2015-2016/5e/Gestion_de_donnees/Tableau_graphique/Création de graphiques.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from opytex import texenv\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "plt.style.use(\"seaborn-notebook\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pymath as pm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Création de graphiques pour les 5e"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visite de villages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[48, 15, 36, 43, 25]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = pm.Dataset.random(5, distrib=\"randint\", rd_args=(10, 50))\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "villes = [\"Chiconi\", \"Sada\", \"Kaweni\", \"Dzaoudzi\", \"Bandrele\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ind = np.arange(5)\n",
    "width = 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Set the font dictionaries (for plot title and axis titles)\n",
    "title_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'20', 'color':'black', 'weight':'normal',\n",
    "              'verticalalignment':'bottom'} # Bottom vertical alignment for more space\n",
    "axis_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'16', 'color':'black', 'weight':'normal'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FtJD0SuAY4OyhBCBpDUm3S/p9Nr6NpD9JmiPpV5KKupqimZmZ1ZEnITgamAf8HysvU3wZ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\nM5wQmJmZGfD/AfNlonDQ9u9xAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fca864db9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "bar = ax.bar(ind, ds, width) \n",
    "\n",
    "ax.set_title('Visites des 5e', **title_font)\n",
    "\n",
    "ax.set_ylabel('Nombre de visiteurs', **axis_font)\n",
    "ax.set_yticks(np.arange(0, 61, 5))\n",
    "ax.set_xticks(ind + width/2)\n",
    "ax.set_xticklabels(villes, **axis_font)\n",
    "\n",
    "ax.yaxis.grid(True)\n",
    "\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "\n",
    "ax.yaxis.set_ticks_position('left')\n",
    "ax.xaxis.set_ticks_position('bottom')\n",
    "\n",
    "\n",
    "fig.savefig(\"./graph1.pdf\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Sortie en mer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[6, 17, 15, 26, 12]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = pm.Dataset.random(5, distrib=\"randint\", rd_args=(5, 30))\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "obs = [\"Boutielles\", \"Poisson \\n Clown\", \"Poisson \\n Soldat\", \"Corail \\n Branche\", \"Corail \\n Mou\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ind = np.arange(5)\n",
    "width = 0.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Set the font dictionaries (for plot title and axis titles)\n",
    "title_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'20', 'color':'black', 'weight':'normal',\n",
    "              'verticalalignment':'bottom'} # Bottom vertical alignment for more space\n",
    "axis_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'14', 'color':'black', 'weight':'normal'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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lT301cGNEbJHL/wh8ISIOGmSemDlzZrtCrBynOGw/t3n7uc3bz23efl2VPjUi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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fca8681f518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize = (8,4))\n",
    "ax.bar(ind, ds, width, color=\"lightgray\")\n",
    "\n",
    "ax.set_title('Observations en mer', **title_font)\n",
    "\n",
    "ax.set_ylabel('Quantité', **axis_font)\n",
    "ax.set_yticks(np.arange(0, 31, 2))\n",
    "ax.set_xticks(ind + width/2)\n",
    "ax.set_xlim(0, 4.8)\n",
    "ax.set_xticklabels(obs, **axis_font)\n",
    "\n",
    "ax.yaxis.grid(True)\n",
    "\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "\n",
    "ax.yaxis.set_ticks_position('left')\n",
    "ax.xaxis.set_ticks_position('bottom')\n",
    "\n",
    "\n",
    "#fig.savefig(\"./fig/graph_poisson.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Olympiades de math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[9, 19, 10, 9, 10, 13, 6]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = pm.Dataset.random(7, distrib=\"randint\", rd_args=(2, 30))\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[9, 19, 9, 10, 10, 13, 6]"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = pm.Dataset([9, 19, 9, 10, 10, 13, 6])\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "villes = [\"Sada\", \"Majicavo\", \"Chiconi\", \"Kaweni1\", \"Bandrélé\", \"Bouéni\", \"Pamandzi\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ind = np.arange(7)\n",
    "width = 0.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Set the font dictionaries (for plot title and axis titles)\n",
    "title_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'20', 'color':'black', 'weight':'normal',\n",
    "              'verticalalignment':'bottom'} # Bottom vertical alignment for more space\n",
    "axis_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'14', 'color':'black', 'weight':'normal'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Xawa5WNJsAEkHAKNdicrMzKxPrDfRC5Q0AswBpkm6hdRr/h3AiZKmAMuBwyc6LjMzs34y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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd89a852470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize = (8,4))\n",
    "ax.bar(ind, ds, width, color=\"lightgray\")\n",
    "\n",
    "ax.set_title('Olympiades de Mathématiques', **title_font)\n",
    "\n",
    "ax.set_ylabel('Nombre de médailles', **axis_font)\n",
    "ax.set_yticks(np.arange(0, max(ds)+2, 2))\n",
    "ax.set_xticks(ind + width/2)\n",
    "ax.set_xlim(0, 6.8)\n",
    "ax.set_xticklabels(villes, **axis_font)\n",
    "\n",
    "ax.yaxis.grid(True)\n",
    "\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "\n",
    "ax.yaxis.set_ticks_position('left')\n",
    "ax.xaxis.set_ticks_position('bottom')\n",
    "\n",
    "fig.savefig(\"./fig/graph_medailles.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "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>Nombre de cadeaux</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Villes</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Sada</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Majicavo</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chiconi</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kaweni1</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bandrélé</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bouéni</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pamandzi</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Nombre de cadeaux\n",
       "Villes                     \n",
       "Sada                      9\n",
       "Majicavo                 19\n",
       "Chiconi                   9\n",
       "Kaweni1                  10\n",
       "Bandrélé                 10\n",
       "Bouéni                   13\n",
       "Pamandzi                  6"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(data=list(ds), index=villes,columns=['Nombre de cadeaux'])\n",
    "df.index.name=\"Villes\"\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lrrrrrrr}\n",
      "\\toprule\n",
      "Villes &  Sada &  Majicavo &  Chiconi &  Kaweni1 &  Bandrélé &  Bouéni &  Pamandzi \\\\\n",
      "\\midrule\n",
      "Nombre de cadeaux &     9 &        19 &        9 &       10 &        10 &      13 &         6 \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(df.T.to_latex())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "title_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'23', 'color':'black', 'weight':'normal',\n",
    "              'verticalalignment':'bottom'} # Bottom vertical alignment for more space\n",
    "axis_font = {'fontname':'Droid Sans Mono Slashed for Powerline', 'size':'14', 'color':'black', 'weight':'normal'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dHR10dHQsthcCdnZ20tbW5rtnmJkNQJXDJLfqPs02MPV2GO2iLgR8JBf8cUnn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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd89a629940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.plot(kind='bar', color='lightgrey', figsize=(12,4), rot=0, fontsize=20)\n",
    "\n",
    "ax.set_title('Olympiades de Mathématiques', **title_font)\n",
    "\n",
    "ax.set_yticks(np.arange(0, max(ds)+2, 2))\n",
    "ax.set_xlabel('')\n",
    "#ax.set_xticks(ind + width/2)\n",
    "ax.yaxis.grid(True)\n",
    "\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.yaxis.set_ticks_position('left')\n",
    "ax.xaxis.set_ticks_position('bottom')\n",
    "\n",
    "fig = ax.get_figure()\n",
    "fig.savefig(\"./fig/graph_medailles.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}