Séance 6 - Chargement des données de l'enquête.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chargement des données de l'enquête sur la représentation de la science"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Chargement des scripts nécessaires"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "#Création d'une fonction qui met en forme un tableau\n",
    "def tri_a_plat(colonne):\n",
    "    effectif = colonne.value_counts().sort_index()\n",
    "    pourcentage = round(100*colonne.value_counts(normalize=True),1)\n",
    "    tableau = pd.DataFrame([effectif,pourcentage]).T\n",
    "    tableau.columns = [\"Effectif\",\"Pourcentage (%)\"]\n",
    "    return tableau"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Chargement de l'enquête"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Unnamed: 0', 'ident', 'poids1', 'in06', 'regsof', 'habp', 'rs1', 'rs2', 'age', 'rs3', 'rs5', 'rs6', 'pcsip', 'rs6b', 'rs7', 'rs7b', 'pcsp', 'rs9', 'rs9b', 'rs69b', 'q1_1', 'q1_2', 'q1_3', 'q1_4', 'q1_5', 'q1_6', 'q1_7', 'q1_8', 'q1_9', 'q1_10', 'q2', 'm_q29_1', 'm_q29_2', 'm_q29_3', 'm_q29_4', 'm_q29_5', 'm_q29_6', 'm_q29_7', 'm_q29_8', 'm_q29_9', 'm_q29_10', 'm_q29_11', 'm_q29_12', 'm_q29_13', 'm_q29_14', 'm_q29_15', 'm_q29_16', 'm_q29_17', 'm_q29_18', 'm_q29_19', 'm_q29_20', 'm_q29_21', 'm_q29_22', 'm_q29_23', 'm_q29_24', 'm_q29_25', 'm_q29_26', 'm_q29_27', 'm_q29_28', 'm_q29_29', 'q3_1', 'q3_2', 'q3_3', 'q3_4', 'q3_5', 'q3_6', 'q3_7', 'q3_8', 'q3_9', 'q3_10', 'q3_11', 'q4', 'q5_1', 'q5_2', 'q5_3', 'q5_4', 'q6_1', 'q6_2', 'q6_3', 'q6_4', 'q6_5', 'q6_6', 'q6_7', 'q6_8', 'q7', 'q8', 'q10', 'q11', 'q12', 'q13', 'q14_1', 'q14_2', 'q15', 'q16_1', 'q16_2', 'q16_3', 'q16_4', 'q16_5', 'q31', 'q17', 'q18', 'q19', 'q20', 'q21_1', 'q21_2', 'q21_3', 'q21_4', 'q21_5', 'q21_6', 'q21_7', 'q21_8', 'q22', 'q22bis', 'm_q2222b_1', 'm_q2222b_2', 'm_q2222b_3', 'm_q2222b_4', 'm_q2222b_5', 'm_q2222b_6', 'q23', 'q24_1', 'q24_2', 'q24_3', 'q24_4', 'q24_5', 'q24_6', 'q25', 'q25bis', 'q26', 'q9', 'q27_1', 'q27_2', 'q27_3', 'q27_4', 'q27_5', 'q27_6', 'splitQ28', 'q28', 'q28bis', 'm_q2828b_1', 'm_q2828b_2', 'm_q2828b_3', 'm_q2828b_4', 'm_q2828b_5', 'm_q2828b_6', 'm_q2828b_7', 'q54a', 'q54_1', 'q54_2', 'q54_3', 'q54_4', 'q54_5', 'q54_6', 'q54_7', 'q54_8', 'q54_9', 'q54_10', 'q54_11', 'degre', 'rs16a', 'rs10b', 'rs11', 'rs14', 'rs101', 'rs102', 'rs15', 'rs16', 'rs11a', 'rs17', 'rs18b', 'relig', 'rs20', 'formation', 'nivet6', 'nivet5', 'cns11', 'cns4', 'PPI13', 'PPI8', 'intedom', 'infonuc', 'imache', 'RecQ7', 'RecQ8', 'recQ9', 'Q7Q8Q9', 'typonuc', 'risque', 'fxdate']\n"
     ]
    }
   ],
   "source": [
    "#enquete = pd.read_csv(\"../mathSHS/Données/enquete2011.csv\")\n",
    "url = \"https://raw.githubusercontent.com/emilienschultz/mathSHS/master/Donn%C3%A9es/enquete2011.csv\"\n",
    "enquete = pd.read_csv(url)\n",
    "    \n",
    "print(list(enquete.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>ident</th>\n",
       "      <th>poids1</th>\n",
       "      <th>in06</th>\n",
       "      <th>regsof</th>\n",
       "      <th>habp</th>\n",
       "      <th>rs1</th>\n",
       "      <th>rs2</th>\n",
       "      <th>age</th>\n",
       "      <th>rs3</th>\n",
       "      <th>...</th>\n",
       "      <th>intedom</th>\n",
       "      <th>infonuc</th>\n",
       "      <th>imache</th>\n",
       "      <th>RecQ7</th>\n",
       "      <th>RecQ8</th>\n",
       "      <th>recQ9</th>\n",
       "      <th>Q7Q8Q9</th>\n",
       "      <th>typonuc</th>\n",
       "      <th>risque</th>\n",
       "      <th>fxdate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.113456</td>\n",
       "      <td>Meurthe-et-Moselle</td>\n",
       "      <td>Est</td>\n",
       "      <td>Plus de 100 000 habitants</td>\n",
       "      <td>Femme</td>\n",
       "      <td>23</td>\n",
       "      <td>18 à 24 ans</td>\n",
       "      <td>J'ai un travail</td>\n",
       "      <td>...</td>\n",
       "      <td>Cinq domaines</td>\n",
       "      <td>Plutôt mal informé</td>\n",
       "      <td>Négatif</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>Pour et hésite</td>\n",
       "      <td>Trois risques</td>\n",
       "      <td>2017-11-16T14:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.752896</td>\n",
       "      <td>Meurthe-et-Moselle</td>\n",
       "      <td>Est</td>\n",
       "      <td>Plus de 100 000 habitants</td>\n",
       "      <td>Homme</td>\n",
       "      <td>41</td>\n",
       "      <td>35 à 49 ans</td>\n",
       "      <td>J'ai un travail</td>\n",
       "      <td>...</td>\n",
       "      <td>Aucun domaine d'intérêt</td>\n",
       "      <td>Très ou plutôt bien informé</td>\n",
       "      <td>Positif</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Pour</td>\n",
       "      <td>Un risque</td>\n",
       "      <td>2017-11-16T15:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.794269</td>\n",
       "      <td>Meurthe-et-Moselle</td>\n",
       "      <td>Est</td>\n",
       "      <td>Plus de 100 000 habitants</td>\n",
       "      <td>Femme</td>\n",
       "      <td>63</td>\n",
       "      <td>50 à 64 ans</td>\n",
       "      <td>Je suis à la retraite ou pré-retraite</td>\n",
       "      <td>...</td>\n",
       "      <td>Neuf domaines</td>\n",
       "      <td>Plutôt mal informé</td>\n",
       "      <td>Ambigu</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>Pour et hésite</td>\n",
       "      <td>Deux risques</td>\n",
       "      <td>2017-11-16T15:31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.848631</td>\n",
       "      <td>Meurthe-et-Moselle</td>\n",
       "      <td>Est</td>\n",
       "      <td>Plus de 100 000 habitants</td>\n",
       "      <td>Homme</td>\n",
       "      <td>30</td>\n",
       "      <td>25 à 34 ans</td>\n",
       "      <td>J'ai un travail</td>\n",
       "      <td>...</td>\n",
       "      <td>Six domaines</td>\n",
       "      <td>Très ou plutôt bien informé</td>\n",
       "      <td>Positif</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>Hésitants</td>\n",
       "      <td>Aucun risque</td>\n",
       "      <td>2017-11-16T15:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.020218</td>\n",
       "      <td>Meurthe-et-Moselle</td>\n",
       "      <td>Est</td>\n",
       "      <td>Plus de 100 000 habitants</td>\n",
       "      <td>Homme</td>\n",
       "      <td>70</td>\n",
       "      <td>65 ans et+</td>\n",
       "      <td>Je suis à la retraite ou pré-retraite</td>\n",
       "      <td>...</td>\n",
       "      <td>Deux domaines</td>\n",
       "      <td>Plutôt mal informé</td>\n",
       "      <td>Positif</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Pour</td>\n",
       "      <td>Trois risques</td>\n",
       "      <td>2017-11-16T16:15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 189 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  ident    poids1                in06 regsof  \\\n",
       "0           0    2.0  1.113456  Meurthe-et-Moselle    Est   \n",
       "1           1    3.0  0.752896  Meurthe-et-Moselle    Est   \n",
       "2           2    4.0  0.794269  Meurthe-et-Moselle    Est   \n",
       "3           3    5.0  0.848631  Meurthe-et-Moselle    Est   \n",
       "4           4    6.0  1.020218  Meurthe-et-Moselle    Est   \n",
       "\n",
       "                        habp    rs1 rs2          age  \\\n",
       "0  Plus de 100 000 habitants  Femme  23  18 à 24 ans   \n",
       "1  Plus de 100 000 habitants  Homme  41  35 à 49 ans   \n",
       "2  Plus de 100 000 habitants  Femme  63  50 à 64 ans   \n",
       "3  Plus de 100 000 habitants  Homme  30  25 à 34 ans   \n",
       "4  Plus de 100 000 habitants  Homme  70   65 ans et+   \n",
       "\n",
       "                                     rs3  ...                  intedom  \\\n",
       "0                        J'ai un travail  ...            Cinq domaines   \n",
       "1                        J'ai un travail  ...  Aucun domaine d'intérêt   \n",
       "2  Je suis à la retraite ou pré-retraite  ...            Neuf domaines   \n",
       "3                        J'ai un travail  ...             Six domaines   \n",
       "4  Je suis à la retraite ou pré-retraite  ...            Deux domaines   \n",
       "\n",
       "                       infonuc   imache RecQ7 RecQ8 recQ9 Q7Q8Q9  \\\n",
       "0           Plutôt mal informé  Négatif   1.0   1.0   3.0  113.0   \n",
       "1  Très ou plutôt bien informé  Positif   1.0   1.0   1.0  111.0   \n",
       "2           Plutôt mal informé   Ambigu   1.0   1.0   3.0  113.0   \n",
       "3  Très ou plutôt bien informé  Positif   1.0   2.0   3.0  123.0   \n",
       "4           Plutôt mal informé  Positif   1.0   1.0   1.0  111.0   \n",
       "\n",
       "          typonuc         risque            fxdate  \n",
       "0  Pour et hésite  Trois risques  2017-11-16T14:13  \n",
       "1            Pour      Un risque  2017-11-16T15:00  \n",
       "2  Pour et hésite   Deux risques  2017-11-16T15:31  \n",
       "3       Hésitants   Aucun risque  2017-11-16T15:42  \n",
       "4            Pour  Trois risques  2017-11-16T16:15  \n",
       "\n",
       "[5 rows x 189 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enquete.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explorer les données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Effectif</th>\n",
       "      <th>Pourcentage (%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Centre</th>\n",
       "      <td>108.0</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Est</th>\n",
       "      <td>113.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nord</th>\n",
       "      <td>102.0</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ouest</th>\n",
       "      <td>168.0</td>\n",
       "      <td>16.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paris</th>\n",
       "      <td>162.0</td>\n",
       "      <td>15.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sud Est</th>\n",
       "      <td>240.0</td>\n",
       "      <td>23.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sud Ouest</th>\n",
       "      <td>134.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Effectif  Pourcentage (%)\n",
       "Centre        108.0             10.5\n",
       "Est           113.0             11.0\n",
       "Nord          102.0              9.9\n",
       "Ouest         168.0             16.4\n",
       "Paris         162.0             15.8\n",
       "Sud Est       240.0             23.4\n",
       "Sud Ouest     134.0             13.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tri_a_plat(enquete[\"regsof\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Effectif</th>\n",
       "      <th>Pourcentage (%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Plutôt mal informé</th>\n",
       "      <td>522.0</td>\n",
       "      <td>51.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Très mal informé</th>\n",
       "      <td>225.0</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Très ou plutôt bien informé</th>\n",
       "      <td>271.0</td>\n",
       "      <td>26.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Effectif  Pourcentage (%)\n",
       "Plutôt mal informé              522.0             51.3\n",
       "Très mal informé                225.0             22.1\n",
       "Très ou plutôt bien informé     271.0             26.6"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tri_a_plat(enquete[\"infonuc\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Effectif</th>\n",
       "      <th>Pourcentage (%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18 à 24 ans</th>\n",
       "      <td>102.0</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25 à 34 ans</th>\n",
       "      <td>185.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35 à 49 ans</th>\n",
       "      <td>274.0</td>\n",
       "      <td>26.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50 à 64 ans</th>\n",
       "      <td>260.0</td>\n",
       "      <td>25.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65 ans et+</th>\n",
       "      <td>206.0</td>\n",
       "      <td>20.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Effectif  Pourcentage (%)\n",
       "18 à 24 ans     102.0              9.9\n",
       "25 à 34 ans     185.0             18.0\n",
       "35 à 49 ans     274.0             26.7\n",
       "50 à 64 ans     260.0             25.3\n",
       "65 ans et+      206.0             20.1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tri_a_plat(enquete[\"age\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Recoder les données"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dans beaucoup de cas, les données que vous avez ne sont pas adaptées, et vous voulez les regrouper. Il y a plusieurs manières de faire. En voici deux :"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Données en catégories \n",
    "\n",
    "Utiliser la fonction replace de pandas en donnant un dictionnaire des éléments à remplacer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['18 à 24 ans', '35 à 49 ans', '50 à 64 ans', '25 à 34 ans',\n",
       "       '65 ans et+'], dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enquete[\"age\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "dictionnaire = {'18 à 24 ans':\"Moins de 50 ans\", '35 à 49 ans':\"Moins de 50 ans\", '50 à 64 ans':\"Plus de 50 ans\", '25 à 34 ans':\"Moins de 50 ans\",\n",
    "       '65 ans et+':\"Plus de 50 ans\"}\n",
    "enquete[\"age-reco\"] = enquete[\"age\"].replace(dictionnaire)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Données numériques\n",
    "\n",
    "Utiliser la fonction pd.cut qui permet de définir un intervalle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       Q2\n",
       "1       Q1\n",
       "2       Q2\n",
       "3       Q2\n",
       "4       Q1\n",
       "        ..\n",
       "1022    Q2\n",
       "1023    Q2\n",
       "1024    Q1\n",
       "1025    Q2\n",
       "1026    Q2\n",
       "Name: recQ9, Length: 1027, dtype: category\n",
       "Categories (2, object): [Q1 < Q2]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.cut(enquete[\"recQ9\"], [0,2,5],labels=[\"Q1\",\"Q2\"])"
   ]
  }
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