/notebooks/python/Devoir2_correction.ipynb

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   "source": [
    "# Correction du Devoir 2 : lecture de données\n",
    "\n",
    "L'objectif de ce deuxième travail est de valider la partie concernant la syntaxe python.\n",
    "\n",
    "## Consignes\n",
    "\n",
    "Vous devez:\n",
    "\n",
    "* Vérifier que vous maîtrisez les notions abordées dans le notebook concernant la lecture des données.\n",
    "* Télécharger le fichier climat_perpignan.csv\n",
    "* Lire sur le fichier, la température maximale et l'ensoleillement.\n",
    "\n",
    "Deux parties sont demandées :\n",
    "\n",
    "* Lire le fichier par vous même en le parcourant ligne par ligne\n",
    "* Utiliser la fonction read_csv() du module pandas pour lire le tableau.\n",
    "\n",
    "\n",
    "## Partie 1 : lecture à la main"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Janvier        12.400  141.200\n",
      "Février        13.200  160.800\n",
      "Mars           16.000  209.600\n",
      "Avril          18.200  218.000\n",
      "Mai            21.800  235.800\n",
      "Juin           26.200  268.900\n",
      "Juillet        29.200  298.200\n",
      "Août           28.900  267.400\n",
      "Septembre      25.400  222.200\n",
      "Octobre        21.000  167.600\n",
      "Novembre       15.900  149.200\n",
      "Décembre       13.100  126.100\n"
     ]
    }
   ],
   "source": [
    "# ouverture du fichier en mode lecture \"r\"\n",
    "with open(\"climat_perpignan.csv\", \"r\") as f:\n",
    "    \n",
    "    # préaration des listes pour enregistrer les valeurs\n",
    "    temperature_max = list()\n",
    "    ensoleillement = list()\n",
    "    \n",
    "    # lecture des deux premières lignes\n",
    "    f.readline()\n",
    "    f.readline()\n",
    "    \n",
    "    # boucle sur les lignes du fichier\n",
    "    for line in f:\n",
    "        # découpage de la ligne suivant le ;\n",
    "        valeurs = line.split(\";\")\n",
    "        \n",
    "        # on récupère la colonne 2 et 4\n",
    "        # on remplace la , par un . avec replace\n",
    "        # on convertit en nombre avec float\n",
    "        tmax = float(valeurs[2].replace(\",\", \".\"))\n",
    "        soleil = float(valeurs[4].replace(\",\", \".\"))\n",
    "        \n",
    "        # ajout dans les listes \n",
    "        temperature_max.append(tmax)\n",
    "        ensoleillement.append(soleil)\n",
    "        \n",
    "        # affichage propre des valeurs\n",
    "        mois = valeurs[0]\n",
    "        print(f\"{mois:12s} {tmax:8.3f} {soleil:8.3f}\")\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut afficher le contenu des listes :\n",
    "\n",
    "##### Température maximale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[12.4, 13.2, 16.0, 18.2, 21.8, 26.2, 29.2, 28.9, 25.4, 21.0, 15.9, 13.1]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temperature_max"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Ensoleillement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[141.2,\n",
       " 160.8,\n",
       " 209.6,\n",
       " 218.0,\n",
       " 235.8,\n",
       " 268.9,\n",
       " 298.2,\n",
       " 267.4,\n",
       " 222.2,\n",
       " 167.6,\n",
       " 149.2,\n",
       " 126.1]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ensoleillement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Partie 2 : lecture du fichier avec pandas\n",
    "\n",
    "Il faut commencer par importer le module pandas :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On utilise maintenant la fonction [`read_csv()`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html) de pandas pour lire le fichier. Voici les éléments que l'on indique pour lire le fichier :\n",
    "\n",
    "* On donne le nom du fichier\n",
    "* Le séparateur est un point virgule => `sep`\n",
    "* On utilise les colonnes 0, 2 et 4 => `usecolos`\n",
    "* On saute la première ligne => `skiprows`\n",
    "* Les nombres décimaux sont écris avec une virgule => `decimal`\n",
    "* La première colonne est utilisée comme index => `index_col`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"climat_perpignan.csv\", sep=\";\", usecols=(0, 2, 4), \n",
    "                 skiprows=1, decimal=\",\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "<div>\n",
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       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Température maximale</th>\n",
       "      <th>Durée d'ensoleillement (h)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Janvier</th>\n",
       "      <td>12.4</td>\n",
       "      <td>141.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Février</th>\n",
       "      <td>13.2</td>\n",
       "      <td>160.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mars</th>\n",
       "      <td>16.0</td>\n",
       "      <td>209.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Avril</th>\n",
       "      <td>18.2</td>\n",
       "      <td>218.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mai</th>\n",
       "      <td>21.8</td>\n",
       "      <td>235.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Juin</th>\n",
       "      <td>26.2</td>\n",
       "      <td>268.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Juillet</th>\n",
       "      <td>29.2</td>\n",
       "      <td>298.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Août</th>\n",
       "      <td>28.9</td>\n",
       "      <td>267.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Septembre</th>\n",
       "      <td>25.4</td>\n",
       "      <td>222.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Octobre</th>\n",
       "      <td>21.0</td>\n",
       "      <td>167.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Novembre</th>\n",
       "      <td>15.9</td>\n",
       "      <td>149.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Décembre</th>\n",
       "      <td>13.1</td>\n",
       "      <td>126.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Température maximale  Durée d'ensoleillement (h)\n",
       "Janvier                    12.4                       141.2\n",
       "Février                    13.2                       160.8\n",
       "Mars                       16.0                       209.6\n",
       "Avril                      18.2                       218.0\n",
       "Mai                        21.8                       235.8\n",
       "Juin                       26.2                       268.9\n",
       "Juillet                    29.2                       298.2\n",
       "Août                       28.9                       267.4\n",
       "Septembre                  25.4                       222.2\n",
       "Octobre                    21.0                       167.6\n",
       "Novembre                   15.9                       149.2\n",
       "Décembre                   13.1                       126.1"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df"
   ]
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