{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualisation de données avec pandas et matplotlib\n",
    "\n",
    "##### Germain Salvato Vallverdu [germain.vallverdu@univ-pau.fr](germain.vallverdu@univ-pau.fr)\n",
    "\n",
    "Ce notebook présente l'utilisation de [`pandas`](http://pandas.pydata.org/) et \n",
    "de [`matplotlib`](http://matplotlib.org/) pour la lecture de données en python \n",
    "et la constructions de quelques représentations graphiques avec matplotlib.\n",
    "Les données utilisées dans cet exemple sont issues de la base de données ouverte de \n",
    "la Communauté d'Agglomération de Pau-Pyrénées (CAPP) [opendata.agglo-pau.fr](opendata.agglo-pau.fr). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chargement des données à partir d'un fichier CSV\n",
    "\n",
    "Les données proviennent de http://opendata.agglo-pau.fr/index.php/fiche?idQ=27\n",
    "\n",
    "Lors du téléchargement de l'archive, le fichier csv contient les données et un fichiers excel décrit le contenu de chaque colonne.\n",
    "\n",
    "Ici, le fichier csv est lu directement avec la fonction `read_csv` de pandas, en précisant que le séparateur est un point virgule. Cette fonction retourne un objet `DataFrame` qui s'apparente à un tableau de données. On précise également que `LIBGEO`, le nom de la commune, sera utilisé comme index de la `DataFrame` de pandas. Chaque ligne portera alors le nom de la ville correspondante."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ccodgeo</th>\n",
       "      <th>reg</th>\n",
       "      <th>dep</th>\n",
       "      <th>arr</th>\n",
       "      <th>cv</th>\n",
       "      <th>ze2010</th>\n",
       "      <th>id_modif_geo</th>\n",
       "      <th>p11_pop</th>\n",
       "      <th>p99_pop</th>\n",
       "      <th>d90_pop</th>\n",
       "      <th>...</th>\n",
       "      <th>c10_pop55p</th>\n",
       "      <th>c10_pop55p_cs1</th>\n",
       "      <th>c10_pop55p_cs2</th>\n",
       "      <th>c10_pop55p_cs3</th>\n",
       "      <th>c10_pop55p_cs4</th>\n",
       "      <th>c10_pop55p_cs5</th>\n",
       "      <th>c10_pop55p_cs6</th>\n",
       "      <th>c10_pop55p_cs7</th>\n",
       "      <th>c10_pop55p_cs8</th>\n",
       "      <th>evol99_11</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>libgeo</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",
       "      <th></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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ARTIGUELOUTAN</th>\n",
       "      <td>64059</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6431</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>944</td>\n",
       "      <td>722.0</td>\n",
       "      <td>669</td>\n",
       "      <td>...</td>\n",
       "      <td>256</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>180</td>\n",
       "      <td>16</td>\n",
       "      <td>30.747922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILLERE</th>\n",
       "      <td>64129</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6451</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>13343</td>\n",
       "      <td>13390.0</td>\n",
       "      <td>12570</td>\n",
       "      <td>...</td>\n",
       "      <td>4245</td>\n",
       "      <td>9</td>\n",
       "      <td>47</td>\n",
       "      <td>188</td>\n",
       "      <td>185</td>\n",
       "      <td>289</td>\n",
       "      <td>101</td>\n",
       "      <td>3150</td>\n",
       "      <td>276</td>\n",
       "      <td>-0.351008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BIZANOS</th>\n",
       "      <td>64132</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6447</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>4773</td>\n",
       "      <td>4674.0</td>\n",
       "      <td>4298</td>\n",
       "      <td>...</td>\n",
       "      <td>1754</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>124</td>\n",
       "      <td>80</td>\n",
       "      <td>52</td>\n",
       "      <td>44</td>\n",
       "      <td>1337</td>\n",
       "      <td>76</td>\n",
       "      <td>2.118100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAN</th>\n",
       "      <td>64230</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6446</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>5481</td>\n",
       "      <td>4961.0</td>\n",
       "      <td>4724</td>\n",
       "      <td>...</td>\n",
       "      <td>1890</td>\n",
       "      <td>12</td>\n",
       "      <td>55</td>\n",
       "      <td>95</td>\n",
       "      <td>103</td>\n",
       "      <td>69</td>\n",
       "      <td>40</td>\n",
       "      <td>1411</td>\n",
       "      <td>106</td>\n",
       "      <td>10.481758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GELOS</th>\n",
       "      <td>64237</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6448</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>3620</td>\n",
       "      <td>3665.0</td>\n",
       "      <td>3529</td>\n",
       "      <td>...</td>\n",
       "      <td>1262</td>\n",
       "      <td>8</td>\n",
       "      <td>24</td>\n",
       "      <td>36</td>\n",
       "      <td>56</td>\n",
       "      <td>72</td>\n",
       "      <td>45</td>\n",
       "      <td>917</td>\n",
       "      <td>104</td>\n",
       "      <td>-1.227831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IDRON</th>\n",
       "      <td>64269</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6431</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>4091</td>\n",
       "      <td>5151.0</td>\n",
       "      <td>2311</td>\n",
       "      <td>...</td>\n",
       "      <td>1144</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>100</td>\n",
       "      <td>96</td>\n",
       "      <td>59</td>\n",
       "      <td>13</td>\n",
       "      <td>763</td>\n",
       "      <td>75</td>\n",
       "      <td>-20.578528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JURANCON</th>\n",
       "      <td>64284</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6446</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>7037</td>\n",
       "      <td>7381.0</td>\n",
       "      <td>7538</td>\n",
       "      <td>...</td>\n",
       "      <td>2494</td>\n",
       "      <td>0</td>\n",
       "      <td>44</td>\n",
       "      <td>104</td>\n",
       "      <td>164</td>\n",
       "      <td>124</td>\n",
       "      <td>96</td>\n",
       "      <td>1744</td>\n",
       "      <td>217</td>\n",
       "      <td>-4.660615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEE</th>\n",
       "      <td>64329</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6431</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>1213</td>\n",
       "      <td>779.0</td>\n",
       "      <td>446</td>\n",
       "      <td>...</td>\n",
       "      <td>300</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>51</td>\n",
       "      <td>16</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>199</td>\n",
       "      <td>20</td>\n",
       "      <td>55.712452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LESCAR</th>\n",
       "      <td>64335</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6419</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>10030</td>\n",
       "      <td>8191.0</td>\n",
       "      <td>5793</td>\n",
       "      <td>...</td>\n",
       "      <td>2733</td>\n",
       "      <td>12</td>\n",
       "      <td>54</td>\n",
       "      <td>207</td>\n",
       "      <td>120</td>\n",
       "      <td>107</td>\n",
       "      <td>87</td>\n",
       "      <td>1912</td>\n",
       "      <td>233</td>\n",
       "      <td>22.451471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LONS</th>\n",
       "      <td>64348</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6419</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>12304</td>\n",
       "      <td>11153.0</td>\n",
       "      <td>9254</td>\n",
       "      <td>...</td>\n",
       "      <td>3696</td>\n",
       "      <td>9</td>\n",
       "      <td>62</td>\n",
       "      <td>183</td>\n",
       "      <td>171</td>\n",
       "      <td>249</td>\n",
       "      <td>146</td>\n",
       "      <td>2603</td>\n",
       "      <td>273</td>\n",
       "      <td>10.320093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAZERES-LEZONS</th>\n",
       "      <td>64373</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6448</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>1921</td>\n",
       "      <td>2143.0</td>\n",
       "      <td>2079</td>\n",
       "      <td>...</td>\n",
       "      <td>743</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12</td>\n",
       "      <td>41</td>\n",
       "      <td>9</td>\n",
       "      <td>597</td>\n",
       "      <td>53</td>\n",
       "      <td>-10.359309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OUSSE</th>\n",
       "      <td>64439</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6431</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>1554</td>\n",
       "      <td>NaN</td>\n",
       "      <td>937</td>\n",
       "      <td>...</td>\n",
       "      <td>388</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>44</td>\n",
       "      <td>17</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>253</td>\n",
       "      <td>35</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAU</th>\n",
       "      <td>64445</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6499</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>79798</td>\n",
       "      <td>78800.0</td>\n",
       "      <td>82157</td>\n",
       "      <td>...</td>\n",
       "      <td>26112</td>\n",
       "      <td>9</td>\n",
       "      <td>383</td>\n",
       "      <td>1078</td>\n",
       "      <td>1155</td>\n",
       "      <td>1535</td>\n",
       "      <td>752</td>\n",
       "      <td>18870</td>\n",
       "      <td>2330</td>\n",
       "      <td>1.266497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SENDETS</th>\n",
       "      <td>64518</td>\n",
       "      <td>72</td>\n",
       "      <td>64</td>\n",
       "      <td>643</td>\n",
       "      <td>6423</td>\n",
       "      <td>7214</td>\n",
       "      <td>ZZZZZZ</td>\n",
       "      <td>873</td>\n",
       "      <td>NaN</td>\n",
       "      <td>640</td>\n",
       "      <td>...</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>16</td>\n",
       "      <td>4</td>\n",
       "      <td>199</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14 rows × 148 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                ccodgeo  reg  dep  arr    cv  ze2010 id_modif_geo  p11_pop  \\\n",
       "libgeo                                                                       \n",
       "ARTIGUELOUTAN     64059   72   64  643  6431    7214       ZZZZZZ      944   \n",
       "BILLERE           64129   72   64  643  6451    7214       ZZZZZZ    13343   \n",
       "BIZANOS           64132   72   64  643  6447    7214       ZZZZZZ     4773   \n",
       "GAN               64230   72   64  643  6446    7214       ZZZZZZ     5481   \n",
       "GELOS             64237   72   64  643  6448    7214       ZZZZZZ     3620   \n",
       "IDRON             64269   72   64  643  6431    7214       ZZZZZZ     4091   \n",
       "JURANCON          64284   72   64  643  6446    7214       ZZZZZZ     7037   \n",
       "LEE               64329   72   64  643  6431    7214       ZZZZZZ     1213   \n",
       "LESCAR            64335   72   64  643  6419    7214       ZZZZZZ    10030   \n",
       "LONS              64348   72   64  643  6419    7214       ZZZZZZ    12304   \n",
       "MAZERES-LEZONS    64373   72   64  643  6448    7214       ZZZZZZ     1921   \n",
       "OUSSE             64439   72   64  643  6431    7214       ZZZZZZ     1554   \n",
       "PAU               64445   72   64  643  6499    7214       ZZZZZZ    79798   \n",
       "SENDETS           64518   72   64  643  6423    7214       ZZZZZZ      873   \n",
       "\n",
       "                p99_pop  d90_pop    ...      c10_pop55p  c10_pop55p_cs1  \\\n",
       "libgeo                              ...                                   \n",
       "ARTIGUELOUTAN     722.0      669    ...             256               8   \n",
       "BILLERE         13390.0    12570    ...            4245               9   \n",
       "BIZANOS          4674.0     4298    ...            1754               0   \n",
       "GAN              4961.0     4724    ...            1890              12   \n",
       "GELOS            3665.0     3529    ...            1262               8   \n",
       "IDRON            5151.0     2311    ...            1144               0   \n",
       "JURANCON         7381.0     7538    ...            2494               0   \n",
       "LEE               779.0      446    ...             300               0   \n",
       "LESCAR           8191.0     5793    ...            2733              12   \n",
       "LONS            11153.0     9254    ...            3696               9   \n",
       "MAZERES-LEZONS   2143.0     2079    ...             743               8   \n",
       "OUSSE               NaN      937    ...             388               0   \n",
       "PAU             78800.0    82157    ...           26112               9   \n",
       "SENDETS             NaN      640    ...             256               0   \n",
       "\n",
       "                c10_pop55p_cs2  c10_pop55p_cs3  c10_pop55p_cs4  \\\n",
       "libgeo                                                           \n",
       "ARTIGUELOUTAN                4               8              12   \n",
       "BILLERE                     47             188             185   \n",
       "BIZANOS                     40             124              80   \n",
       "GAN                         55              95             103   \n",
       "GELOS                       24              36              56   \n",
       "IDRON                       38             100              96   \n",
       "JURANCON                    44             104             164   \n",
       "LEE                          4              51              16   \n",
       "LESCAR                      54             207             120   \n",
       "LONS                        62             183             171   \n",
       "MAZERES-LEZONS               4              20              12   \n",
       "OUSSE                       17              44              17   \n",
       "PAU                        383            1078            1155   \n",
       "SENDETS                      0              24               8   \n",
       "\n",
       "                c10_pop55p_cs5  c10_pop55p_cs6  c10_pop55p_cs7  \\\n",
       "libgeo                                                           \n",
       "ARTIGUELOUTAN               16              12             180   \n",
       "BILLERE                    289             101            3150   \n",
       "BIZANOS                     52              44            1337   \n",
       "GAN                         69              40            1411   \n",
       "GELOS                       72              45             917   \n",
       "IDRON                       59              13             763   \n",
       "JURANCON                   124              96            1744   \n",
       "LEE                          8               4             199   \n",
       "LESCAR                     107              87            1912   \n",
       "LONS                       249             146            2603   \n",
       "MAZERES-LEZONS              41               9             597   \n",
       "OUSSE                       22               0             253   \n",
       "PAU                       1535             752           18870   \n",
       "SENDETS                     16               4             199   \n",
       "\n",
       "                c10_pop55p_cs8  evol99_11  \n",
       "libgeo                                     \n",
       "ARTIGUELOUTAN               16  30.747922  \n",
       "BILLERE                    276  -0.351008  \n",
       "BIZANOS                     76   2.118100  \n",
       "GAN                        106  10.481758  \n",
       "GELOS                      104  -1.227831  \n",
       "IDRON                       75 -20.578528  \n",
       "JURANCON                   217  -4.660615  \n",
       "LEE                         20  55.712452  \n",
       "LESCAR                     233  22.451471  \n",
       "LONS                       273  10.320093  \n",
       "MAZERES-LEZONS              53 -10.359309  \n",
       "OUSSE                       35        NaN  \n",
       "PAU                       2330   1.266497  \n",
       "SENDETS                      4        NaN  \n",
       "\n",
       "[14 rows x 148 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"Evolution_et_structure_de_la_population/Evolution_structure_population.csv\", sep=\";\")\n",
    "df = df.set_index(\"libgeo\")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Un diagramme en barres\n",
    "\n",
    "Premièrement nous allons construire un graphique sous forme de barres horizontales, représentant la population dans chaque ville de l'aglomération de Pau-Pyrénées en 2011.\n",
    "\n",
    "Nous utiliserons un diagramme en barre horizontale avec la fonction `barh` de matplotlib ([exemple](http://matplotlib.org/examples/lines_bars_and_markers/barh_demo.html)).\n",
    "\n",
    "Commençons par extraire la colonne qui nous intéresse (`P11_POP`) et classons les valeurs par ordre croissant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "libgeo\n",
       "SENDETS             873\n",
       "ARTIGUELOUTAN       944\n",
       "LEE                1213\n",
       "OUSSE              1554\n",
       "MAZERES-LEZONS     1921\n",
       "GELOS              3620\n",
       "IDRON              4091\n",
       "BIZANOS            4773\n",
       "GAN                5481\n",
       "JURANCON           7037\n",
       "LESCAR            10030\n",
       "LONS              12304\n",
       "BILLERE           13343\n",
       "PAU               79798\n",
       "Name: p11_pop, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pop11 = df[\"p11_pop\"]\n",
    "pop11 = pop11.sort_values(ascending=True)\n",
    "pop11"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Construisons maintenant le graphique avec les données ci-dessus. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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GxLcbNrmK/FX7muSLsR4HdoqI/hssHEFeam0Q2I+8skOHPELZ1O96348k3yjjhWqbD5O/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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c2180b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# figure\n",
    "fig = plt.figure(figsize=(10, 10))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_title(\"Population de la CAPP en 2011\", fontsize=20)\n",
    "# bar plot\n",
    "ax.barh(\n",
    "    # position et longueur des barres\n",
    "    bottom=range(pop11.count()), \n",
    "    width=pop11,\n",
    "    # labels\n",
    "    align=\"center\", \n",
    "    tick_label=pop11.index,\n",
    "    # couleurs et traits\n",
    "    color=\"RoyalBlue\",\n",
    "    linewidth=0\n",
    ")\n",
    "# format axis\n",
    "ax.set_frame_on(False)\n",
    "ax.set_xticks([])\n",
    "ax.tick_params(\"both\", length=0)\n",
    "ax.vlines(0, -1, pop11.count(), color=\"gray\", linewidth=4)\n",
    "# add the value at the end of the bar\n",
    "for y, pop in enumerate(pop11):\n",
    "    ax.annotate(\n",
    "        # texte\n",
    "        \"%.0f\" % pop,\n",
    "        # position\n",
    "        xy=(pop, y), \n",
    "        xytext=(5, -4), \n",
    "        textcoords=\"offset points\", \n",
    "        # format\n",
    "        fontsize=14, \n",
    "        color=\"RoyalBlue\"\n",
    "    )\n",
    "fig.savefig(\"barh_pop.png\", dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Réalisation d'une Treemap\n",
    "\n",
    "Pour faire ce graphique on va utiliser la librairie [`squarify`](https://pypi.python.org/pypi/python3-squarify/0.1.5). La superficie des rectangles représentera la superficie de la commune. Une échelle de couleur donnera la population de la commune."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import squarify"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extraction de la superficie des communes et de la population en 2011. Le tableau est trié par ordre décroissant de la superficie."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>superf</th>\n",
       "      <th>p11_pop</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>libgeo</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GAN</th>\n",
       "      <td>40</td>\n",
       "      <td>5481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAU</th>\n",
       "      <td>32</td>\n",
       "      <td>79798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LESCAR</th>\n",
       "      <td>27</td>\n",
       "      <td>10030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JURANCON</th>\n",
       "      <td>19</td>\n",
       "      <td>7037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LONS</th>\n",
       "      <td>12</td>\n",
       "      <td>12304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GELOS</th>\n",
       "      <td>11</td>\n",
       "      <td>3620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARTIGUELOUTAN</th>\n",
       "      <td>8</td>\n",
       "      <td>944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IDRON</th>\n",
       "      <td>8</td>\n",
       "      <td>4091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SENDETS</th>\n",
       "      <td>8</td>\n",
       "      <td>873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILLERE</th>\n",
       "      <td>5</td>\n",
       "      <td>13343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BIZANOS</th>\n",
       "      <td>4</td>\n",
       "      <td>4773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAZERES-LEZONS</th>\n",
       "      <td>4</td>\n",
       "      <td>1921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OUSSE</th>\n",
       "      <td>4</td>\n",
       "      <td>1554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEE</th>\n",
       "      <td>3</td>\n",
       "      <td>1213</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                superf  p11_pop\n",
       "libgeo                         \n",
       "GAN                 40     5481\n",
       "PAU                 32    79798\n",
       "LESCAR              27    10030\n",
       "JURANCON            19     7037\n",
       "LONS                12    12304\n",
       "GELOS               11     3620\n",
       "ARTIGUELOUTAN        8      944\n",
       "IDRON                8     4091\n",
       "SENDETS              8      873\n",
       "BILLERE              5    13343\n",
       "BIZANOS              4     4773\n",
       "MAZERES-LEZONS       4     1921\n",
       "OUSSE                4     1554\n",
       "LEE                  3     1213"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df[[\"superf\", \"p11_pop\"]]\n",
    "df2 = df2.sort_values(by=\"superf\", ascending=False)\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Superficie et population de Pau :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pau: superficie = 32 km2, population = 79798\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Pau: superficie = %d km2, population = %d\\n\" % (df2[\"superf\"][\"PAU\"], df2[\"p11_pop\"][\"PAU\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Représentation en Treemaps avec les fonctions inclues dans [`squarify`](https://pypi.python.org/pypi/python3-squarify/0.1.5)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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rksvz2KmVLYeINA5+cDGhZE+1+boiSu3HjVTUuD9Ws48lIybMJ3tBTtZmYNfaaDJexzSD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\nfJitW7fwt7++wpy582hsauQPfwzsp/y9797F3r17gMCOJ48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duVbtKOGLff8EAssxtnla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\nkgD/AEqFI3hgLMB7AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c216a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = 0.\n",
    "y = 0.\n",
    "width = 100.\n",
    "height = 100.\n",
    "cmap = matplotlib.cm.viridis\n",
    "\n",
    "# color scale on the population\n",
    "# min and max values without Pau\n",
    "mini, maxi = df2.drop(\"PAU\").p11_pop.min(), df2.drop(\"PAU\").p11_pop.max()\n",
    "norm = matplotlib.colors.Normalize(vmin=mini, vmax=maxi)\n",
    "colors = [cmap(norm(value)) for value in df2.p11_pop]\n",
    "colors[1] = \"#FBFCFE\"\n",
    "\n",
    "# labels for squares\n",
    "labels = [\"%s\\n%d km2\\n%d hab\" % (label) for label in zip(df2.index, df2.superf, df2.p11_pop)]\n",
    "labels[11] = \"MAZERES-\\nLEZONS\\n%d km2\\n%d hab\" % (df2[\"superf\"][\"MAZERES-LEZONS\"], df2[\"p11_pop\"][\"MAZERES-LEZONS\"])\n",
    "\n",
    "# make plot\n",
    "fig = plt.figure(figsize=(12, 10))\n",
    "fig.suptitle(\"Population et superficie des communes de la CAPP\", fontsize=20)\n",
    "ax = fig.add_subplot(111, aspect=\"equal\")\n",
    "ax = squarify.plot(df2.superf, color=colors, label=labels, ax=ax, alpha=.7)\n",
    "ax.set_xticks([])\n",
    "ax.set_yticks([])\n",
    "ax.set_title(\"L'aire de chaque carré est proportionnelle à la superficie de la commune\\n\", fontsize=14)\n",
    "\n",
    "# color bar\n",
    "# create dummy invisible image with a color map\n",
    "img = plt.imshow([df2.p11_pop], cmap=cmap)\n",
    "img.set_visible(False)\n",
    "fig.colorbar(img, orientation=\"vertical\", shrink=.96)\n",
    "\n",
    "fig.text(.76, .9, \"Population\", fontsize=14)\n",
    "fig.text(.5, 0.1,\n",
    "         \"Superficie totale %d km2, Population de la CAPP : %d hab\" % (df2.superf.sum(), df2.p11_pop.sum()),\n",
    "         fontsize=14,\n",
    "         ha=\"center\")\n",
    "fig.text(.5, 0.07,\n",
    "         \"Source : http://opendata.agglo-pau.fr/\",\n",
    "         fontsize=14,\n",
    "         ha=\"center\")\n",
    "\n",
    "fig.savefig(\"treemap_capp_pau.png\", dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Graphique xy classique\n",
    "\n",
    "Dans ce graphique nous allons simplement représenter le nombre de naissances et de décés à Pau entre 1999 et 2011. C'est un graphique très simple à réaliser avec pandas. Nous allons voir tout d'abord comment extraire les données puis nous ferons un premier graphique basique avec la fonction `plot()` de pandas. Ensuite, nous ajouterons une courbe de tendance linéaire avec [`lineregress()`](http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.stats.linregress.html) de scipy.\n",
    "\n",
    "Tout d'abord nous devons extraire les colonnes `NAISXX` et `DECEXX` du tableau global pour la ligne concernant Pau."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>deces</th>\n",
       "      <th>naissance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>773</td>\n",
       "      <td>900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>744</td>\n",
       "      <td>981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>768</td>\n",
       "      <td>936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>759</td>\n",
       "      <td>897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>797</td>\n",
       "      <td>952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>772</td>\n",
       "      <td>932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>794</td>\n",
       "      <td>909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>784</td>\n",
       "      <td>984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>744</td>\n",
       "      <td>879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>774</td>\n",
       "      <td>906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>736</td>\n",
       "      <td>913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>761</td>\n",
       "      <td>918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>720</td>\n",
       "      <td>851</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     deces naissance\n",
       "1999   773       900\n",
       "2000   744       981\n",
       "2001   768       936\n",
       "2002   759       897\n",
       "2003   797       952\n",
       "2004   772       932\n",
       "2005   794       909\n",
       "2006   784       984\n",
       "2007   744       879\n",
       "2008   774       906\n",
       "2009   736       913\n",
       "2010   761       918\n",
       "2011   720       851"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# noms des colonnes:\n",
    "years = [99] + list(range(0, 12))\n",
    "naissance = [\"nais%02d\" % y for y in years]\n",
    "deces = [\"dece%02d\" % y for y in years]\n",
    "\n",
    "# nouvelle DataFrame avec les deces et les naissances à Pau en fonction des années\n",
    "df4 = pd.DataFrame(\n",
    "    data={\n",
    "        \"naissance\": df.loc[\"PAU\", naissance].values, \n",
    "        \"deces\": df.loc[\"PAU\", deces].values\n",
    "    },\n",
    "    index=[1999 + i for i in range(0, 13)]\n",
    ")\n",
    "df4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "À partir de ce type de tableau, il est très simple de tracer des courbes avec la fonction `plot()` de `pandas`. Les arguments sont du même type que ceux de matplotlib :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10c2e1f60>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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kOlQ22Dmc8WmjjziTwW63803REiamj5OdCYUQPY4r926YiTHw8GEgEvgW+HXb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\nCUIIIYTwS5IEIYQQQvglSYIQQggh/Pp/HN7/KAamVa4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c218518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df4.plot(\n",
    "    marker=\"o\", \n",
    "    linestyle=\"dashed\", \n",
    "    title=\"Naissances et décés à Pau entre 1999 et 2011\",\n",
    "    figsize=(8, 6),\n",
    "    fontsize=16,\n",
    "    xlim=(1998, 2012)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ajoutons maintenant une courbe de tendance et ajoutons les données au tableau (bien que deux points seulement auraient suffit) :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>deces</th>\n",
       "      <th>naissance</th>\n",
       "      <th>trend_naissance</th>\n",
       "      <th>trend_deces</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>773</td>\n",
       "      <td>900</td>\n",
       "      <td>945.164835</td>\n",
       "      <td>777.054945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>744</td>\n",
       "      <td>981</td>\n",
       "      <td>940.945055</td>\n",
       "      <td>774.802198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>768</td>\n",
       "      <td>936</td>\n",
       "      <td>936.725275</td>\n",
       "      <td>772.549451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>759</td>\n",
       "      <td>897</td>\n",
       "      <td>932.505495</td>\n",
       "      <td>770.296703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>797</td>\n",
       "      <td>952</td>\n",
       "      <td>928.285714</td>\n",
       "      <td>768.043956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>772</td>\n",
       "      <td>932</td>\n",
       "      <td>924.065934</td>\n",
       "      <td>765.791209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>794</td>\n",
       "      <td>909</td>\n",
       "      <td>919.846154</td>\n",
       "      <td>763.538462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>784</td>\n",
       "      <td>984</td>\n",
       "      <td>915.626374</td>\n",
       "      <td>761.285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>744</td>\n",
       "      <td>879</td>\n",
       "      <td>911.406593</td>\n",
       "      <td>759.032967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>774</td>\n",
       "      <td>906</td>\n",
       "      <td>907.186813</td>\n",
       "      <td>756.780220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>736</td>\n",
       "      <td>913</td>\n",
       "      <td>902.967033</td>\n",
       "      <td>754.527473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>761</td>\n",
       "      <td>918</td>\n",
       "      <td>898.747253</td>\n",
       "      <td>752.274725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>720</td>\n",
       "      <td>851</td>\n",
       "      <td>894.527473</td>\n",
       "      <td>750.021978</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     deces naissance  trend_naissance  trend_deces\n",
       "1999   773       900       945.164835   777.054945\n",
       "2000   744       981       940.945055   774.802198\n",
       "2001   768       936       936.725275   772.549451\n",
       "2002   759       897       932.505495   770.296703\n",
       "2003   797       952       928.285714   768.043956\n",
       "2004   772       932       924.065934   765.791209\n",
       "2005   794       909       919.846154   763.538462\n",
       "2006   784       984       915.626374   761.285714\n",
       "2007   744       879       911.406593   759.032967\n",
       "2008   774       906       907.186813   756.780220\n",
       "2009   736       913       902.967033   754.527473\n",
       "2010   761       918       898.747253   752.274725\n",
       "2011   720       851       894.527473   750.021978"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import linregress\n",
    "# pour les naissances\n",
    "p_naissance, i_naissance, *others = linregress(x=df4.index, y=df4.naissance)\n",
    "df4[\"trend_naissance\"] = p_naissance * df4.index + i_naissance\n",
    "# pour les décés\n",
    "p_deces, i_deces, *others  = linregress(x=df4.index, y=df4.deces)\n",
    "df4[\"trend_deces\"] = p_deces * df4.index + i_deces\n",
    "\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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33fZFSkpK6e7uJhI50pB36dKzaWx0L+SBQJAPf/gqjj76GN797vfw5S/fTCQS5fLL349h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\nIiIoIBAREREUEIiIiAgKCERERAT4/9NEbXIW+4bsAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c2c0e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = sns.color_palette(\"husl\", 2)\n",
    "# figure\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_title(\"Naissances et décés à Pau entre 1999 et 2011\", color=\"#555555\")\n",
    "# plot the differents quantities\n",
    "ax.plot(df4.index, df4.naissance, marker=\"o\", label=\"Naissances\", linestyle=\"--\", linewidth=.5, color=colors[0])\n",
    "ax.plot(df4.index, df4.deces, marker=\"o\", label=\"Décés\", linestyle=\"--\", linewidth=.5, color=colors[1])\n",
    "ax.plot(df4.index, df4.trend_naissance, label=\"\", color=colors[0])\n",
    "ax.plot(df4.index, df4.trend_deces, label=\"\", color=colors[1])\n",
    "# format and style\n",
    "ax.set_xlabel(\"Année\")\n",
    "ax.set_ylabel(\"Nombre de naissances ou décés\")\n",
    "ax.legend()\n",
    "fig.savefig(\"xy_pop.png\", dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Camembert ou pie chart ou wedge chart\n",
    "\n",
    "Le fichiers de données de la CAPP contient aussi les catégorie socio-professionnelle pour chaque commune. Nous allons les représenter avec un diagramme de type camembert.\n",
    "\n",
    "Commençons par regrouper les données dans une nouvelle table et faisons la somme sur toutes les communes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Intermédiaires</th>\n",
       "      <th>Retraités</th>\n",
       "      <th>Autres</th>\n",
       "      <th>Employés</th>\n",
       "      <th>Cadres</th>\n",
       "      <th>agriculteurs</th>\n",
       "      <th>Ouvriers</th>\n",
       "      <th>Artisans</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>libgeo</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ARTIGUELOUTAN</th>\n",
       "      <td>164</td>\n",
       "      <td>184</td>\n",
       "      <td>80</td>\n",
       "      <td>140</td>\n",
       "      <td>40</td>\n",
       "      <td>24</td>\n",
       "      <td>72</td>\n",
       "      <td>20</td>\n",
       "      <td>724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILLERE</th>\n",
       "      <td>1790</td>\n",
       "      <td>3178</td>\n",
       "      <td>1325</td>\n",
       "      <td>2270</td>\n",
       "      <td>908</td>\n",
       "      <td>18</td>\n",
       "      <td>1352</td>\n",
       "      <td>245</td>\n",
       "      <td>11086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BIZANOS</th>\n",
       "      <td>534</td>\n",
       "      <td>1337</td>\n",
       "      <td>578</td>\n",
       "      <td>622</td>\n",
       "      <td>446</td>\n",
       "      <td>0</td>\n",
       "      <td>401</td>\n",
       "      <td>132</td>\n",
       "      <td>4050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAN</th>\n",
       "      <td>778</td>\n",
       "      <td>1415</td>\n",
       "      <td>450</td>\n",
       "      <td>658</td>\n",
       "      <td>393</td>\n",
       "      <td>36</td>\n",
       "      <td>406</td>\n",
       "      <td>209</td>\n",
       "      <td>4345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GELOS</th>\n",
       "      <td>483</td>\n",
       "      <td>921</td>\n",
       "      <td>491</td>\n",
       "      <td>498</td>\n",
       "      <td>246</td>\n",
       "      <td>20</td>\n",
       "      <td>293</td>\n",
       "      <td>127</td>\n",
       "      <td>3079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IDRON</th>\n",
       "      <td>554</td>\n",
       "      <td>763</td>\n",
       "      <td>587</td>\n",
       "      <td>436</td>\n",
       "      <td>507</td>\n",
       "      <td>4</td>\n",
       "      <td>193</td>\n",
       "      <td>159</td>\n",
       "      <td>3203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JURANCON</th>\n",
       "      <td>940</td>\n",
       "      <td>1761</td>\n",
       "      <td>900</td>\n",
       "      <td>932</td>\n",
       "      <td>428</td>\n",
       "      <td>16</td>\n",
       "      <td>755</td>\n",
       "      <td>183</td>\n",
       "      <td>5915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEE</th>\n",
       "      <td>183</td>\n",
       "      <td>199</td>\n",
       "      <td>172</td>\n",
       "      <td>98</td>\n",
       "      <td>172</td>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>43</td>\n",
       "      <td>941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LESCAR</th>\n",
       "      <td>1342</td>\n",
       "      <td>1920</td>\n",
       "      <td>1408</td>\n",
       "      <td>1222</td>\n",
       "      <td>965</td>\n",
       "      <td>21</td>\n",
       "      <td>925</td>\n",
       "      <td>310</td>\n",
       "      <td>8113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LONS</th>\n",
       "      <td>1646</td>\n",
       "      <td>2615</td>\n",
       "      <td>1604</td>\n",
       "      <td>1866</td>\n",
       "      <td>992</td>\n",
       "      <td>37</td>\n",
       "      <td>1028</td>\n",
       "      <td>319</td>\n",
       "      <td>10107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAZERES-LEZONS</th>\n",
       "      <td>226</td>\n",
       "      <td>597</td>\n",
       "      <td>230</td>\n",
       "      <td>286</td>\n",
       "      <td>98</td>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>15</td>\n",
       "      <td>1643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OUSSE</th>\n",
       "      <td>214</td>\n",
       "      <td>253</td>\n",
       "      <td>223</td>\n",
       "      <td>196</td>\n",
       "      <td>175</td>\n",
       "      <td>9</td>\n",
       "      <td>79</td>\n",
       "      <td>57</td>\n",
       "      <td>1206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAU</th>\n",
       "      <td>8991</td>\n",
       "      <td>19014</td>\n",
       "      <td>16149</td>\n",
       "      <td>11137</td>\n",
       "      <td>6083</td>\n",
       "      <td>35</td>\n",
       "      <td>7087</td>\n",
       "      <td>1724</td>\n",
       "      <td>70220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SENDETS</th>\n",
       "      <td>126</td>\n",
       "      <td>207</td>\n",
       "      <td>65</td>\n",
       "      <td>118</td>\n",
       "      <td>61</td>\n",
       "      <td>12</td>\n",
       "      <td>53</td>\n",
       "      <td>28</td>\n",
       "      <td>670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAPP</th>\n",
       "      <td>17971</td>\n",
       "      <td>34364</td>\n",
       "      <td>24262</td>\n",
       "      <td>20479</td>\n",
       "      <td>11514</td>\n",
       "      <td>244</td>\n",
       "      <td>12897</td>\n",
       "      <td>3571</td>\n",
       "      <td>125302</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Intermédiaires  Retraités  Autres  Employés  Cadres  \\\n",
       "libgeo                                                                \n",
       "ARTIGUELOUTAN              164        184      80       140      40   \n",
       "BILLERE                   1790       3178    1325      2270     908   \n",
       "BIZANOS                    534       1337     578       622     446   \n",
       "GAN                        778       1415     450       658     393   \n",
       "GELOS                      483        921     491       498     246   \n",
       "IDRON                      554        763     587       436     507   \n",
       "JURANCON                   940       1761     900       932     428   \n",
       "LEE                        183        199     172        98     172   \n",
       "LESCAR                    1342       1920    1408      1222     965   \n",
       "LONS                      1646       2615    1604      1866     992   \n",
       "MAZERES-LEZONS             226        597     230       286      98   \n",
       "OUSSE                      214        253     223       196     175   \n",
       "PAU                       8991      19014   16149     11137    6083   \n",
       "SENDETS                    126        207      65       118      61   \n",
       "CAPP                     17971      34364   24262     20479   11514   \n",
       "\n",
       "                agriculteurs  Ouvriers  Artisans   total  \n",
       "libgeo                                                    \n",
       "ARTIGUELOUTAN             24        72        20     724  \n",
       "BILLERE                   18      1352       245   11086  \n",
       "BIZANOS                    0       401       132    4050  \n",
       "GAN                       36       406       209    4345  \n",
       "GELOS                     20       293       127    3079  \n",
       "IDRON                      4       193       159    3203  \n",
       "JURANCON                  16       755       183    5915  \n",
       "LEE                        4        70        43     941  \n",
       "LESCAR                    21       925       310    8113  \n",
       "LONS                      37      1028       319   10107  \n",
       "MAZERES-LEZONS             8       183        15    1643  \n",
       "OUSSE                      9        79        57    1206  \n",
       "PAU                       35      7087      1724   70220  \n",
       "SENDETS                   12        53        28     670  \n",
       "CAPP                     244     12897      3571  125302  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns = {\n",
    "    \"c10_pop15p_cs1\": \"agriculteurs\",\n",
    "    \"c10_pop15p_cs2\": \"Artisans\",\n",
    "    \"c10_pop15p_cs3\": \"Cadres\",\n",
    "    \"c10_pop15p_cs4\": \"Intermédiaires\",\n",
    "    \"c10_pop15p_cs5\": \"Employés\",\n",
    "    \"c10_pop15p_cs6\": \"Ouvriers\",\n",
    "    \"c10_pop15p_cs7\": \"Retraités\",\n",
    "    \"c10_pop15p_cs8\": \"Autres\"\n",
    "}\n",
    "df_cat = df[list(columns.keys())]\n",
    "df_cat = df_cat.rename(columns=columns)\n",
    "# add the sum over CAPP\n",
    "df_cat.loc[\"CAPP\"] = df_cat.sum(axis=0)\n",
    "df_cat[\"total\"] = df_cat.sum(axis=1)\n",
    "df_cat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Construction du graphique :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FA4B9zWxl/G76gniT06m0n6cEfNSsa4BHzewGvAnmaniXjPtijMUQvafj+3Bn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\nr5ZfW6uNeg3Hkx3fHkLol1K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wHXAFPsrVyXiezzuLmVJK/w0h3ANsil+zlB0L3BRCGI/n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\naN2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44YYbzBbLPx9LfnoGrqIwBg/w6tzdzGnT3rJqRWH48vUcJXNEPDGaNLstHnL31oBy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iNYU1ODzZs3RwoLC6GUetw0zd+IyCG3cxERxTql1IhgIOk227YWThw3F+ee/e1gZtc+bsei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\nEBERERERERHFGRY6RERERERERERx5v8DZWfGHEw+ZgQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e596400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(18, 10))\n",
    "fig.suptitle(\"Catégories socio-professionnelles de la CAPP en 2010\\nPau et Billère\", fontsize=20, color=\"#444444\")\n",
    "width = .3\n",
    "\n",
    "# color scale\n",
    "colors = [\"#F4A460\", '#E24A33', '#348ABD', '#988ED5', '#777777', '#FBC15E', '#8EBA42', '#FFB5B8']\n",
    "\n",
    "# PAU et CAPP\n",
    "ax1 = fig.add_subplot(121, aspect=\"equal\")\n",
    "pau_pie = ax1.pie(\n",
    "    # data\n",
    "    df_cat.loc[\"PAU\"].drop(\"total\"), \n",
    "    # wedges\n",
    "    colors=colors, \n",
    "    radius=1, \n",
    "    wedgeprops={\"width\": width, \"linewidth\": 1},\n",
    "    # labels\n",
    "    autopct=\"%4.1f%%\",\n",
    "    pctdistance=.85\n",
    ")\n",
    "capp_pie = ax1.pie(\n",
    "    df_cat.loc[\"CAPP\"].drop(\"total\"), \n",
    "    colors=colors, \n",
    "    radius=1 - width,\n",
    "    wedgeprops={\"width\": width, \"linewidth\": 1},\n",
    "    autopct=\"%4.1f%%\",\n",
    "    pctdistance=.75\n",
    ")\n",
    "ax1.set_title(\"Pau\", fontsize=18, color=\"#555555\")\n",
    "ax1.text(.1, -.1, \"CAPP\", fontsize=18, color='#555555')\n",
    "ax1.text(.8, -.7, \"Pau\", size=18, color='#555555')\n",
    "\n",
    "# Billere et CAPP\n",
    "ax2 = fig.add_subplot(122, aspect=\"equal\")\n",
    "bill_pie = ax2.pie(\n",
    "    df_cat.loc[\"BILLERE\"].drop(\"total\"), \n",
    "    colors=colors, \n",
    "    radius=1, \n",
    "    wedgeprops={\"width\": width, \"linewidth\": 1},\n",
    "    autopct=\"%4.1f%%\",\n",
    "    pctdistance=.85\n",
    ")\n",
    "capp_pie = ax2.pie(\n",
    "    df_cat.loc[\"CAPP\"].drop(\"total\"), \n",
    "    colors=colors, \n",
    "    radius=1 - width,\n",
    "    wedgeprops={\"width\": width, \"linewidth\": 1},\n",
    "    autopct=\"%4.1f%%\",\n",
    "    pctdistance=.75\n",
    ")\n",
    "ax2.set_title(\"Billère\", fontsize=18, color=\"#555555\")\n",
    "ax2.text(.1, -.1, \"CAPP\", size=18, color='#555555')\n",
    "ax2.text(.8, -.7, \"Billère\", size=18, color='#555555')\n",
    "\n",
    "# legende\n",
    "fig.legend(pau_pie[0], df_cat.columns.values, fontsize=16)\n",
    "fig.subplots_adjust(wspace=0)\n",
    "fig.savefig(\"capp_pie.png\", dpi=300)"
   ]
  }
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