{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Projet Maman\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "donnees = pd.read_csv('donnees.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D01FUN\n",
    "\n",
    "homme=len(donnees.loc[donnees.loc[:,'Indiquez votre genre :']=='Masculin','Indiquez votre genre :'])\n",
    "femme=len(donnees.loc[donnees.loc[:,'Indiquez votre genre :']=='Féminin','Indiquez votre genre :'])\n",
    "autre=len(donnees.loc[donnees.loc[:,'Indiquez votre genre :']=='Autre / Non renseigné','Indiquez votre genre :'])\n",
    "\n",
    "plt.figure(figsize = (8, 8))\n",
    "plt.pie([homme,femme,autre], colors = ['lightblue', 'lightgreen', 'salmon', 'blanchedalmond'], labels = ['Hommes','Femmes','Autres'],autopct='%1.1f%%',)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D02FUN\n",
    "\n",
    "donnees_pays=donnees.loc[:,'Quel est votre pays de résidence ?']\n",
    "liste_pays=list(set(donnees_pays))\n",
    "dico_pays={}\n",
    "for pays in liste_pays:\n",
    "    dico_pays[pays]=len(donnees.loc[donnees.loc[:,'Quel est votre pays de résidence ?']==pays,'Quel est votre pays de résidence ?'])\n",
    "dico_pays_bis={}\n",
    "valeur_totale=0\n",
    "for key,value in dico_pays.items():\n",
    "    if value/(sum(dico_pays.values()))*100>1:\n",
    "        dico_pays_bis[key]=value\n",
    "    else:\n",
    "        valeur_totale=valeur_totale+value\n",
    "dico_pays_bis['Autres']=valeur_totale\n",
    "\n",
    "\n",
    "plt.figure(figsize = (8, 8))\n",
    "plt.pie(dico_pays_bis.values(), autopct='%1.1f%%', colors = ['lightblue', 'lightgreen', 'salmon', 'blanchedalmond'], labels = dico_pays_bis.keys())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D04FUN\n",
    "\n",
    "donnees_age=donnees.loc[:,'Quelle est votre année de naissance ?'].count()\n",
    "a=donnees.loc[donnees.loc[:,'Quelle est votre année de naissance ?'] >= 2002,'Quelle est votre année de naissance ?'].count()\n",
    "b=donnees.loc[donnees.loc[:,'Quelle est votre année de naissance ?'] >= 2020-24,'Quelle est votre année de naissance ?'].count()\n",
    "c=donnees.loc[donnees.loc[:,'Quelle est votre année de naissance ?'] >= 2020-35,'Quelle est votre année de naissance ?'].count()\n",
    "d=donnees.loc[donnees.loc[:,'Quelle est votre année de naissance ?'] >= 2020-45,'Quelle est votre année de naissance ?'].count()\n",
    "e=donnees.loc[donnees.loc[:,'Quelle est votre année de naissance ?'] >= 2020-55,'Quelle est votre année de naissance ?'].count()\n",
    "f=donnees.loc[donnees.loc[:,'Quelle est votre année de naissance ?'] >= 2020-65,'Quelle est votre année de naissance ?'].count()\n",
    "g=donnees.loc[donnees.loc[:,'Quelle est votre année de naissance ?'] < 2020-65,'Quelle est votre année de naissance ?'].count()\n",
    "dico_age={'moins de 18ans':a,'19/24ans':b-a ,'25/35ans':c-b,'36/45ans':d-c,'46/55ans':e-d,'56/65ans':f-e,'plus de 65ans':g}\n",
    "\n",
    "plt.figure(figsize = (10, 5))\n",
    "pd.Series(dico_age).plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D05FUN\n",
    "\n",
    "donnees_formation=donnees.loc[:,'Quel est votre niveau de formation ?']\n",
    "liste_formation=list(set(donnees_formation))\n",
    "dico_formation={}\n",
    "for formation in liste_formation:\n",
    "    dico_formation[formation]=len(donnees.loc[donnees.loc[:,'Quel est votre niveau de formation ?']==formation,'Quel est votre niveau de formation ?'])\n",
    "\n",
    "plt.figure(figsize = (10, 5))\n",
    "pd.Series(dico_formation).sort_values(ascending=False).plot.bar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D06FUN\n",
    "\n",
    "donnees_langue=donnees.loc[:,'Quelle est votre langue maternelle ? ']\n",
    "donnees_langue=donnees_langue.str.lower()\n",
    "liste_langue=list(set(donnees_langue))\n",
    "dico_langue={}\n",
    "for langue in liste_langue:\n",
    "    dico_langue[langue]=len(donnees.loc[donnees.loc[:,'Quelle est votre langue maternelle ? '].str.lower()==langue,'Quelle est votre langue maternelle ? '])\n",
    "\n",
    "\n",
    "del dico_langue['autre']\n",
    "donnees_langue_autre=donnees.loc[:,'Quelle est votre langue maternelle ?  [Autre]']\n",
    "donnees_langue_autre=donnees_langue_autre.str.lower()\n",
    "\n",
    "\n",
    "\n",
    "liste_langue_autre=list(set(donnees_langue_autre))\n",
    "del liste_langue_autre[liste_langue_autre.index(np.nan)]\n",
    "dico_langue_autre={'arabe':0}\n",
    "for langue in liste_langue_autre:\n",
    "    if langue=='arabic':\n",
    "        dico_langue_autre['arabe']+=len(donnees.loc[donnees.loc[:,'Quelle est votre langue maternelle ?  [Autre]'].str.lower()==langue,'Quelle est votre langue maternelle ?  [Autre]'])\n",
    "    else:\n",
    "        dico_langue_autre[langue]=len(donnees.loc[donnees.loc[:,'Quelle est votre langue maternelle ?  [Autre]'].str.lower()==langue,'Quelle est votre langue maternelle ?  [Autre]'])\n",
    "\n",
    "\n",
    "d_touteslangues={**dico_langue, **dico_langue_autre}\n",
    "plt.figure(figsize = (20, 10))\n",
    "pd.Series(d_touteslangues).sort_values(ascending=False).plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D07FUNC01\n",
    "\n",
    "donnees_raison=donnees.loc[:,'Pourquoi suivez-vous ce MOOC ?']\n",
    "liste_raison=list(set(donnees_raison))\n",
    "del liste_raison[liste_raison.index(np.nan)]\n",
    "dico_raison={}\n",
    "for raison in liste_raison:\n",
    "    dico_raison[raison]=len(donnees.loc[donnees.loc[:,'Pourquoi suivez-vous ce MOOC ?']==raison,'Pourquoi suivez-vous ce MOOC ?'])\n",
    "\n",
    "plt.figure(figsize = (10, 5))\n",
    "pd.Series(dico_raison).sort_values(ascending=False).plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D07FUNC02\n",
    "\n",
    "donnees_ects=donnees.loc[:,'Ce MOOC vous apporte-t-il des points ECTS par rapport à un cursus ?']\n",
    "liste_ects=list(set(donnees_ects))\n",
    "dico_ects={}\n",
    "del liste_ects[liste_ects.index(np.nan)]\n",
    "for ects in liste_ects:\n",
    "    dico_ects[ects]=len(donnees.loc[donnees.loc[:,'Ce MOOC vous apporte-t-il des points ECTS par rapport à un cursus ?']==ects,'Ce MOOC vous apporte-t-il des points ECTS par rapport à un cursus ?'])\n",
    "\n",
    "plt.figure(figsize = (8, 8))\n",
    "plt.pie(dico_ects.values(),labels=dico_ects.keys(),colors=['lightblue','salmon'],autopct='%1.1f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D008FUN\n",
    "\n",
    "donnees_connaissance=donnees.loc[:,'Comment avez-vous eu connaissance de ce MOOC ?']\n",
    "liste_connaissance=list(set(donnees_connaissance))\n",
    "dico_connaissance={}\n",
    "for connaissance in liste_connaissance:\n",
    "    dico_connaissance[connaissance]=len(donnees.loc[donnees.loc[:,'Comment avez-vous eu connaissance de ce MOOC ?']==connaissance,'Comment avez-vous eu connaissance de ce MOOC ?'])\n",
    "d_connaissance=dict(sorted(dico_connaissance.items(),key=lambda t : t[1], reverse=True))\n",
    "\n",
    "plt.figure(figsize=(10,5))\n",
    "pd.Series(d_connaissance).plot(kind='bar', rot = 25)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'the label [Est-ce le premier MOOC que vous suivez ? ] is not in the [columns]'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_type\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1505\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontains\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1506\u001b[0;31m                     \u001b[0merror\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1507\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36merror\u001b[0;34m()\u001b[0m\n\u001b[1;32m   1500\u001b[0m                                .format(key=key,\n\u001b[0;32m-> 1501\u001b[0;31m                                        axis=self.obj._get_axis_name(axis)))\n\u001b[0m\u001b[1;32m   1502\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'the label [Est-ce le premier MOOC que vous suivez ? ] is not in the [columns]'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-47-d81232d7f840>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m## D009FUN\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0moui\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'Oui'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0mnon\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'Non'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1365\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1366\u001b[0m                 \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1367\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1368\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1369\u001b[0m             \u001b[0;31m# we by definition only have the 0th axis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m    856\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    857\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 858\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_lowerdim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    859\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mIndexingError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    860\u001b[0m             \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m    989\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    990\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_label_like\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 991\u001b[0;31m                 \u001b[0msection\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    992\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    993\u001b[0m                 \u001b[0;31m# we have yielded a scalar ?\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1624\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1625\u001b[0m         \u001b[0;31m# fall thru to straight lookup\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1626\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_valid_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1627\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1628\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_type\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1512\u001b[0m                 \u001b[0;32mraise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1513\u001b[0m             \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1514\u001b[0;31m                 \u001b[0merror\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1515\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1516\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36merror\u001b[0;34m()\u001b[0m\n\u001b[1;32m   1499\u001b[0m                 raise KeyError(u\"the label [{key}] is not in the [{axis}]\"\n\u001b[1;32m   1500\u001b[0m                                .format(key=key,\n\u001b[0;32m-> 1501\u001b[0;31m                                        axis=self.obj._get_axis_name(axis)))\n\u001b[0m\u001b[1;32m   1502\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1503\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'the label [Est-ce le premier MOOC que vous suivez ? ] is not in the [columns]'"
     ]
    }
   ],
   "source": [
    "## D009FUN\n",
    "\n",
    "oui=donnees.loc[donnees.loc[:,'Est-ce le premier MOOC que vous suivez ? ']=='Oui','Est-ce le premier MOOC que vous suivez ? '].count()\n",
    "non=donnees.loc[donnees.loc[:,'Est-ce le premier MOOC que vous suivez ? ']=='Non','Est-ce le premier MOOC que vous suivez ? '].count()\n",
    "\n",
    "plt.pie([oui,non],labels=['Oui','Non'],colors=['lightblue','salmon'],autopct='%1.1f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D010FUN\n",
    "\n",
    "apprendre=donnees.loc[donnees.loc[:,\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Parce que j'éprouve du plaisir et de la satisfaction à apprendre de nouvelles choses]\"]=='Oui',\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Parce que j'éprouve du plaisir et de la satisfaction à apprendre de nouvelles choses]\"].count()\n",
    "sujet_interessant=donnees.loc[donnees.loc[:,\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Parce que ce sujet m'intéresse particulièrement]\"]=='Oui',\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Parce que ce sujet m'intéresse particulièrement]\"].count()\n",
    "poursuite_carriere=donnees.loc[donnees.loc[:,\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Parce que selon moi il va m'aider dans la poursuite de ma carrière]\"]=='Oui',\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Parce que selon moi il va m'aider dans la poursuite de ma carrière]\"].count()\n",
    "insertion_professionelle=donnees.loc[donnees.loc[:,\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [ Pour m'aider dans mon insertion professionnelle ]\"]=='Oui',\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [ Pour m'aider dans mon insertion professionnelle ]\"].count()\n",
    "trouver_emploi=donnees.loc[donnees.loc[:,\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [ Pour m’aider à retrouver un emploi]\"]=='Oui',\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [ Pour m’aider à retrouver un emploi]\"].count()\n",
    "defi=donnees.loc[donnees.loc[:,\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Pour relever un défi]\"]=='Oui',\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Pour relever un défi]\"].count()\n",
    "aucune_raison=donnees.loc[donnees.loc[:,\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Je n’ai pas de raison particulière]\"]=='Oui',\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Je n’ai pas de raison particulière]\"].count()\n",
    "\n",
    "liste_raison_autres=list(donnees.loc[donnees.loc[:,\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Autre]\"]!=np.nan,\"Pour quelles raisons ce MOOC vous intéresse-t-il ? [Autre]\"].dropna())\n",
    "dico_raison_autres={\"coronavirus\":0,\"curiosité\":0,\"école doctorale\":0,\"recherche\":0}\n",
    "for raison_autres in liste_raison_autres:\n",
    "    if \"coro\" in raison_autres.lower() or \"covi\" in raison_autres.lower() or \"confi\" in raison_autres.lower():\n",
    "        dico_raison_autres[\"coronavirus\"]+=1\n",
    "    if 'docto' in raison_autres.lower():\n",
    "        dico_raison_autres[\"école doctorale\"]+=1\n",
    "    if 'rch' in raison_autres.lower() or 'thèse' in raison_autres.lower():\n",
    "        dico_raison_autres[\"recherche\"]+=1\n",
    "    if 'curiosit' in raison_autres.lower() or 'générale' in raison_autres.lower() or \"découverte\" in raison_autres.lower() or \"approche\" in raison_autres.lower():\n",
    "        dico_raison_autres[\"curiosité\"]+=1\n",
    "\n",
    "\n",
    "raisons=[\"apprendre\",\"sujet intéressant\",\"poursuite de carrière\",\"insertion professionelle\",\"trouver un emploi\",\"défi\",\"aucune raison\"]+list(dico_raison_autres.keys())\n",
    "nbr_raisons=[apprendre,sujet_interessant,poursuite_carriere,insertion_professionelle,trouver_emploi,defi,aucune_raison]+list(dico_raison_autres.values())\n",
    "plt.figure(figsize=(10,5))\n",
    "pd.Series(nbr_raisons,index=raisons).sort_values(ascending=False).plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D011FUN\n",
    "\n",
    "donnees_niveau=donnees.loc[:,'Quel est votre niveau de connaissance sur le sujet ?']\n",
    "liste_niveau=list(set(donnees_niveau))\n",
    "dico_niveau={}\n",
    "for niveau in liste_niveau:\n",
    "    dico_niveau[niveau]=donnees.loc[donnees.loc[:,'Quel est votre niveau de connaissance sur le sujet ?']==niveau,'Quel est votre niveau de connaissance sur le sujet ?'].count()\n",
    "\n",
    "plt.figure(figsize=(8,8))\n",
    "plt.pie(dico_niveau.values(),labels=dico_niveau.keys(),colors=['lightblue','salmon','lightgreen'],autopct='%1.1f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlMAAAFICAYAAAB0uHstAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAHDlJREFUeJzt3Xu4XVV97vHvC8GC4IXIBiOKQaUIrUesAVFbtQUUxRLUUlGrqYc2R217BKsWrfXWaqnVU+2p7SkVJX3wArUoHLy0McLRekGDoIjgQUERTUnEC14qCPz6x5hbdmNwr2Tsy9p7fz/PwzPXnGuurN9+GM9a7xpjjjFTVUiSJGnH7DTfBUiSJC1khilJkqQOhilJkqQOhilJkqQOhilJkqQOhilJkqQOhilJkqQOhilJkqQOhilJkqQOy+byzfbaa69auXLlXL6lJEnSDrn44ou/WVUT0503p2Fq5cqVbNy4cS7fUpIkaYck+eoo5znMJ0mS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1GFO780nLUivvNt8VzCeXvnd+a5AksaCPVOSJEkdDFOSJEkdDFOSJEkdDFOSJEkdDFOSJEkdDFOSJEkdDFOSJEkdDFOSJEkdDFOSJEkdDFOSJEkdDFOSJEkdRgpTSU5OcnmSzyd5Z5JdkyxPsj7JVcN2z9kuVpIkadxMG6aS7Av8T2BVVf0isDNwAnAKsKGqDgA2DPuSJElLyqjDfMuA3ZIsA+4MfANYDawbnl8HHDfz5UmSJI23acNUVX0deD1wLbAJ+G5V/SuwT1VtGs7ZBOy9rdcnWZtkY5KNW7ZsmbnKJUmSxsAow3x70nqh9gfuBeye5LdGfYOqOq2qVlXVqomJiR2vVJIkaQyNMsx3JHBNVW2pqh8D5wCPAK5PsgJg2G6evTIlSZLG0yhh6lrg8CR3ThLgCOAK4DxgzXDOGuDc2SlRkiRpfC2b7oSquijJu4HPALcAlwCnAXsAZyc5kRa4jp/NQiVJksbRtGEKoKpeAbxiq8M30XqpJEmSlixXQJckSepgmJIkSepgmJIkSepgmJIkSepgmJIkSepgmJIkSepgmJIkSepgmJIkSepgmJIkSepgmJIkSepgmJIkSepgmJIkSeow0o2OF6OVp7xvvksYS1859Zj5LkGSpAXFnilJkqQOhilJkqQOhilJkqQOhilJkqQOhilJkqQOhilJkqQOhilJkqQOhilJkqQO04apJAcmuXTKfzcmOSnJ8iTrk1w1bPeci4IlSZLGybRhqqq+WFWHVNUhwEOBHwLvAU4BNlTVAcCGYV+SJGlJ2d5hviOAL1fVV4HVwLrh+DrguJksTJIkaSHY3jB1AvDO4fE+VbUJYNjuPZOFSZIkLQQjh6kkdwKOBf5pe94gydokG5Ns3LJly/bWJ0mSNNa2p2fq8cBnqur6Yf/6JCsAhu3mbb2oqk6rqlVVtWpiYqKvWkmSpDGzPWHqadw+xAdwHrBmeLwGOHemipIkSVooRgpTSe4MHAWcM+XwqcBRSa4anjt15suTJEkab8tGOamqfgjcY6tjN9Bm90mSJC1ZroAuSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUwTAlSZLUYaQwleTuSd6d5MokVyR5eJLlSdYnuWrY7jnbxUqSJI2bUXum3gR8sKoeCDwYuAI4BdhQVQcAG4Z9SZKkJWXaMJXkrsCjgNMBqurmqvoOsBpYN5y2DjhutoqUJEkaV6P0TN0P2AK8LcklSd6SZHdgn6raBDBs997Wi5OsTbIxycYtW7bMWOGSJEnjYJQwtQz4JeDvquohwA/YjiG9qjqtqlZV1aqJiYkdLFOSJGk8jRKmrgOuq6qLhv1308LV9UlWAAzbzbNToiRJ0viaNkxV1b8DX0ty4HDoCOALwHnAmuHYGuDcWalQkiRpjC0b8bw/AN6e5E7A1cCzaUHs7CQnAtcCx89OiZIkSeNrpDBVVZcCq7bx1BEzW44kSdLC4grokiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHQxTkiRJHZaNclKSrwDfA24FbqmqVUmWA2cBK4GvAL9ZVd+enTIlSZLG0/b0TP1qVR1SVauG/VOADVV1ALBh2JckSVpSeob5VgPrhsfrgOP6y5EkSVpYRg1TBfxrkouTrB2O7VNVmwCG7d6zUaAkSdI4G+maKeCRVfWNJHsD65NcOeobDOFrLcB+++23AyVKkiSNr5F6pqrqG8N2M/Ae4DDg+iQrAIbt5jt47WlVtaqqVk1MTMxM1ZIkSWNi2jCVZPckd5l8DDwW+DxwHrBmOG0NcO5sFSlJkjSuRhnm2wd4T5LJ899RVR9M8mng7CQnAtcCx89emZIkSeNp2jBVVVcDD97G8RuAI2ajKEmSpIXCFdAlSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6jBymkuyc5JIk5w/7y5OsT3LVsN1z9sqUJEkaT9vTM/V84Iop+6cAG6rqAGDDsC9JkrSkjBSmktwbOAZ4y5TDq4F1w+N1wHEzW5okSdL4G7Vn6o3Ai4Hbphzbp6o2AQzbvbf1wiRrk2xMsnHLli1dxUqSJI2bacNUkicCm6vq4h15g6o6rapWVdWqiYmJHfknJEmSxtayEc55JHBskicAuwJ3TXImcH2SFVW1KckKYPNsFipJkjSOpu2ZqqqXVNW9q2olcALw4ar6LeA8YM1w2hrg3FmrUpIkaUz1rDN1KnBUkquAo4Z9SZKkJWWUYb6fqKoLgQuHxzcAR8x8SZIkSQuHK6BLkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1MExJkiR1mDZMJdk1yaeSfDbJ5UleNRxfnmR9kquG7Z6zX64kSdJ4GaVn6ibg16rqwcAhwNFJDgdOATZU1QHAhmFfkiRpSZk2TFXz/WF3l+G/AlYD64bj64DjZqVCSZKkMTbSNVNJdk5yKbAZWF9VFwH7VNUmgGG79x28dm2SjUk2btmyZabqliRJGgsjhamqurWqDgHuDRyW5BdHfYOqOq2qVlXVqomJiR2tU5IkaSxt12y+qvoOcCFwNHB9khUAw3bzjFcnSZI05kaZzTeR5O7D492AI4ErgfOANcNpa4BzZ6tISZKkcbVshHNWAOuS7EwLX2dX1flJPgGcneRE4Frg+FmsU5IkaSxNG6aq6nPAQ7Zx/AbgiNkoSpIkaaFwBXRJkqQOowzzSZKkGXbFAw+a7xLG0kFXXjHfJWw3e6YkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6GKYkSZI6TBumktwnyQVJrkhyeZLnD8eXJ1mf5Kphu+fslytJkjReRumZugX4w6o6CDgc+L0kBwOnABuq6gBgw7AvSZK0pEwbpqpqU1V9Znj8PeAKYF9gNbBuOG0dcNxsFSlJkjSutuuaqSQrgYcAFwH7VNUmaIEL2PsOXrM2ycYkG7ds2dJXrSRJ0pgZOUwl2QP4Z+Ckqrpx1NdV1WlVtaqqVk1MTOxIjZIkSWNrpDCVZBdakHp7VZ0zHL4+yYrh+RXA5tkpUZIkaXyNMpsvwOnAFVX1v6Y8dR6wZni8Bjh35suTJEkab8tGOOeRwDOBy5JcOhx7KXAqcHaSE4FrgeNnp0RJkqTxNW2Yqqp/A3IHTx8xs+VIkiQtLK6ALkmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1MEwJUmS1GHaMJXkrUk2J/n8lGPLk6xPctWw3XN2y5QkSRpPo/RMnQEcvdWxU4ANVXUAsGHYlyRJWnKmDVNV9RHgW1sdXg2sGx6vA46b4bokSZIWhGU7+Lp9qmoTQFVtSrL3HZ2YZC2wFmC//fbbwbeTpIXhQeseNN8ljKXL1lw23yVIs2bWL0CvqtOqalVVrZqYmJjtt5MkSZpTOxqmrk+yAmDYbp65kiRJkhaOHQ1T5wFrhsdrgHNnphxJkqSFZZSlEd4JfAI4MMl1SU4ETgWOSnIVcNSwL0mStORMewF6VT3tDp46YoZrkSRJWnBcAV2SJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKmDYUqSJKlDV5hKcnSSLyb5UpJTZqooSZKkhWKHw1SSnYE3A48HDgaeluTgmSpMkiRpIejpmToM+FJVXV1VNwPvAlbPTFmSJEkLQ0+Y2hf42pT964ZjkiRJS8ayjtdmG8fqp05K1gJrh93vJ/lix3suVnsB35zvIgDyF/NdgaYxNm2FV23rI0BjZmzaS37b9jLmxqatkLFqK/cd5aSeMHUdcJ8p+/cGvrH1SVV1GnBax/ssekk2VtWq+a5D48+2ou1he9GobCt9eob5Pg0ckGT/JHcCTgDOm5myJEmSFoYd7pmqqluS/D7wL8DOwFur6vIZq0ySJGkB6Bnmo6reD7x/hmpZyhwG1ahsK9oetheNyrbSIVU/dc24JEmSRuTtZCRJkjoYpiRJkjoYphagZLwW4dD4sq1optiWNKql2FYMUwtIkr2TLCsvdNM0bCuaKUn2BrAtaTpJ7gVLs60YphaIYSX5PwZ2T7IsyW8n+YX5rkvjJ8nvYltRpyQ7JTke+Idhf7ckT0kyMc+lacwMbeVk4HnD/vKhrew/+fy8FjgHFv0fuJAlOS7JocPuvwHLgWcCFwJPBk5P8rjh3CXXrarbJXlBkpcMu58E7o5tRTtgSu/CbcCVwI+SvAb4AHAy8LdJDpjHEjUGkuye5E+SHDe0lWuA3ZK8CtgAPB34wNBDftu8FjsHDFNjJsnOSV6Y5AvAs4A3JHlmVX2B9sF2DPBXVXUs8A7gT+exXM2j4dfgSUk+AzwM+BBAVV1G+2B7ArYVjSDNc5PcDLw0yT7DU18FPgo8CXhaVf0ycCPw+CR3m6dyNY+GHspXAhcB9wM+Ozx1AXAT8MvAb1TVU2ifQyfNR51zzTA1fnahNdBnVdWTgdOBw5LsRrtdz60Mi61W1V8DK5McVlVlj8PSMvzaOx44s6qeWlWfTrLL8PR7gduwrehnSLLHMGy3C+374NW0m9g/EKCqbgQ+AvwcMNkb9T7gQOCgOS9Y4+C+wBHAa6vq2VV1TZJU1XeBjwM/Bu4/nPsXwPFJ9pynWueMYWrMVNWPgFdX1cbh0IeBxw3PXQZ8Edg3yT2H5/8O+JvhsV+QS0SSnYeH64D7J3loktcCz02yX1VdClwO3Me2oq0NIWoX4EXAM6rqZuAdVfVntC/DQ5PcYzj9K8DbaMPF0G4hdivwiCS7z23lmm9VdSWtt/KuSY5M8mrgqUNg+n/AZbT79u5cVRcC3wXWzFvBc8QwNceS3CXJvkmWD/s/9aVWVf8+Zfd+wKeAOw37/xc4mNt/Jf4psDnJbkthXHop+VltpapuHR6uAw6l9WDeRGsbf57kYbShvV/AtqLBMDT8GOBdVfVj4BLg3kn2r6pvD6e9jymfMUPv1IdoPZsHV9UPaEM7t2AoX7SGod+dtjo2uf9+2mUorwdupl1+8re0Hs6P0b63Hjqc+w/AXou9N9wwNff2Ap4CnAJ3PIV0ynDNI4FNQxcqQ9LfBXhYkrtU1S1V9cSq+o9Zr1xz7We2leGX303AHwBHV9WrgD+i/TJ8TFV9lnYT8sNsKxray2203u3vJTma1pNwMfDDyfOqaj3tC/LQKV+A/x/YBPz3Yf+Mqvrrqvr+nP0BmjNJdqrmtsk2MAzl3QZQVf8GvAI4dOjNfCHwLVqo+hhwN2DVcO4/VdXLFvtyCd6bb54keThwInAF8KGq+uzwYXfrVue9A3gZrav0eFpvw72AG6pqyxyXrXkwaluZcv7fA5+oqjOSPAT4WlV9cw5L1phK8nO0WVaHArtV1bO3en6n4Qv0CNoEhguAB1TVG5McCNxYVZvmvHDNmiEkVZJDh+suJ/fvSZu9uQfwZuBLVXXzZBvZxr9zJvDmqvpEksOBz1XVD7c+b7GyZ2oeJDkS+HvaTIdrgXOG6aNbB6mDgQcBb6JdBLocuKmqrjRILQ2jtpXh3Eck+VvgvwGfB6iqSwxSAkiyH/AZ4MHDoYOH0PSTnvApX5LfBZ5NG6I5MMkuVfVFg9TiMwSnXwLWJ9lj2L8/7dKBLwOfBl4DPHY4/ydBKskuSR6d5O3ABPC14ZxPLqUgBYapWTPlAuFtuZR2Ufl5wBOB/YDnTHntZNf63Whjz+cDv1RVrx2GdbSI9LSVKf/G/rSLy6+hDfFt3PocLX7TtKWjgQur6iTglcBZwDMAhuunJv+N5cALgP8D7F9Vz536vBafqvoMbbj36cOhn6ddLnAB8FRgV9pEhK0dC/wl8JGqelxVXTf71Y4nh/lmUJK7AL8GrJ9M5ZNdpts495G0RvgntIb6V8BDhos7tYgNYXkPZqit3NHrtHQlWUG7FOAnwzJJjgX+sKoenWQZbT2gPwZeXFWX/KyhYy0+U4bzjqYN6R5A+/F+EK0X6i20tQ3fUFUfGF5z96r6zpQ2tc0hv6XInqmZtYI2Y+p+SY5IcgHw4mG4bnJBzslep/sCl1fVBtoFoQ+gXROlRWz4MCrg3sxQWzFILV1bz5BK8tgkH6YF7gn4L8MynwO2JFldVbcMx+7B0NNpkFpahiA1QbuQ/OO03si70Xorv0Gb1fnmqvrAMJz3IlqP1U/alEHqdvZMdUjyaFo354smG1WSNwF3pk0bvoj2pfmYqjpyq9c+jZb+/wO4C22mzNuq6oq5+ws0l5L8A+3D6ElV9a0kf0NbDNG2opENASpbf5EluQ9tgsqfV9X77+C1a2hrS51F65l6J3DJMPNTi8zQVnb6GZNVHkebMfw/hnD1FOAlwMOBxwOvA9YDv0L7IXdyVX1jTopfYOyZ2kFJnke7puA3gOdOeep04CHANVV1Bq0x3iPJY4fXTV2h+m20/wdvqKoX++W4OE1Zm2VyrbAThu1bsa1oRBlu8TI5ZX049rwkT0xbPHMF7TqXQ5L8epJnTvZ0TqqqdcDv0FbGf3lVnWGQWryGtnJr2iKtz0pyP/gvn0nfp60pttMQvM6h/eA7tqrOA1bTeq1+o9pdFgxSd8CeqR00fEjdRutKf31VPWzKc6fT1mV5Y1XdlOT5tHWAHu/1LUtTkvsCb6CFoufQ7nP2/SRn0JY8sK1om4brm54E7FFVbxtC9qNpy2XsQVsj6saq+t0kJwKPoPUiHAV8HfiTqvqa7WnpGSYknET7wX8+8Kaqumarc9YDH6TdIeFewNm0ZRB+c47LXdAMU53S1m05H1hXVWcOx36N1pX+e1V1dZI9aFNGj6yqi+evWs2XoQ28njbj7iTgA1X1z0keQZtZ9RzbiqaaenFv2r05f0xbHuW+tHb08ao6eZj4ch1w0NSegySPp83gO9lrWxa3yckDUy4q3xvYHdhC69levfWElSR3GiYoHE67VdCjaIu1vga4oNothjQih/k6DUsVnAH87pRjH6bdWf2YocF+nzat/bNbXzCqJeNI4OtV9XnaDJnXJfnHqvo48G3gCbYVwe1DMFsFoJ1pq9u/vKo+DXwC+EGSe1TV94BzaaGctPulvRd4FXCZQWrxSbst0PIkx8DtkweGkLQL7YbVJ9DCEcD5Sd4wjJq8YTh2y/CaT1bVi2mh+1FV9S8Gqe1nmJoZ76eNOR865dhZtAU3lwFU1ceq3c7DrsClaQvwoCTnAL8P/Ih2E2tos2Z+EdvKkpXknkkeCLeHqCQPS/LGJL9Cm3zwEWDX4bz30y4xWDn8Ey8DfifJnYdz311Vh1XVW+b4T9EsS3LXoY08gHavVpLcOclfJllVbU2wC2lDdvcFfpvWK/5e2r08n5nk/luH7Kr6xNz9FYuPYWoGVLtB6Jm01ak/kuTXq+qcqlpbS2wVWN2hH9Kub/kYbYXy19Eu7qSq/rGqnmNbWZqS/DxtKvprpxx7Ie3OB9cDf0hbZ+wi2jVQT6bdeDi0gH6XqrqWdsuPlUMYP3Nu/wrNtiQPT/JPwFlJnlRVnwI+lOT5w2fHzwGT1zl9ECjgV2nrjb2PdnPqFbSgdeOc/wGL3LL5LmAxSHIC8GJuX+Dsg/NcksbPpVX1hMmdJB8FNg6PvTB4iUmyom6/NctmWi/lRJInDMsa7Ae8qtoaP/vRbkj8OloY/01g3+HYUcP2e1X1B3P9d2huJDkbOBxYSwtExye5FXg58G5a8D4LeGmSB1TVl5J8hXbN3EeHHst30j5zXlvejmzG2TM1M75Dmzp6lEFK2zIZloaZWVTV1VV1+dTntDQkeQ/wubSV7aGtL/Zl4D3c3rNwMPCttPswXgtcQhuu+Qhw03DeWcArtp6dpUVpI3Dt8P3yDuBy4LCq+iRwY5KnV9XHaLM4J6/fvZLWjg4bHv9qVT29qi6Z+/IXP8PUDKiqD9pANYq6feVpLV3/Qlt5/KlJfnmYlHAIbYmMOw3XRF1Au9Hw5NpknwS+XVU/oq1lt264ru6rc1++5lpVvQ54YJKfHyY97Uvr0YQ2PPyy4fEZwOohsJ88PHd2Vf2gqr4+x2UvKS6NIElzLMl1wN/Tpq9/lDas9x3aEM6+tPswrgO+CewGrAKOLxdrXbKSnAocQ7v2aV/gBZM/4pNcPey/N8nDaRMTzhmCl+aAYUqS5liSPwN+gbYe3dm05TGeT1sC4c+AP6qqLyR5Bu1+aaf7xbi0DWsa3gC8pKr+93Bscn2pU4DDq+q4eS1yCTNMSdIcGxbhvB7Ynza782XAS4FLaUMz36qq18xfhRpHaff3/HFVPS/JrsBNXnM5HgxTkjQPkryF9hl8YpJ9aVPYf5RkeVV9a77r0/gZ7s+4CZioqhvmux7dzjAlSfNgyhfjXoYnjSrJC4B3AZvslRofhilJmid+MUqLg2FKkiSpg+tMSZIkdTBMSZIkdTBMSZIkdTBMSZIkdTBMSZIkdTBMSZIkdTBMSZIkdfhPLzkA8L90rz8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D012FUN\n",
    "\n",
    "donnees_heures=donnees.loc[:,\"Combien d'heures par semaine pensez-vous passer sur le MOOC ?\"]\n",
    "liste_heures=[\"Moins d'1h\",'1h à 2h', '4h à 5h', 'Plus de 5h']\n",
    "dico_heures={}\n",
    "for heures in liste_heures:\n",
    "    dico_heures[heures]=len(donnees.loc[donnees.loc[:,\"Combien d'heures par semaine pensez-vous passer sur le MOOC ?\"]==heures,\"Combien d'heures par semaine pensez-vous passer sur le MOOC ?\"])\n",
    "\n",
    "plt.figure(figsize=(8,8))\n",
    "plt.pie(dico_heures.values(),labels=dico_heures.keys(),colors=['lightblue','salmon','lightgreen','violet','blanchedalmond'],autopct='%1.1f%%')\n",
    "plt.show()\n",
    "plt.figure(figsize=(10,5))\n",
    "pd.Series(dico_heures).plot(kind='bar', rot = 25)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D016FUN\n",
    "\n",
    "donnees_attestation=donnees.loc[:,\"Avez-vous l'intention d'obtenir une attestation de suivi avec succès gratuite pour ce MOOC ?\"]\n",
    "liste_attestation=list(set(donnees_attestation))\n",
    "dico_attestation={}\n",
    "for attestation in liste_attestation:\n",
    "    dico_attestation[attestation]=len(donnees.loc[donnees.loc[:,\"Avez-vous l'intention d'obtenir une attestation de suivi avec succès gratuite pour ce MOOC ?\"]==attestation,\"Avez-vous l'intention d'obtenir une attestation de suivi avec succès gratuite pour ce MOOC ?\"])\n",
    "\n",
    "plt.figure(figsize=(8,8))\n",
    "plt.pie(dico_attestation.values(),colors=['lightblue','salmon','lightgreen','violet','blanchedalmond'],autopct='%1.1f%%')\n",
    "plt.legend(dico_attestation.keys(),loc=\"upper center\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## DILLCurrentStatus\n",
    "\n",
    "donnees_situation=donnees.loc[:,'Merci de nous préciser votre situation professionnelle.  Vous êtes actuellement : ']\n",
    "liste_situation=list(set(donnees_situation))\n",
    "del liste_situation[liste_situation.index(np.nan)]\n",
    "dico_situation={}\n",
    "for situation in liste_situation:\n",
    "    dico_situation[situation]=len(donnees.loc[donnees.loc[:,'Merci de nous préciser votre situation professionnelle.  Vous êtes actuellement : ']==situation,'Merci de nous préciser votre situation professionnelle.  Vous êtes actuellement : '])\n",
    "\n",
    "a=pd.Series(d_situation)\n",
    "a_clé=list(a.keys())\n",
    "a_clé[8]='Salarié(e) de la fonction publique'\n",
    "a_clé[9]=\"Salarié(e) d'une entreprise\"\n",
    "plt.figure(figsize=(10,5))\n",
    "pd.Series(a.values,index=a_clé).sort_values(ascending=False).plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## D0xxFUN DILLPrivatePublic\n",
    "\n",
    "donnees_fonction=donnees.loc[:,'Quelle est votre fonction ?']\n",
    "liste_fonction=list(set(donnees_fonction))\n",
    "del liste_fonction[liste_fonction.index(np.nan)]\n",
    "dico_fonction={}\n",
    "for fonction in liste_fonction:\n",
    "    dico_fonction[fonction]=len(donnees.loc[donnees.loc[:,'Quelle est votre fonction ?']==fonction,'Quelle est votre fonction ?'])\n",
    "\n",
    "plt.figure(figsize=(10,5))\n",
    "pd.Series(dico_fonction).sort_values(ascending=False).plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## DILLDiscipline\n",
    "\n",
    "chimie=donnees.loc[donnees.loc[:,'Quelle est votre discipline ? [Chimie]']=='Oui','Quelle est votre discipline ? [Chimie]'].count()\n",
    "physique_SI=donnees.loc[donnees.loc[:,\"Quelle est votre discipline ? [Physique, sciences de l'ingénieur]\"]=='Oui',\"Quelle est votre discipline ? [Physique, sciences de l'ingénieur]\"].count()\n",
    "informatique=donnees.loc[donnees.loc[:,\"Quelle est votre discipline ? [Informatique]\"]=='Oui',\"Quelle est votre discipline ? [Informatique]\"].count()\n",
    "maths=donnees.loc[donnees.loc[:,\"Quelle est votre discipline ? [Mathématiques]\"]=='Oui',\"Quelle est votre discipline ? [Mathématiques]\"].count()\n",
    "science_cognitives=donnees.loc[donnees.loc[:,\"Quelle est votre discipline ? [Sciences cognitives]\"]=='Oui',\"Quelle est votre discipline ? [Sciences cognitives]\"].count()\n",
    "environnement_planete_univers=donnees.loc[donnees.loc[:,\"Quelle est votre discipline ? [Sciences de l'environnement, Planète et Univers]\"]=='Oui',\"Quelle est votre discipline ? [Sciences de l'environnement, Planète et Univers]\"].count()\n",
    "sciences_du_vivant=donnees.loc[donnees.loc[:,\"Quelle est votre discipline ? [Sciences du Vivant (Biologie, Sciences agricoles, Sciences pharmaceutiques,  Alimentation, Médecine, ...)]\"]=='Oui',\"Quelle est votre discipline ? [Sciences du Vivant (Biologie, Sciences agricoles, Sciences pharmaceutiques,  Alimentation, Médecine, ...)]\"].count()\n",
    "homme_société=donnees.loc[donnees.loc[:,\"Quelle est votre discipline ? [Sciences de l'Homme et Société]\"]=='Oui',\"Quelle est votre discipline ? [Sciences de l'Homme et Société]\"].count()\n",
    "economie=donnees.loc[donnees.loc[:,\"Quelle est votre discipline ? [Économie et finance quantitative]\"]=='Oui',\"Quelle est votre discipline ? [Économie et finance quantitative]\"].count()\n",
    "autre=donnees.loc[donnees.loc[:,\"Quelle est votre discipline ? [Autre]\"]!=np.nan,\"Quelle est votre discipline ? [Autre]\"].count()\n",
    "\n",
    "discipline=[\"Chimie\",\"Physique et Scince de l'ingénieur\",\"Informatique\",\"Mathématiques\",\"Sciences cognitives\",\"Sciences de l'environnement, Planète et Univers\",\"Sciences du vivant\",\"Sciences de l'homme et société\",\"Economie et finance quantitative\",\"Autre\"]\n",
    "nbr_discipline=[chimie,physique_SI,informatique,maths,science_cognitives,environnement_planete_univers,sciences_du_vivant,homme_société,economie,autre]\n",
    "plt.figure(figsize=(10,5))\n",
    "pd.Series(nbr_discipline,index=discipline).sort_values(ascending=False).plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## DILLlevel\n",
    "\n",
    "liste_niveau_info=[\"Inconnu\",\"Débutant\",\"Intermédiaire\",\"Confirmé\"]\n",
    "\n",
    "donnees_python=donnees.loc[:,'Quel est votre niveau de connaissance de :  [Langage Python]']\n",
    "dico_python={}\n",
    "for niveau in liste_niveau_info:\n",
    "    dico_python[niveau]=len(donnees.loc[donnees.loc[:,'Quel est votre niveau de connaissance de :  [Langage Python]']==niveau,'Quel est votre niveau de connaissance de :  [Langage Python]'])\n",
    "python=pd.Series(dico_python)\n",
    "\n",
    "donnees_R=donnees.loc[:,'Quel est votre niveau de connaissance de :  [langage R]']\n",
    "dico_R={}\n",
    "for niveau in liste_niveau_info:\n",
    "    dico_R[niveau]=len(donnees.loc[donnees.loc[:,'Quel est votre niveau de connaissance de :  [langage R]']==niveau,'Quel est votre niveau de connaissance de :  [langage R]'])\n",
    "R=pd.Series(dico_R)\n",
    "\n",
    "donnees_git=donnees.loc[:,'Quel est votre niveau de connaissance de :  [Git / Gitlab]']\n",
    "dico_git={}\n",
    "for niveau in liste_niveau_info:\n",
    "    dico_git[niveau]=len(donnees.loc[donnees.loc[:,'Quel est votre niveau de connaissance de :  [Git / Gitlab]']==niveau,'Quel est votre niveau de connaissance de :  [Git / Gitlab]'])\n",
    "git=pd.Series(dico_git)\n",
    "\n",
    "pd.DataFrame({\"Git/Gitlab\":git,\"Python\":python,\"R\":R}).T.plot(kind='bar',figsize=(15,7))\n",
    "plt.legend(loc='upper center')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autres :\n",
      "\n",
      "['LORIA', 'Sustainable Research Unit - REHABS (Nelson Mandela University & Univ. de Lyon)', 'LAAS', 'LEGOS/OBS-MIP', 'IRCGN', 'LAMIH', 'GEPEA', 'SCK-CEN, Belgique', 'VetAgro Sup', 'IMT Atlantique', 'IGF ', 'EPHE (Ecole Pratique des Hautes Etudes)', 'IADI', 'FEMTO-ST', 'CRCA', 'ENSAM', 'Arts et métiers ParisTech', 'National Institute of Standards and Technology ; Centre de Recherche en Automation de Nancy', 'Institut du Cerveau (ICM)', 'CEA/LITEN/LCO GRENOBLE', 'CEA Grenoble', 'Agrocampus', 'Sorbonne Université', 'CEA LETI', 'IRIT', 'ENSAM PARIS', 'CRBM', 'Collège de France', 'PhLAM']\n"
     ]
    }
   ],
   "source": [
    "## DILLEPST\n",
    "\n",
    "EPST=donnees.loc[donnees.loc[:,\"Si vous travaillez dans un institut de recherche ou une université, précisez son type et son nom (acronyme si possible) [EPST (établissement public à caractère scientifique et technologique)]\"]=='Oui',\"Si vous travaillez dans un institut de recherche ou une université, précisez son type et son nom (acronyme si possible) [EPST (établissement public à caractère scientifique et technologique)]\"].count()\n",
    "EPIC=donnees.loc[donnees.loc[:,\"Si vous travaillez dans un institut de recherche ou une université, précisez son type et son nom (acronyme si possible) [EPIC (établissements publics industriels et commerciaux)]\"]=='Oui',\"Si vous travaillez dans un institut de recherche ou une université, précisez son type et son nom (acronyme si possible) [EPIC (établissements publics industriels et commerciaux)]\"].count()\n",
    "Universite=donnees.loc[donnees.loc[:,\"Si vous travaillez dans un institut de recherche ou une université, précisez son type et son nom (acronyme si possible) [Université]\"]=='Oui',\"Si vous travaillez dans un institut de recherche ou une université, précisez son type et son nom (acronyme si possible) [Université]\"].count()\n",
    "autre=donnees.loc[donnees.loc[:,\"Si vous travaillez dans un institut de recherche ou une université, précisez son type et son nom (acronyme si possible) [Autre]\"]=='Oui',\"Si vous travaillez dans un institut de recherche ou une université, précisez son type et son nom (acronyme si possible) [Autre]\"].count()\n",
    "\n",
    "etablissement=[\"EPST\",\"EPIC\",\"Université\",\"Autre\"]\n",
    "nbr_etablissement=[EPST,EPIC,Universite,autre]\n",
    "pd.Series(nbr_etablissement,index=etablissement).sort_values(ascending=False).plot(kind='bar',figsize=(15,7))\n",
    "plt.show()\n",
    "\n",
    "liste_EPST=list(donnees.loc[:,\"Si vous travaillez dans un institut de recherche ou une université, précisez son type et son nom (acronyme si possible) [EPST (établissement public à caractère scientifique et technologique)][Commentaire]\"].dropna())\n",
    "dico_EPST={\"INRA\":0,\"CNRS\":0,\"IFSTTAR\":0,\"INED\":0,\"INRIA\":0,\"INSERM\":0,\"IRD\":0,\"Autre\":0}\n",
    "liste_autres=[]\n",
    "for n_EPST in liste_EPST:\n",
    "    if \"INRA\" in n_EPST.upper():\n",
    "        dico_EPST[\"INRA\"]+=1\n",
    "    elif \"CNRS\" in n_EPST.upper():\n",
    "        dico_EPST[\"CNRS\"]+=1\n",
    "    elif \"IFSTTAR\" in n_EPST.upper():\n",
    "        dico_EPST[\"IFSTTAR\"]+=1\n",
    "    elif \"INED\" in n_EPST.upper():\n",
    "        dico_EPST[\"INED\"]+=1\n",
    "    elif \"INRIA\" in n_EPST.upper():\n",
    "        dico_EPST[\"INRIA\"]+=1\n",
    "    elif \"INSERM\" in n_EPST.upper():\n",
    "        dico_EPST[\"INSERM\"]+=1\n",
    "    elif \"IRD\" in n_EPST.upper():\n",
    "        dico_EPST[\"IRD\"]+=1\n",
    "    else:\n",
    "        liste_autres+=[n_EPST]\n",
    "        dico_EPST[\"Autre\"]+=1\n",
    "        \n",
    "pd.Series(dico_EPST).sort_values(ascending=False).plot(kind=\"bar\",figsize=(15,7))\n",
    "plt.show()\n",
    "print(\"Autres :\\n\")\n",
    "print(liste_autres)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## ILLOs\n",
    "\n",
    "linux=donnees.loc[donnees.loc[:,\"Sur quel système d'exploitation travaillez-vous ? [Linux]\"]=='Oui',\"Sur quel système d'exploitation travaillez-vous ? [Linux]\"].count()\n",
    "windows=donnees.loc[donnees.loc[:,\"Sur quel système d'exploitation travaillez-vous ? [Windows]\"]=='Oui',\"Sur quel système d'exploitation travaillez-vous ? [Windows]\"].count()\n",
    "macOS=donnees.loc[donnees.loc[:,\"Sur quel système d'exploitation travaillez-vous ? [macOS]\"]=='Oui',\"Sur quel système d'exploitation travaillez-vous ? [macOS]\"].count()\n",
    "Android=donnees.loc[donnees.loc[:,\"Sur quel système d'exploitation travaillez-vous ? [Android]\"]=='Oui',\"Sur quel système d'exploitation travaillez-vous ? [Android]\"].count()\n",
    "iOS=donnees.loc[donnees.loc[:,\"Sur quel système d'exploitation travaillez-vous ? [iOS]\"]=='Oui',\"Sur quel système d'exploitation travaillez-vous ? [iOS]\"].count()\n",
    "autre=donnees.loc[donnees.loc[:,\"Sur quel système d'exploitation travaillez-vous ? [Autre]\"]=='Oui',\"Sur quel système d'exploitation travaillez-vous ? [Autre]\"].count()\n",
    "\n",
    "OS=[\"linus\",\"windows\",\"macOS\",\"android\",\"iOS\",\"Autre\"]\n",
    "nbr_OS=[linux,windows,macOS,Android,iOS,autre]\n",
    "pd.Series(nbr_OS,index=OS).sort_values(ascending=False).plot(kind='bar',figsize=(10,5))\n",
    "plt.show()"
   ]
  }
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