDc4Eh8PMcGE63b6J9agKJy/RYcT7/vrH2cJ\n/3auxdocejgOIiUSSbgqVVVdiv16CUDlPq/TADwnhLgghPj1BK5HlDEaKgtRaLeif3KNvSW3sO0L\nYnzew3EQdGhF+TY0VxdidM4Dry8kOxzd0jQN/RPryM+1oLnKITucjHTLHi4hxLMAqvb4n/7jjV+o\nqqoJIfb71LhXVdVFIUQ5gGeFEMOqqr50uHCJMoMpdvTIawNLmFvZRn1FgeyQdGlgch2a9lZZiOgw\njrSUYnJxEwNT6zjTWSE7HF2aWdqCa9OPu3sqYTKxKJUKt0y4VFV9ZL//TQixJISoUlX1uhCiGsDy\nPt9jMfb/V4QQ3wdwFgATLsp6vS2leG1gCdcm1phw7SNeBuI4CErEsbYyPPnKFPrGV5lw7eNqrMft\nWFuZ5EgyVyIlxScB/Ers178C4Ac3v0AIYRdCFMZ+nQ/gvQD6E7gmUcboaS6BgmiPEr1TRNPQPxkd\nB9FQyXEQdHiNVYVw2K3oH19DhCX8PV0dW9tdeafUSCTh+q8AHhFCjAB4KPY1hBA1Qogfx15TBeAl\nIcQVAG8A+JGqqj9JJGCiTOGw29BUXYiRWQ+2efTIO8wubWFjO4AjLaUcB0EJMSkKjrSUYsMbxDRP\neHgHz3YAk4sb6KjnOIhUOvQcLlVV1wE8vMfvLwB4f+zXEwCOHzo6ogx3vK0Mk4ub6J9Yw7nuvdol\nsxeny1MyHW0rwyvXrqNvfA3N1WwKv1H8XjvaynJiKnHSPJFEx9vLAQBXRjkj6Gb9E+tQFKC7iSUO\nSlxPUwnMJoXzuPbQNxZtazjezoQrlZhwEUlUV56PUkcu+ifWEQpHZIejG1s7QYwveNBaU8RxEJQU\n9lwL2uuKMLm4Cc92QHY4uhEMRXBtah2VzjxUldhlh5PRmHARSaQoCo63lWHHH8Lo7DtOxspaV8dW\noWl84qbkipeneXD8W9RZF/yBMHcnpgETLiLJ4knF5TGWOuLiJdYTTLgoieI9Slc5dX7X1Vg58Rh7\nJVOOCReRZKKhGLk2M66MrnLqPIBAMIz+yTVUldhRXcrDhil5akrtKCvKxcAkS/hAdLr81bFV5OWY\n0V5fLDucjMeEi0gyi9mEIy2lWPX4sLC6LTsc6QanXQgEI1zdoqRTFAVHW0tZwo9ZWPNi1eNDT3Mp\nLGamA6nGnzCRDhyP9U9cYVkRl0dWAAAnOsolR0KZKP7v6tII77W+2PsNy4npwYSLSAeOtEaHe2b7\neIhIRMOVsVU48m1oqeGsJEo+UV+M/FwLLo2uZP3U+atjq1AAHGXClRZMuIh0oCDPiva6IkwsbMCz\n5ZcdjjTjCx5seoM43lbG6fKUEhazCcfayuDa9GNqMXunzm/tBDE670FrbREK7TbZ4WQFJlxEOnG8\nvQwasnsH1eUR7k6k1Du5W1ZckRyJPNFNOsCxNq5upQsTLiKdiPdxXc3SPi5N03BpdAU5VjO6m5yy\nw6EM1tNcApvFhIsjK1m7M/iCugwAON1ZITmS7MGEi0gnKkvsqC61Y2ByHYFgWHY4abew5sWyawe9\nLSWwWsyyw6EMlmM140hLKZbWvVhY88oOJ+28vhAGJtdRX1GASieny6cLEy4iHTneVoZAKIKByXXZ\noaTdldFoeedkO3cnUurtlhVjKz3Z5Or4KsIRDacE77V0YsJFpCPx5f3zWfghcGlkFSZF2T1+hSiV\njrWVwmxSsnI8xIXhWDlRsJyYTky4iHSkqaoQZUW5uDK6imAoe8qKrk0/Jhc3IBqKeVg1pYU914rO\nRiemlzax6tmRHU7a+AIhXJtcR3WpHTVlPMkhnZhwEemIoig401kBXyCMaxPZU1aMD3zlYdWUTqey\ncAhq3/gagqEIV7ckYMJFpDO7ZcXh7Ckrnh9aAsD+LUqvE+1lUJBd4yEuqNH/Vu5OTD8mXEQ6Ey8r\nXh5bzYrdiq5NP9QZN9rrilBalCs7HMoiRQU5aK0rwuisGxvbAdnhpJw/GEb/+BoqnHmoK2c5Md2Y\ncBHpjKIoONNVAX8gjP4sKCueH16GBuBsV6XsUCgLnWwvh4bsOMf02sQ6/MEwTosKKDzJIe2YcBHp\n0NnOaPJxfnhJciSp9+bQEhQFOMMSB0kQH43w5lDm32sXR6JtChwHIQcTLiIdaqgsQEVxHq6OrcGf\nwWXFZfcOJhY20N3ohCOf57lR+pUX56G1xoGhaRfcGXyOaTAUwZXRVZQ6ctFUVSg7nKzEhItIh3bL\nirGei0wVb5Y/281yIslzrqcKmga8OZi5q1wDU+vwBcI4JcpZTpSECReRTp3Jgt2KbwwuwWJWdrfn\nE8lwpqsCJkXBaxmccJ0f4rBT2ZhwEelU9JyzPFwdX4U/kHllxfmVLcytbONISynsuRx2SvI47Db0\ntpRg+vomFte2ZYeTdL5ACBdHllFWlIvWWofscLIWEy4inYqXFQPBCPomMq+s+GbsiZu7E0kPzsXK\n2q8NZN4q10V1BYFgBPf0VrGcKBETLiIdOxPbrfhGhpU6NE3DG0NLsFlNON7G6fIk34n2cuRYzXhj\n8Do0TZMdTlK9eu06AOCe3irJkWQ3JlxEOlZXno+68nxcHVvFpjdzBjNOL21i2bWD421lyLGZZYdD\nhBybGSc7yrDi9mF8YUN2OEmz5vFheNqF9roiVDjtssPJaky4iHRMURTcd7QG4YiG1zOo1BFfsbuL\nuxNJR871RFeAXhu4LjmS5Hl98Do0cHVLD5hwEencuZ5KmE0KXupbyIhSRySi4c2hZdhzLOhtLpUd\nDtGu7iYnHHYrzg8tIxSOyA4nYZqm4ZX+67CYTRwsrANMuIh0zmG34XhbGeZWtjG9tCk7nIRdm1yD\na9OPs10VsFr4FkT6YTaZcLarEls7QQxMGv9YrcnFTVxf9+JkRxl3AusA3+2IDOC+o9UAgJf6FiVH\nkrgXriwAAB44Xis5EqJ3ipcVX8+AjSqvXou+X7CcqA9MuIgMoLelBEUFNrwxsIRgyLgzuVybflwd\nW0NjZSEaebwI6VBzdSEqnXm4PLICry8kO5xDC4YieGNwCY58G3qaS2SHQ2DCRWQIZpMJ9/RWwesP\n4dLIquxwDu3l/kVENA0PHK+RHQrRnqIbVaoRCEUM3TzfN76GbV8I57orYTbxo14P+LdAZBD3HYmW\nFV/uW5AcyeFENA0vXV2AzWri7kTStXcdrYHZpOCnl+YMu1GF5UT9YcJFZBDVpfloqyvC4JQLq54d\n2eHcscGpdax6fLirqxJ5ORbZ4RDty5Fvw5nOCiyueaHOuGWHc8c8W370ja+hrrwADZUs3esFEy4i\nA3nXkWpoAF7tN16pg83yZCQPnoz+O/3p5XnJkdy5n12eRzii7f43kD4w4SIykNOdFbBZTbu9UEbh\n2Q7gyugq6soL0FzNJ27Sv7baItSV5+PyyArcW37Z4RxYMBTBzy/Pw55jwT09LCfqCRMuIgPJy7Hg\nbGclVj0+9I8b50DrV/oXEY5Em+V5eC4ZgaIoePBkHcIRDS9eNU7f5PnhJWx4g7j/WA2PzdIZJlxE\nBvPw6ToAwDNvzkiO5GAiWvQDy2Yx4e4eNsuTcZzrrkSuzYwXriwgHNH/5HlN0/DshTkoCvAQy4m6\nw4SLyGAaKgvR0+TE8Iwb09f1P3l+aNqFZdcOznRWcNo1GUpejgX39FbBtenHlVH9ryiPz29g+vom\njreVoaw4T3Y4dBMmXEQG9OhdDQCMscr1L69PAwAePFknORKiO/fgiehK0c8vz0mO5PaevTALAHjk\ndL3kSGgvTLiIDKinqQR15fl4c2gZax6f7HD2Nbm4gYEpF7oanWipccgOh+iO1ZYXoKO+GANTLlxf\n98oOZ1/rGz5cVFdQV14A0VAsOxzaAxMuIgNSFAWPnm1ARNN2n2r16KnXoqtb77+7UXIkRIcX74f6\niY5XlH92eR4RTcPDp+u4MUWnmHARGdRd3ZUoKrDhxasLujzzbWF1G5dGVtBcXYiuRqfscIgO7ZQo\nR4UzDy/1LepyRTkQDOOFKwvIz7XgHE9x0C0mXEQGZTGb8PCpOvgCYV1uW3/69WloAB4/18QnbjI0\ns8mED9zThHBEw49jPYl68urAdWztBPHA8VrYrBwFoVdMuIgM7N0napFjNePZC7MIhfWzbX3Vs4PX\nB5dQXWrHiY4y2eEQJexcT2V0levqgq5WuQLBMH74yhSsFhPec4obU/SMCReRgeXnWvGuo9Vwbfrx\n5tCS7HB2PfPGLMIRDY+fa4SJq1uUAd62yvXalOxwdv300jxcm348fKoOzsIc2eHQLTDhIjK4956p\nh9mk4AcvTSIYCssOBxvbAbzYt4BSRy7uYj8JZZBzPZWojPVy6eEAea8vhKden0ZejgXvO8eNKXrH\nhIvI4MqK8/CeU3VY9fjw3EX5s4KevTCLYCiCx+5qgMXMtxjKHGaTCR+4N7rKFd+BK9Mzb85gayeI\n993VgII8DhXWO74bEmWAD9zbhII8K3706hQ2vAFpcax6dvDs+VkU5dvwrqPV0uIgSpW7uvWxyrWx\nHcBPzs/CkW/joFODYMJFlAHyc6340H3N2PGH8c8vTUqL49vPjyEQiuDjD7ZytxRlpBtXuX4scZXr\nR69OwR8M4wP3NPGQaoNgwkWUIR44XoOqEjt+fmUe8ytbab9+3/gaLo2soKOuCHf3VKX9+kTpcld3\nJapK7Hjx6gImFzfSfv1V9w5+fmUeZUW5eOB4TdqvT4fDhIsoQ1jMJnzioTZoGvAPPxtP67WDoTC+\n+ewITIqCf/VewblblNHMJhM+/aiApgFffWoo7SNZvv/SJEJhDR+5v4V9kgbCvymiDHKstRRdjU70\nT6zh2sRa2q779BszWHbv4OHTdairKEjbdYlk6Wp04v5jNZhb2cbTaRyG2je+itcGrqO+ooC7gA2G\nCRdRBlEUBZ96TzsUAN96fhSBYOrHRKy4d/Dj16ZRlG/Dh+5rTvn1iPTiEw+2orjAhh++OoX51e2U\nX2/DG8BXnhqGxazgf3l/F2fcGQwTLqIMU19RgIdO1mFxzYtvPjeS8ut967lRBEMRfPKhNuTlWFJ+\nPSK9sOda8elHBUJhDf/f00OIRLSUXUvTNHzt6WFsbAfw0ftb0VBZmLJrUWow4SLKQJ94qBUNlQV4\n8eoiXu5bTNl1Xry6gCtjqxD1xSxvUFY60V6Os10VGJ/fwPOXUjcH76W+RVweXUVnQzHee5ZjIIyI\nCRdRBrJazPjCR44gL8eCb/xExexy8nctDk278PfPqCjIs+Kzj3eyUZ6y1i893IH8XAu+98IEFteS\nX1pccnnxredGkZdjweee6GYp0aCYcBFlqIriPHzu/V0IhCL4y+/3Y8cfStr3vr7uxV9+vx8A8K8/\n0osKpz1p35vIaBz5NvzyezvgD4bxh9+5gvWN5B1uHY5E8OUfDsIfDOPTj3agxJGbtO9N6cWEiyiD\nnegox2N3NWDJtYOvPj0MTUu8x2RrJ4g/+cer2PaF8CuPdUI0OJMQKZGxneuuwkfvb8Hahh///dtX\nsLGd+IkPwVAE/+8/D2B8YQN3dVfiXDfn2xkZEy6iDPfR+1vQUVeEC8PL+MazIwnNDAqFo6tlS64d\nPH6uEffx+B6iXe+/uxHvu6sB19e9+MPvXIHXFzz09/IHw/izf+rDRXUFor4Yn3lUJDFSkkE57BOv\nEOLjAP4vAJ0Azqiqemmf1z0G4I8BmAF8WVXV/3a7772yspm6rR5EWci95ccffucK5la20dlQjN/8\ncC8K7bY7+h4b2wF85akh9I2v4WRHOb7wkV72khDdRNM0/P0zKn5+ZQFtdUX47U8cv+Ojd7y+EP7k\nu1cxOufB0dZSfOHDvTwqS+fKywtv+2aYyApXP4CPAHhxvxcIIcwA/hzAYwC6AfyiEKIrgWsS0SEU\nF+Tg9z59Cic7yjE848b//bULmLuDRvrLoyv4T3/3BvrG19DV6MSvs3GXaE9K7LSFu7orMTbnwe9/\n4yJGZt0H/vMb3gD+4FuXMTrnwdmuCnzxo0eYbGWIQ69wxQkhfgbgt/da4RJC3A3gv6iq+ljs698B\nAFVV/+utvidXuIhSI6JpePLlSTz5yhRyrGZ88qE2nO6sQEGedc/X7/hD+Pbzo3ipbxEWswkfe6AF\nD5+pZ7JFdBuhcARff0bdHctyWpTj4w+2obw4b8/Xr7p38NzFObzUt4Adfxj3H6vGZx7thMnEe80I\nDrLCleophbUAZm/4eg7AXSm+JhHtw6Qo+PC7WlBXXoAv/3gQX39GxTd+MgLRUIyTHeXoqC/G0roX\nM8tbmFnaxMTCBrZ2gmioKMCvf6AbteU8tofoICxmE37t8S48cLwG335uFBfUFVwZW8W7jtWgsjgP\nebkW2HOsMJsUvDpwHRfVZWgaUJRvwwfvbcZ7z9Rz1EqGuWXCJYR4FsBe2yJ+T1XVHx7g+3OlikiH\nTnhSKc0AAAWJSURBVHdWoKmqEG8MLeHSyAqGpl0Ymna943XOwhw8cU8TPnhvEw/JJTqE1poi/N6n\nT+HNoWX848/H8LNL83u+rqGiAI+cqcfZrkpYLbzXMtEtEy5VVR9J8PvPA7hxJG49oqtct3SQpTki\nSkx5eSG62ivwq7IDIcoCT1Q48MQDbbLDIImSVVLcL0G6AKBdCNEEYAHAJwH8YpKuSURERGQIh163\nFEJ8RAgxC+AcgB8LIZ6O/X6NEOLHAKCqagjAFwE8A2AQwHdUVR1KPGwiIiIi40h4lyIRERER3Ro7\n84iIiIhSjAkXERERUYox4SIiIiJKsVQPPj0UIcRZRI8EsgIIAfiCqqrn5UalD0KIfwPgCwDCAH6s\nqup/kBySbgghfhvAHwAoU1V1XXY8sgkh/gDAEwACAMYBfFZVVY/cqOQ4zJmumU4IUQ/g6wAqEJ2Z\n+Deqqv6p3Kj0I3Y03QUAc6qqfkB2PLIJIYoBfBlAD6L/Xn5NVdXX5UYlnxDidwH8KwARRI88/Kyq\nqv69XqvXFa7/B8B/UlX1BID/HPs66wkhHgTwQQBHVVXtBfDfJYekG7EPj0cATMuORUd+AqBHVdVj\nAEYA/K7keKTgma77CgL431RV7UF0t/m/5s/lbf4torvrubMs6k8APKWqaheAowCyfuJAbOTVrwM4\nqarqEUQf6D613+v1mnAtAiiK/boY0QGqBPwmgN9XVTUIAKqqrkiOR0/+EMD/ITsIPVFV9VlVVSOx\nL98AUCczHonOAhhTVXUqdu98G8CHJMcknaqq11VVvRL79RaiH6A1cqPSByFEHYDHEV3RyfpB3EKI\nIgDvUlX1K0B05FO2rpbfZAPRBxe7EMICwI5b5Ct6Tbh+B8D/EELMIFoiyson8z20A7hfCPG6EOLn\nQojTsgPSAyHEhxBd9u+THYuO/RqAp2QHIcleZ7rWSopFl2JP6icQTcwJ+CMA/x7RMhEBzQBWhBBf\nFUJcEkL8rRDCLjso2WKtK/8DwAyiw93dqqo+t9/rpfVw3eKcxv8I4EsAvqSq6veFEB8H8BVEy0UZ\n7zY/FwsAp6qq54QQZwD8A4CWdMYny21+Lr8L4L03/F7WPJEe5LxTIcR/BBBQVfWbaQ1OP1gSugUh\nRAGA7wL4t7GVrqwmhHgCwLKqqpeFEO+WHY9OWACcBPBFVVXPCyH+GNGFkf8sNyy5hBCtAH4LQBMA\nD4B/FEL8sqqq/3Ov10tLuG51TqMQ4huqqj4c+/K7iC7rZoXb/Fx+E8D3Yq87L4SICCFKVVVdS1uA\nkuz3cxFC9CL69HVVCAFEy2YXhRBnVVVdTmOIUtzuvFMhxK8iWhp5T1oC0qdDnemaDYQQVgD/BOAb\nqqr+QHY8OnEPgA8KIR4HkAvAIYT4uqqqn5Ecl0xziFYR4pvXvotowpXtTgN4Nf4ZLIT4HqL/fvZM\nuPRaUhwTQjwQ+/VDiDb8EvADRH8eEEJ0ALBlQ7J1K6qqXlNVtVJV1WZVVZsRfWM4mQ3J1u3Edub9\newAfUlXVJzseiXbPdBVC2BA90/VJyTFJJ4RQAPwdgEFVVf9Ydjx6oarq76mqWh97P/kUgJ9mebIF\nVVWvA5iNfe4AwMMABiSGpBfDAM4JIfJi99PDiG602JMux0IA+A0AfyGEyAGwE/uaoqXVrwgh+hHd\n6p/VbwL7YPnoLX8GwAbg2djq32uqqn5Bbkjpp6pqSAgRP9PVDODveKYrAOBeRLez9wkhLsd+73dV\nVf0XiTHpEd9Tov4NgP8Ze2gZB/BZyfFIp6rqVSHE1xF9qIsAuATgb/Z7Pc9SJCIiIkoxvZYUiYiI\niDIGEy4iIiKiFGPCRURERJRiTLiIiIiIUowJFxEREVGKMeEiIiIiSjEmXEREREQpxoSLiIiIKMX+\nf/L6tJpLceoaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1138a7f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(rc={\"figure.figsize\": (10, 5)})\n",
    "# sns.plotting_context\n",
    "plt.plot(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Les palettes de couleurs peuvent être modifiées avec `color_palette` et `set_palette`:\n",
    "\n",
    "    * deep\n",
    "    * muted\n",
    "    * pastel\n",
    "    * bright\n",
    "    * dark\n",
    "    * colorblind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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pRBkPpYxlLR/Q7HkMA8jJofJMONDR5sYtraRr3LWk+F3go3q9/qher4+Afwz8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\nmR8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113a65150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#print sns.color_palette(\"deep\")\n",
    "sns.set_palette(\"pastel\")\n",
    "plt.plot(x, y)\n",
    "plt.plot(x, np.cos(x));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## jointplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AOdv093+yRmXaN0THCVoeSX+8tA6cqgJTAdul0w06z5ECmbAmWREBnuoxTUGk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OD6awD+u7W1tZ98mBsehsV3EPi6YfEgPUMwgWtHFGe0XaA5iOrZqRJRu3UBPbZr0GShK94k7bWD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\nMQzDMKWEExTDMAxTSjhBMQzDMKXk/wE7sHkhT3UCvwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112ab5910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.random.normal(0, 1, size=5000)\n",
    "y = np.random.normal(2, 0.5, size=5000)\n",
    "\n",
    "with sns.axes_style(\"white\"):\n",
    "    sns.jointplot(x, y, kind=\"hexbin\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Estimer la densité des observations avec *rugplot* et *kdeplot*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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F4yzjf9blPPXCSn7q3fZEsUW++NSrSSZborYrw1PPLyfZuRK1dnnD6VuumcuhF3uZm1te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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11392c4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.random.normal(size=200)\n",
    "sns.set_palette(\"muted\", 1)\n",
    "plt.hist(data, alpha=0.3)\n",
    "sns.rugplot(data);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11371cc90>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+qnKvS5Iid8mWLWOMH/g6sAlYAdxvjGm54LQu4E+Av/uIH+ECt1lr1yloieSG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\nFv3/nNfOqmFjWIUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113702cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.hist(data, alpha=0.3, normed=True);\n",
    "sns.kdeplot(data, shade=True);\n",
    "#sns.kdeplot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Estimation de la densité des données multidimensionnelles avec *kdeplot*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = np.random.normal(size=200)\n",
    "y = np.random.normal(size=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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QRs1ZKClPRNWehfK2HxTx5NfQgHqhpEfnfv7Yzv8Dkks9+1Rrqr7rxoTrdNlY8eiJ5xJS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\ntvxgAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1137f6850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# shade: True, False\n",
    "# cmap: \"Purples\", \"PuRd_d\", \"BuGn_d\", ...\n",
    "sns.kdeplot(x, y, shade=True, cmap=\"Purples\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparer les distributions avec *boxplot* et *violinplot*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = [x, y]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FBwoAYJAOFEuz2B0Au40OFCvJYncArDIdKJZmsTsAdhsdKACAQQIUALvG3r2nrvx8TXYG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\nCgBgkAAFADBIgAIAGPS/ARk63c6VXq+jAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113813250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Boxplot avec matplotlib\")\n",
    "plt.boxplot(data);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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J7lpVxyX5pyRPSHLGpEUBAMyziabwuvv6JM9MckGSzyX5k+62gBwAWNMmvqBCd78/yfun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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1136c1090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Boxplot avec seaborn\")\n",
    "sns.boxplot(data, names=[\"group1\", \"group2\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Y7XazJDcXj8PeNmPBWIyd4TA+n49Pf+aLTJo02dZ6hBC3Ztu2zbz00vOMUFXuzM/v0V13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\nEqAAAHoSoAAAehKgAAB6EqAAAHr6Pwog7+vq7GAlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113be67d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(data, names=[\"group1\", \"group1\"], color=\"indianred\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modèles linéaires"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips = sns.load_dataset(\"tips\")\n",
    "tips.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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h8BTwBrDSGPNmPCsmIpLq+mTbbhGR/kgruUREHKIAKyLiEAVYERGH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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114304590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5.5, 5))\n",
    "ar, br = scipy.polyfit(tips.total_bill, tips.tip, 1)\n",
    "plt.scatter(tips.total_bill, tips.tip);\n",
    "xr = scipy.polyval([ar,br], tips.total_bill)\n",
    "plt.plot(tips.total_bill, xr, 'r-');\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x11431a8d0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ojd6yeZPr01nypoWiKFybtpuqn/pJdVP17XcGeGpHhJXh8j9/ywS3C0IBqfEV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\nfLG/XwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1138097d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(\"total_bill\", \"tip\", data=tips, ci=68);\n",
    "# ci (intervalle de confiance par défaut 95%) "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}