exo pandas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ce fichier vous servira pour vos exercises "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "importer la librairie pandas et renommer la en pd\n",
    "\n",
    "Créer un DataFrame food_info via le fichier csv food_info.csv\n",
    "\n",
    "Assigner la 100 eme ligne du dataframe food_info à la variable row_100\n",
    "\n",
    "afficher le resultat.\n",
    "\n",
    "Je voudrais connaitre le nombre de ligne effectives dans la colonne \"Water_(g)\" (Combien de lignes sont avec du contenu \"donc sans la valeur NaN\")\n",
    "\n",
    "Assigner le résultat sous c_water et afficher le résultat\n",
    "\n",
    "pour info : https://pandas.pydata.org/pandas-docs/stable/reference/frame.html\n",
    "\n",
    "​\n",
    "Sélectionner les 5 dernieres lignes de food_info et assigner à la variable last_rows.\n",
    "\n",
    "Recommencer mais d'une autre façon en assignant la variable last_rows2\n",
    "\n",
    "\n",
    "​\n",
    "Assigner la colonne \"protein_(g)\" à la variable protein.\n",
    "\n",
    "Assigner la colonne \"Cholestrl_(mg)\" à la variable cholesterol.\n",
    "\n",
    "Afficher les resultats\n",
    "\n",
    "\n",
    "​\n",
    "Sélectionner les colonnes \"Shrt_Desc\", \"Selenium_(mcg)\" et \"Thiamin_(mg)\" et assigner le DataFrame resultant à la variable selenium_thiamin.\n",
    "\n",
    "Afficher le résultat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "food_info = pd.read_csv(\"food_info.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "row_100 = food_info.loc[99]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NDB_No                                  1111\n",
       "Shrt_Desc          MILK SHAKES THICK VANILLA\n",
       "Water_(g)                              74.45\n",
       "Energ_Kcal                               112\n",
       "Protein_(g)                             3.86\n",
       "Lipid_Tot_(g)                           3.03\n",
       "Ash_(g)                                 0.91\n",
       "Carbohydrt_(g)                         17.75\n",
       "Fiber_TD_(g)                               0\n",
       "Sugar_Tot_(g)                          17.75\n",
       "Calcium_(mg)                             146\n",
       "Iron_(mg)                                0.1\n",
       "Magnesium_(mg)                            12\n",
       "Phosphorus_(mg)                          115\n",
       "Potassium_(mg)                           183\n",
       "Sodium_(mg)                               95\n",
       "Zinc_(mg)                               0.39\n",
       "Copper_(mg)                            0.051\n",
       "Manganese_(mg)                         0.014\n",
       "Selenium_(mcg)                           2.3\n",
       "Vit_C_(mg)                                 0\n",
       "Thiamin_(mg)                            0.03\n",
       "Riboflavin_(mg)                        0.195\n",
       "Niacin_(mg)                            0.146\n",
       "Vit_B6_(mg)                            0.042\n",
       "Vit_B12_(mcg)                           0.52\n",
       "Vit_A_IU                                  91\n",
       "Vit_A_RAE                                 25\n",
       "Vit_E_(mg)                              0.05\n",
       "Vit_D_mcg                                1.2\n",
       "Vit_D_IU                                  48\n",
       "Vit_K_(mcg)                              0.2\n",
       "FA_Sat_(g)                             1.886\n",
       "FA_Mono_(g)                            0.875\n",
       "FA_Poly_(g)                            0.113\n",
       "Cholestrl_(mg)                            12\n",
       "Name: 99, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "row_100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "c_water = food_info[\"Water_(g)\"].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8612"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c_water"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       15.87\n",
       "1       15.87\n",
       "2        0.24\n",
       "3       42.41\n",
       "4       41.11\n",
       "        ...  \n",
       "8613    43.00\n",
       "8614    70.25\n",
       "8615    26.00\n",
       "8616    79.20\n",
       "8617    78.50\n",
       "Name: Water_(g), Length: 8618, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "food_info[\"Water_(g)\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "last_rows = food_info.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>NDB_No</th>\n",
       "      <th>Shrt_Desc</th>\n",
       "      <th>Water_(g)</th>\n",
       "      <th>Energ_Kcal</th>\n",
       "      <th>Protein_(g)</th>\n",
       "      <th>Lipid_Tot_(g)</th>\n",
       "      <th>Ash_(g)</th>\n",
       "      <th>Carbohydrt_(g)</th>\n",
       "      <th>Fiber_TD_(g)</th>\n",
       "      <th>Sugar_Tot_(g)</th>\n",
       "      <th>...</th>\n",
       "      <th>Vit_A_IU</th>\n",
       "      <th>Vit_A_RAE</th>\n",
       "      <th>Vit_E_(mg)</th>\n",
       "      <th>Vit_D_mcg</th>\n",
       "      <th>Vit_D_IU</th>\n",
       "      <th>Vit_K_(mcg)</th>\n",
       "      <th>FA_Sat_(g)</th>\n",
       "      <th>FA_Mono_(g)</th>\n",
       "      <th>FA_Poly_(g)</th>\n",
       "      <th>Cholestrl_(mg)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8613</th>\n",
       "      <td>83110</td>\n",
       "      <td>MACKEREL SALTED</td>\n",
       "      <td>43.00</td>\n",
       "      <td>305</td>\n",
       "      <td>18.50</td>\n",
       "      <td>25.10</td>\n",
       "      <td>13.40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>157.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>2.38</td>\n",
       "      <td>25.2</td>\n",
       "      <td>1006.0</td>\n",
       "      <td>7.8</td>\n",
       "      <td>7.148</td>\n",
       "      <td>8.320</td>\n",
       "      <td>6.210</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8614</th>\n",
       "      <td>90240</td>\n",
       "      <td>SCALLOP (BAY&amp;SEA) CKD STMD</td>\n",
       "      <td>70.25</td>\n",
       "      <td>111</td>\n",
       "      <td>20.54</td>\n",
       "      <td>0.84</td>\n",
       "      <td>2.97</td>\n",
       "      <td>5.41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.218</td>\n",
       "      <td>0.082</td>\n",
       "      <td>0.222</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8615</th>\n",
       "      <td>90480</td>\n",
       "      <td>SYRUP CANE</td>\n",
       "      <td>26.00</td>\n",
       "      <td>269</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.86</td>\n",
       "      <td>73.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8616</th>\n",
       "      <td>90560</td>\n",
       "      <td>SNAIL RAW</td>\n",
       "      <td>79.20</td>\n",
       "      <td>90</td>\n",
       "      <td>16.10</td>\n",
       "      <td>1.40</td>\n",
       "      <td>1.30</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.361</td>\n",
       "      <td>0.259</td>\n",
       "      <td>0.252</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8617</th>\n",
       "      <td>93600</td>\n",
       "      <td>TURTLE GREEN RAW</td>\n",
       "      <td>78.50</td>\n",
       "      <td>89</td>\n",
       "      <td>19.80</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.127</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.170</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      NDB_No                   Shrt_Desc  Water_(g)  Energ_Kcal  Protein_(g)  \\\n",
       "8613   83110             MACKEREL SALTED      43.00         305        18.50   \n",
       "8614   90240  SCALLOP (BAY&SEA) CKD STMD      70.25         111        20.54   \n",
       "8615   90480                  SYRUP CANE      26.00         269         0.00   \n",
       "8616   90560                   SNAIL RAW      79.20          90        16.10   \n",
       "8617   93600            TURTLE GREEN RAW      78.50          89        19.80   \n",
       "\n",
       "      Lipid_Tot_(g)  Ash_(g)  Carbohydrt_(g)  Fiber_TD_(g)  Sugar_Tot_(g)  \\\n",
       "8613          25.10    13.40            0.00           0.0            0.0   \n",
       "8614           0.84     2.97            5.41           0.0            0.0   \n",
       "8615           0.00     0.86           73.14           0.0           73.2   \n",
       "8616           1.40     1.30            2.00           0.0            0.0   \n",
       "8617           0.50     1.20            0.00           0.0            0.0   \n",
       "\n",
       "      ...  Vit_A_IU  Vit_A_RAE  Vit_E_(mg)  Vit_D_mcg  Vit_D_IU  Vit_K_(mcg)  \\\n",
       "8613  ...     157.0       47.0        2.38       25.2    1006.0          7.8   \n",
       "8614  ...       5.0        2.0        0.00        0.0       2.0          0.0   \n",
       "8615  ...       0.0        0.0        0.00        0.0       0.0          0.0   \n",
       "8616  ...     100.0       30.0        5.00        0.0       0.0          0.1   \n",
       "8617  ...     100.0       30.0        0.50        0.0       0.0          0.1   \n",
       "\n",
       "      FA_Sat_(g)  FA_Mono_(g)  FA_Poly_(g)  Cholestrl_(mg)  \n",
       "8613       7.148        8.320        6.210            95.0  \n",
       "8614       0.218        0.082        0.222            41.0  \n",
       "8615       0.000        0.000        0.000             0.0  \n",
       "8616       0.361        0.259        0.252            50.0  \n",
       "8617       0.127        0.088        0.170            50.0  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "last_rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>NDB_No</th>\n",
       "      <th>Shrt_Desc</th>\n",
       "      <th>Water_(g)</th>\n",
       "      <th>Energ_Kcal</th>\n",
       "      <th>Protein_(g)</th>\n",
       "      <th>Lipid_Tot_(g)</th>\n",
       "      <th>Ash_(g)</th>\n",
       "      <th>Carbohydrt_(g)</th>\n",
       "      <th>Fiber_TD_(g)</th>\n",
       "      <th>Sugar_Tot_(g)</th>\n",
       "      <th>...</th>\n",
       "      <th>Vit_A_IU</th>\n",
       "      <th>Vit_A_RAE</th>\n",
       "      <th>Vit_E_(mg)</th>\n",
       "      <th>Vit_D_mcg</th>\n",
       "      <th>Vit_D_IU</th>\n",
       "      <th>Vit_K_(mcg)</th>\n",
       "      <th>FA_Sat_(g)</th>\n",
       "      <th>FA_Mono_(g)</th>\n",
       "      <th>FA_Poly_(g)</th>\n",
       "      <th>Cholestrl_(mg)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8613</th>\n",
       "      <td>83110</td>\n",
       "      <td>MACKEREL SALTED</td>\n",
       "      <td>43.00</td>\n",
       "      <td>305</td>\n",
       "      <td>18.50</td>\n",
       "      <td>25.10</td>\n",
       "      <td>13.40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>157.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>2.38</td>\n",
       "      <td>25.2</td>\n",
       "      <td>1006.0</td>\n",
       "      <td>7.8</td>\n",
       "      <td>7.148</td>\n",
       "      <td>8.320</td>\n",
       "      <td>6.210</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8614</th>\n",
       "      <td>90240</td>\n",
       "      <td>SCALLOP (BAY&amp;SEA) CKD STMD</td>\n",
       "      <td>70.25</td>\n",
       "      <td>111</td>\n",
       "      <td>20.54</td>\n",
       "      <td>0.84</td>\n",
       "      <td>2.97</td>\n",
       "      <td>5.41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.218</td>\n",
       "      <td>0.082</td>\n",
       "      <td>0.222</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8615</th>\n",
       "      <td>90480</td>\n",
       "      <td>SYRUP CANE</td>\n",
       "      <td>26.00</td>\n",
       "      <td>269</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.86</td>\n",
       "      <td>73.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8616</th>\n",
       "      <td>90560</td>\n",
       "      <td>SNAIL RAW</td>\n",
       "      <td>79.20</td>\n",
       "      <td>90</td>\n",
       "      <td>16.10</td>\n",
       "      <td>1.40</td>\n",
       "      <td>1.30</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.361</td>\n",
       "      <td>0.259</td>\n",
       "      <td>0.252</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8617</th>\n",
       "      <td>93600</td>\n",
       "      <td>TURTLE GREEN RAW</td>\n",
       "      <td>78.50</td>\n",
       "      <td>89</td>\n",
       "      <td>19.80</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.127</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.170</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      NDB_No                   Shrt_Desc  Water_(g)  Energ_Kcal  Protein_(g)  \\\n",
       "8613   83110             MACKEREL SALTED      43.00         305        18.50   \n",
       "8614   90240  SCALLOP (BAY&SEA) CKD STMD      70.25         111        20.54   \n",
       "8615   90480                  SYRUP CANE      26.00         269         0.00   \n",
       "8616   90560                   SNAIL RAW      79.20          90        16.10   \n",
       "8617   93600            TURTLE GREEN RAW      78.50          89        19.80   \n",
       "\n",
       "      Lipid_Tot_(g)  Ash_(g)  Carbohydrt_(g)  Fiber_TD_(g)  Sugar_Tot_(g)  \\\n",
       "8613          25.10    13.40            0.00           0.0            0.0   \n",
       "8614           0.84     2.97            5.41           0.0            0.0   \n",
       "8615           0.00     0.86           73.14           0.0           73.2   \n",
       "8616           1.40     1.30            2.00           0.0            0.0   \n",
       "8617           0.50     1.20            0.00           0.0            0.0   \n",
       "\n",
       "      ...  Vit_A_IU  Vit_A_RAE  Vit_E_(mg)  Vit_D_mcg  Vit_D_IU  Vit_K_(mcg)  \\\n",
       "8613  ...     157.0       47.0        2.38       25.2    1006.0          7.8   \n",
       "8614  ...       5.0        2.0        0.00        0.0       2.0          0.0   \n",
       "8615  ...       0.0        0.0        0.00        0.0       0.0          0.0   \n",
       "8616  ...     100.0       30.0        5.00        0.0       0.0          0.1   \n",
       "8617  ...     100.0       30.0        0.50        0.0       0.0          0.1   \n",
       "\n",
       "      FA_Sat_(g)  FA_Mono_(g)  FA_Poly_(g)  Cholestrl_(mg)  \n",
       "8613       7.148        8.320        6.210            95.0  \n",
       "8614       0.218        0.082        0.222            41.0  \n",
       "8615       0.000        0.000        0.000             0.0  \n",
       "8616       0.361        0.259        0.252            50.0  \n",
       "8617       0.127        0.088        0.170            50.0  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "last_rows1 = [8613, 8614, 8615, 8616, 8617]\n",
    "last_row2 = food_info.loc[last_rows1]\n",
    "last_row2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8618\n"
     ]
    },
    {
     "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>NDB_No</th>\n",
       "      <th>Shrt_Desc</th>\n",
       "      <th>Water_(g)</th>\n",
       "      <th>Energ_Kcal</th>\n",
       "      <th>Protein_(g)</th>\n",
       "      <th>Lipid_Tot_(g)</th>\n",
       "      <th>Ash_(g)</th>\n",
       "      <th>Carbohydrt_(g)</th>\n",
       "      <th>Fiber_TD_(g)</th>\n",
       "      <th>Sugar_Tot_(g)</th>\n",
       "      <th>...</th>\n",
       "      <th>Vit_A_IU</th>\n",
       "      <th>Vit_A_RAE</th>\n",
       "      <th>Vit_E_(mg)</th>\n",
       "      <th>Vit_D_mcg</th>\n",
       "      <th>Vit_D_IU</th>\n",
       "      <th>Vit_K_(mcg)</th>\n",
       "      <th>FA_Sat_(g)</th>\n",
       "      <th>FA_Mono_(g)</th>\n",
       "      <th>FA_Poly_(g)</th>\n",
       "      <th>Cholestrl_(mg)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8613</th>\n",
       "      <td>83110</td>\n",
       "      <td>MACKEREL SALTED</td>\n",
       "      <td>43.00</td>\n",
       "      <td>305</td>\n",
       "      <td>18.50</td>\n",
       "      <td>25.10</td>\n",
       "      <td>13.40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>157.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>2.38</td>\n",
       "      <td>25.2</td>\n",
       "      <td>1006.0</td>\n",
       "      <td>7.8</td>\n",
       "      <td>7.148</td>\n",
       "      <td>8.320</td>\n",
       "      <td>6.210</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8614</th>\n",
       "      <td>90240</td>\n",
       "      <td>SCALLOP (BAY&amp;SEA) CKD STMD</td>\n",
       "      <td>70.25</td>\n",
       "      <td>111</td>\n",
       "      <td>20.54</td>\n",
       "      <td>0.84</td>\n",
       "      <td>2.97</td>\n",
       "      <td>5.41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.218</td>\n",
       "      <td>0.082</td>\n",
       "      <td>0.222</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8615</th>\n",
       "      <td>90480</td>\n",
       "      <td>SYRUP CANE</td>\n",
       "      <td>26.00</td>\n",
       "      <td>269</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.86</td>\n",
       "      <td>73.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8616</th>\n",
       "      <td>90560</td>\n",
       "      <td>SNAIL RAW</td>\n",
       "      <td>79.20</td>\n",
       "      <td>90</td>\n",
       "      <td>16.10</td>\n",
       "      <td>1.40</td>\n",
       "      <td>1.30</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.361</td>\n",
       "      <td>0.259</td>\n",
       "      <td>0.252</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8617</th>\n",
       "      <td>93600</td>\n",
       "      <td>TURTLE GREEN RAW</td>\n",
       "      <td>78.50</td>\n",
       "      <td>89</td>\n",
       "      <td>19.80</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.127</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.170</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      NDB_No                   Shrt_Desc  Water_(g)  Energ_Kcal  Protein_(g)  \\\n",
       "8613   83110             MACKEREL SALTED      43.00         305        18.50   \n",
       "8614   90240  SCALLOP (BAY&SEA) CKD STMD      70.25         111        20.54   \n",
       "8615   90480                  SYRUP CANE      26.00         269         0.00   \n",
       "8616   90560                   SNAIL RAW      79.20          90        16.10   \n",
       "8617   93600            TURTLE GREEN RAW      78.50          89        19.80   \n",
       "\n",
       "      Lipid_Tot_(g)  Ash_(g)  Carbohydrt_(g)  Fiber_TD_(g)  Sugar_Tot_(g)  \\\n",
       "8613          25.10    13.40            0.00           0.0            0.0   \n",
       "8614           0.84     2.97            5.41           0.0            0.0   \n",
       "8615           0.00     0.86           73.14           0.0           73.2   \n",
       "8616           1.40     1.30            2.00           0.0            0.0   \n",
       "8617           0.50     1.20            0.00           0.0            0.0   \n",
       "\n",
       "      ...  Vit_A_IU  Vit_A_RAE  Vit_E_(mg)  Vit_D_mcg  Vit_D_IU  Vit_K_(mcg)  \\\n",
       "8613  ...     157.0       47.0        2.38       25.2    1006.0          7.8   \n",
       "8614  ...       5.0        2.0        0.00        0.0       2.0          0.0   \n",
       "8615  ...       0.0        0.0        0.00        0.0       0.0          0.0   \n",
       "8616  ...     100.0       30.0        5.00        0.0       0.0          0.1   \n",
       "8617  ...     100.0       30.0        0.50        0.0       0.0          0.1   \n",
       "\n",
       "      FA_Sat_(g)  FA_Mono_(g)  FA_Poly_(g)  Cholestrl_(mg)  \n",
       "8613       7.148        8.320        6.210            95.0  \n",
       "8614       0.218        0.082        0.222            41.0  \n",
       "8615       0.000        0.000        0.000             0.0  \n",
       "8616       0.361        0.259        0.252            50.0  \n",
       "8617       0.127        0.088        0.170            50.0  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_rows = food_info.shape[0]\n",
    "print(num_rows)\n",
    "# shape[0] permet de connaitre le nombre de lignes dans notre DataFrame\n",
    "\n",
    "last_rows = food_info.loc[num_rows - 5:num_rows -1]\n",
    "last_rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0        0.85\n",
      "1        0.85\n",
      "2        0.28\n",
      "3       21.40\n",
      "4       23.24\n",
      "        ...  \n",
      "8613    18.50\n",
      "8614    20.54\n",
      "8615     0.00\n",
      "8616    16.10\n",
      "8617    19.80\n",
      "Name: Protein_(g), Length: 8618, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "protein = food_info[\"Protein_(g)\"]\n",
    "print(protein)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0       215.0\n",
      "1       219.0\n",
      "2       256.0\n",
      "3        75.0\n",
      "4        94.0\n",
      "        ...  \n",
      "8613     95.0\n",
      "8614     41.0\n",
      "8615      0.0\n",
      "8616     50.0\n",
      "8617     50.0\n",
      "Name: Cholestrl_(mg), Length: 8618, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "cholesterol = food_info[\"Cholestrl_(mg)\"]\n",
    "print(cholesterol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "selenium_thiamin = food_info[[\"Shrt_Desc\", \"Selenium_(mcg)\", \"Thiamin_(mg)\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Shrt_Desc</th>\n",
       "      <th>Selenium_(mcg)</th>\n",
       "      <th>Thiamin_(mg)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BUTTER WITH SALT</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BUTTER WHIPPED WITH SALT</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BUTTER OIL ANHYDROUS</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CHEESE BLUE</td>\n",
       "      <td>14.5</td>\n",
       "      <td>0.029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CHEESE BRICK</td>\n",
       "      <td>14.5</td>\n",
       "      <td>0.014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8613</th>\n",
       "      <td>MACKEREL SALTED</td>\n",
       "      <td>73.4</td>\n",
       "      <td>0.020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8614</th>\n",
       "      <td>SCALLOP (BAY&amp;SEA) CKD STMD</td>\n",
       "      <td>21.7</td>\n",
       "      <td>0.012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8615</th>\n",
       "      <td>SYRUP CANE</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8616</th>\n",
       "      <td>SNAIL RAW</td>\n",
       "      <td>27.4</td>\n",
       "      <td>0.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8617</th>\n",
       "      <td>TURTLE GREEN RAW</td>\n",
       "      <td>16.8</td>\n",
       "      <td>0.120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8618 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Shrt_Desc  Selenium_(mcg)  Thiamin_(mg)\n",
       "0               BUTTER WITH SALT             1.0         0.005\n",
       "1       BUTTER WHIPPED WITH SALT             1.0         0.005\n",
       "2           BUTTER OIL ANHYDROUS             0.0         0.001\n",
       "3                    CHEESE BLUE            14.5         0.029\n",
       "4                   CHEESE BRICK            14.5         0.014\n",
       "...                          ...             ...           ...\n",
       "8613             MACKEREL SALTED            73.4         0.020\n",
       "8614  SCALLOP (BAY&SEA) CKD STMD            21.7         0.012\n",
       "8615                  SYRUP CANE             0.7         0.130\n",
       "8616                   SNAIL RAW            27.4         0.010\n",
       "8617            TURTLE GREEN RAW            16.8         0.120\n",
       "\n",
       "[8618 rows x 3 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selenium_thiamin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# (Cas pratique)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Selectionner et afficher seulement les colonnes qui utilisent comme unité de mesure les grammes (c'est à dire qui se termine par \"(g)\". Pour cela :\n",
    "\n",
    "Utiliser l'attribut columns pour retourner le nom des colonnes du dataframe food_info et convertir en liste utilisant la methode tolist()\n",
    "\n",
    "Créer une nouvelle liste qu'on nommera gram_columns, contenant seulement les colonnes se terminant par \"(g)\". Indice: la méthode endswith() retourne True si l'objet sur lequel on l'applique se termine par l'élément entre parenthèse. ex: total(g).endswith(\"g\") retourne True. Une boucle for est fortement conseillé pour parcourir les noms de colonne. -Selectionner les colonnes de gram_columns pour le dataframe food_info et assigner le dataframe résultant à la variable gram_df\n",
    "\n",
    "Afficher les 3 premieres valeurs de ce dataframe gram_df\n",
    "\n",
    "Voici la doc pandas au cas ou : https://pandas.pydata.org/pandas-docs/stable/reference/io.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "col_names = food_info.columns.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['NDB_No', 'Shrt_Desc', 'Water_(g)', 'Energ_Kcal', 'Protein_(g)', 'Lipid_Tot_(g)', 'Ash_(g)', 'Carbohydrt_(g)', 'Fiber_TD_(g)', 'Sugar_Tot_(g)', 'Calcium_(mg)', 'Iron_(mg)', 'Magnesium_(mg)', 'Phosphorus_(mg)', 'Potassium_(mg)', 'Sodium_(mg)', 'Zinc_(mg)', 'Copper_(mg)', 'Manganese_(mg)', 'Selenium_(mcg)', 'Vit_C_(mg)', 'Thiamin_(mg)', 'Riboflavin_(mg)', 'Niacin_(mg)', 'Vit_B6_(mg)', 'Vit_B12_(mcg)', 'Vit_A_IU', 'Vit_A_RAE', 'Vit_E_(mg)', 'Vit_D_mcg', 'Vit_D_IU', 'Vit_K_(mcg)', 'FA_Sat_(g)', 'FA_Mono_(g)', 'FA_Poly_(g)', 'Cholestrl_(mg)']\n"
     ]
    }
   ],
   "source": [
    "print(col_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "grams_columns = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>Water_(g)</th>\n",
       "      <th>Protein_(g)</th>\n",
       "      <th>Lipid_Tot_(g)</th>\n",
       "      <th>Ash_(g)</th>\n",
       "      <th>Carbohydrt_(g)</th>\n",
       "      <th>Fiber_TD_(g)</th>\n",
       "      <th>Sugar_Tot_(g)</th>\n",
       "      <th>FA_Sat_(g)</th>\n",
       "      <th>FA_Mono_(g)</th>\n",
       "      <th>FA_Poly_(g)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15.87</td>\n",
       "      <td>0.85</td>\n",
       "      <td>81.11</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>51.368</td>\n",
       "      <td>21.021</td>\n",
       "      <td>3.043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.87</td>\n",
       "      <td>0.85</td>\n",
       "      <td>81.11</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>50.489</td>\n",
       "      <td>23.426</td>\n",
       "      <td>3.012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.24</td>\n",
       "      <td>0.28</td>\n",
       "      <td>99.48</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>61.924</td>\n",
       "      <td>28.732</td>\n",
       "      <td>3.694</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Water_(g)  Protein_(g)  Lipid_Tot_(g)  Ash_(g)  Carbohydrt_(g)  \\\n",
       "0      15.87         0.85          81.11     2.11            0.06   \n",
       "1      15.87         0.85          81.11     2.11            0.06   \n",
       "2       0.24         0.28          99.48     0.00            0.00   \n",
       "\n",
       "   Fiber_TD_(g)  Sugar_Tot_(g)  FA_Sat_(g)  FA_Mono_(g)  FA_Poly_(g)  \n",
       "0           0.0           0.06      51.368       21.021        3.043  \n",
       "1           0.0           0.06      50.489       23.426        3.012  \n",
       "2           0.0           0.00      61.924       28.732        3.694  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for c in col_names :\n",
    "    if c.endswith(\"(g)\"):\n",
    "        grams_columns.append(c)\n",
    "        \n",
    "gram_df = food_info[grams_columns]\n",
    "gram_df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importer la librairie Pandas.\n",
    "\n",
    "Lire le fichier \"food_info.csv\" dans un dataframe qu'on nommera food_info.\n",
    "\n",
    "Utiliser l'attribut DataFrame columns suivi de la méthode Index.tolist() pour retourner une liste contenant tous les noms de colonne de food_info.\n",
    "\n",
    "Assigner la liste resultante à la variable col-names et utiliser la fonction print() pour afficher le nom des colonnes.\n",
    "\n",
    "Enfin afficher les 3 premiers éléments de food_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>NDB_No</th>\n",
       "      <th>Shrt_Desc</th>\n",
       "      <th>Water_(g)</th>\n",
       "      <th>Energ_Kcal</th>\n",
       "      <th>Protein_(g)</th>\n",
       "      <th>Lipid_Tot_(g)</th>\n",
       "      <th>Ash_(g)</th>\n",
       "      <th>Carbohydrt_(g)</th>\n",
       "      <th>Fiber_TD_(g)</th>\n",
       "      <th>Sugar_Tot_(g)</th>\n",
       "      <th>...</th>\n",
       "      <th>Vit_A_IU</th>\n",
       "      <th>Vit_A_RAE</th>\n",
       "      <th>Vit_E_(mg)</th>\n",
       "      <th>Vit_D_mcg</th>\n",
       "      <th>Vit_D_IU</th>\n",
       "      <th>Vit_K_(mcg)</th>\n",
       "      <th>FA_Sat_(g)</th>\n",
       "      <th>FA_Mono_(g)</th>\n",
       "      <th>FA_Poly_(g)</th>\n",
       "      <th>Cholestrl_(mg)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>BUTTER WITH SALT</td>\n",
       "      <td>15.87</td>\n",
       "      <td>717</td>\n",
       "      <td>0.85</td>\n",
       "      <td>81.11</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>...</td>\n",
       "      <td>2499.0</td>\n",
       "      <td>684.0</td>\n",
       "      <td>2.32</td>\n",
       "      <td>1.5</td>\n",
       "      <td>60.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>51.368</td>\n",
       "      <td>21.021</td>\n",
       "      <td>3.043</td>\n",
       "      <td>215.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>BUTTER WHIPPED WITH SALT</td>\n",
       "      <td>15.87</td>\n",
       "      <td>717</td>\n",
       "      <td>0.85</td>\n",
       "      <td>81.11</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>...</td>\n",
       "      <td>2499.0</td>\n",
       "      <td>684.0</td>\n",
       "      <td>2.32</td>\n",
       "      <td>1.5</td>\n",
       "      <td>60.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>50.489</td>\n",
       "      <td>23.426</td>\n",
       "      <td>3.012</td>\n",
       "      <td>219.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>BUTTER OIL ANHYDROUS</td>\n",
       "      <td>0.24</td>\n",
       "      <td>876</td>\n",
       "      <td>0.28</td>\n",
       "      <td>99.48</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>...</td>\n",
       "      <td>3069.0</td>\n",
       "      <td>840.0</td>\n",
       "      <td>2.80</td>\n",
       "      <td>1.8</td>\n",
       "      <td>73.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>61.924</td>\n",
       "      <td>28.732</td>\n",
       "      <td>3.694</td>\n",
       "      <td>256.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   NDB_No                 Shrt_Desc  Water_(g)  Energ_Kcal  Protein_(g)  \\\n",
       "0    1001          BUTTER WITH SALT      15.87         717         0.85   \n",
       "1    1002  BUTTER WHIPPED WITH SALT      15.87         717         0.85   \n",
       "2    1003      BUTTER OIL ANHYDROUS       0.24         876         0.28   \n",
       "\n",
       "   Lipid_Tot_(g)  Ash_(g)  Carbohydrt_(g)  Fiber_TD_(g)  Sugar_Tot_(g)  ...  \\\n",
       "0          81.11     2.11            0.06           0.0           0.06  ...   \n",
       "1          81.11     2.11            0.06           0.0           0.06  ...   \n",
       "2          99.48     0.00            0.00           0.0           0.00  ...   \n",
       "\n",
       "   Vit_A_IU  Vit_A_RAE  Vit_E_(mg)  Vit_D_mcg  Vit_D_IU  Vit_K_(mcg)  \\\n",
       "0    2499.0      684.0        2.32        1.5      60.0          7.0   \n",
       "1    2499.0      684.0        2.32        1.5      60.0          7.0   \n",
       "2    3069.0      840.0        2.80        1.8      73.0          8.6   \n",
       "\n",
       "   FA_Sat_(g)  FA_Mono_(g)  FA_Poly_(g)  Cholestrl_(mg)  \n",
       "0      51.368       21.021        3.043           215.0  \n",
       "1      50.489       23.426        3.012           219.0  \n",
       "2      61.924       28.732        3.694           256.0  \n",
       "\n",
       "[3 rows x 36 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "food_info = pd.read_csv(\"food_info.csv\")\n",
    "col_names = food_info.columns.tolist()\n",
    "food_info.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Transformer une colonne (pratique)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Diviser la colonne \"Sodium_(mg)\" par 1000 pour convertir cette colonne en grammes et assigner le resultat à la variable sodium_grams.\n",
    "\n",
    "- Multiplier la colonne \"Sugar_Tot_(g)\" par 1000 pour convertir en milligrammes et assigner le resultat à la variable sugar_milligrams."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0       0.643\n",
      "1       0.659\n",
      "2       0.002\n",
      "3       1.146\n",
      "4       0.560\n",
      "        ...  \n",
      "8613    4.450\n",
      "8614    0.667\n",
      "8615    0.058\n",
      "8616    0.070\n",
      "8617    0.068\n",
      "Name: Sodium_(mg), Length: 8618, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "sodium_grams = food_info[\"Sodium_(mg)\"] / 1000\n",
    "print(sodium_grams)\n",
    "sugar_milligrams = food_info[\"Sugar_Tot_(g)\"] * 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        643.0\n",
       "1        659.0\n",
       "2          2.0\n",
       "3       1146.0\n",
       "4        560.0\n",
       "         ...  \n",
       "8613    4450.0\n",
       "8614     667.0\n",
       "8615      58.0\n",
       "8616      70.0\n",
       "8617      68.0\n",
       "Name: Sodium_(mg), Length: 8618, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "food_info[\"Sodium_(mg)\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Opérations mathématiques entre colonnes (pratique)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Diviser la colonne \"Protein(g)\" par la colonne \"Water(g)\" et assigner le résultat à la variable grams_of_protein_per_gram_of_water.\n",
    "\n",
    "- Additionner les colonnes \"Calcium(mg)\" et \"Iron(mg\" et assigner le résultat à la variable milligrams_of_calcium_and_iron.\n",
    "\n",
    "- Afficher les resultats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0       0.053560\n",
      "1       0.053560\n",
      "2       1.166667\n",
      "3       0.504598\n",
      "4       0.565313\n",
      "          ...   \n",
      "8613    0.430233\n",
      "8614    0.292384\n",
      "8615    0.000000\n",
      "8616    0.203283\n",
      "8617    0.252229\n",
      "Length: 8618, dtype: float64\n",
      "0        24.02\n",
      "1        24.16\n",
      "2         4.00\n",
      "3       528.31\n",
      "4       674.43\n",
      "         ...  \n",
      "8613     67.40\n",
      "8614     10.58\n",
      "8615     16.60\n",
      "8616     13.50\n",
      "8617    119.40\n",
      "Length: 8618, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "grams_of_protein_per_gram_of_water = food_info[\"Protein_(g)\"] / food_info[\"Water_(g)\"]\n",
    "print(grams_of_protein_per_gram_of_water)\n",
    "\n",
    "milligrams_of_calcium_and_iron = food_info[\"Calcium_(mg)\"] + food_info[\"Iron_(mg)\"]\n",
    "print(milligrams_of_calcium_and_iron)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Créer un indice nutritionnel (pratique)\n",
    "\n",
    "Score = 2 x (Protein_(g)) - 0.75 x (LipidTot(g))\n",
    "\n",
    "Multiplier la colonne \"Protein_(g)\" par 2 et assigner le résultat à la variable protein.\n",
    "\n",
    "Multiplier la colonne \"LipidTot(g)\" par -0.75 et assigner le résultat à la variable fat.\n",
    "\n",
    "Additionner les variables ensemble et assigner le résultat à la variable rating.\n",
    "\n",
    "Afficher le résultat."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      -59.1325\n",
       "1      -59.1325\n",
       "2      -74.0500\n",
       "3       21.2450\n",
       "4       24.2200\n",
       "         ...   \n",
       "8613    18.1750\n",
       "8614    40.4500\n",
       "8615     0.0000\n",
       "8616    31.1500\n",
       "8617    39.2250\n",
       "Length: 8618, dtype: float64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "protein = food_info[\"Protein_(g)\"] * 2\n",
    "fat = food_info['Lipid_Tot_(g)'] * (-0.75)\n",
    "rating = protein + fat\n",
    "rating"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Normaliser des colonnes (pratique)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Normaliser les valeurs de la colonne \"Protein_(g)\" et assigner le resultat à la variable normalized_protein.\n",
    "\n",
    "- Normaliser les valeurs de la colonne \"Lipid_tot_(g)\" et assigner à la variable normalized_fat.\n",
    "\n",
    "- Afficher les variables normalized_protein et normalized_fat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "normalized_protein = food_info[\"Protein_(g)\"] / food_info[\"Protein_(g)\"].max()\n",
    "\n",
    "normalized_fat = food_info[\"Lipid_Tot_(g)\"] / food_info[\"Lipid_Tot_(g)\"].max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Créer une nouvelle colonne (pratique)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Assigner la colonne normalisée representée par la variable normalized_protein à la nouvelle colonne qu'on nommera \"Normalized_Protein\" dans le DataFrame food_info.\n",
    "\n",
    "Assigner la colonne normalisée représentée par la variable normalized_fat à la nouvelle colonne qu'on nommera \"Normalized_Fat\" dans le DataFrame food_info.\n",
    "\n",
    "Afficher les 5 premieres valeurs du DataFrame food_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>NDB_No</th>\n",
       "      <th>Shrt_Desc</th>\n",
       "      <th>Water_(g)</th>\n",
       "      <th>Energ_Kcal</th>\n",
       "      <th>Protein_(g)</th>\n",
       "      <th>Lipid_Tot_(g)</th>\n",
       "      <th>Ash_(g)</th>\n",
       "      <th>Carbohydrt_(g)</th>\n",
       "      <th>Fiber_TD_(g)</th>\n",
       "      <th>Sugar_Tot_(g)</th>\n",
       "      <th>...</th>\n",
       "      <th>Vit_D_mcg</th>\n",
       "      <th>Vit_D_IU</th>\n",
       "      <th>Vit_K_(mcg)</th>\n",
       "      <th>FA_Sat_(g)</th>\n",
       "      <th>FA_Mono_(g)</th>\n",
       "      <th>FA_Poly_(g)</th>\n",
       "      <th>Cholestrl_(mg)</th>\n",
       "      <th>Normalized_Protein</th>\n",
       "      <th>Normalized_Fat</th>\n",
       "      <th>Norm_Nutr_Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>BUTTER WITH SALT</td>\n",
       "      <td>15.87</td>\n",
       "      <td>717</td>\n",
       "      <td>0.85</td>\n",
       "      <td>81.11</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>...</td>\n",
       "      <td>1.5</td>\n",
       "      <td>60.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>51.368</td>\n",
       "      <td>21.021</td>\n",
       "      <td>3.043</td>\n",
       "      <td>215.0</td>\n",
       "      <td>0.009624</td>\n",
       "      <td>0.8111</td>\n",
       "      <td>-0.589077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>BUTTER WHIPPED WITH SALT</td>\n",
       "      <td>15.87</td>\n",
       "      <td>717</td>\n",
       "      <td>0.85</td>\n",
       "      <td>81.11</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>...</td>\n",
       "      <td>1.5</td>\n",
       "      <td>60.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>50.489</td>\n",
       "      <td>23.426</td>\n",
       "      <td>3.012</td>\n",
       "      <td>219.0</td>\n",
       "      <td>0.009624</td>\n",
       "      <td>0.8111</td>\n",
       "      <td>-0.589077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>BUTTER OIL ANHYDROUS</td>\n",
       "      <td>0.24</td>\n",
       "      <td>876</td>\n",
       "      <td>0.28</td>\n",
       "      <td>99.48</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>73.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>61.924</td>\n",
       "      <td>28.732</td>\n",
       "      <td>3.694</td>\n",
       "      <td>256.0</td>\n",
       "      <td>0.003170</td>\n",
       "      <td>0.9948</td>\n",
       "      <td>-0.739759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>CHEESE BLUE</td>\n",
       "      <td>42.41</td>\n",
       "      <td>353</td>\n",
       "      <td>21.40</td>\n",
       "      <td>28.74</td>\n",
       "      <td>5.11</td>\n",
       "      <td>2.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>18.669</td>\n",
       "      <td>7.778</td>\n",
       "      <td>0.800</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.242301</td>\n",
       "      <td>0.2874</td>\n",
       "      <td>0.269051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>CHEESE BRICK</td>\n",
       "      <td>41.11</td>\n",
       "      <td>371</td>\n",
       "      <td>23.24</td>\n",
       "      <td>29.68</td>\n",
       "      <td>3.18</td>\n",
       "      <td>2.79</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.51</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>18.764</td>\n",
       "      <td>8.598</td>\n",
       "      <td>0.784</td>\n",
       "      <td>94.0</td>\n",
       "      <td>0.263134</td>\n",
       "      <td>0.2968</td>\n",
       "      <td>0.303668</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   NDB_No                 Shrt_Desc  Water_(g)  Energ_Kcal  Protein_(g)  \\\n",
       "0    1001          BUTTER WITH SALT      15.87         717         0.85   \n",
       "1    1002  BUTTER WHIPPED WITH SALT      15.87         717         0.85   \n",
       "2    1003      BUTTER OIL ANHYDROUS       0.24         876         0.28   \n",
       "3    1004               CHEESE BLUE      42.41         353        21.40   \n",
       "4    1005              CHEESE BRICK      41.11         371        23.24   \n",
       "\n",
       "   Lipid_Tot_(g)  Ash_(g)  Carbohydrt_(g)  Fiber_TD_(g)  Sugar_Tot_(g)  ...  \\\n",
       "0          81.11     2.11            0.06           0.0           0.06  ...   \n",
       "1          81.11     2.11            0.06           0.0           0.06  ...   \n",
       "2          99.48     0.00            0.00           0.0           0.00  ...   \n",
       "3          28.74     5.11            2.34           0.0           0.50  ...   \n",
       "4          29.68     3.18            2.79           0.0           0.51  ...   \n",
       "\n",
       "   Vit_D_mcg  Vit_D_IU  Vit_K_(mcg)  FA_Sat_(g)  FA_Mono_(g)  FA_Poly_(g)  \\\n",
       "0        1.5      60.0          7.0      51.368       21.021        3.043   \n",
       "1        1.5      60.0          7.0      50.489       23.426        3.012   \n",
       "2        1.8      73.0          8.6      61.924       28.732        3.694   \n",
       "3        0.5      21.0          2.4      18.669        7.778        0.800   \n",
       "4        0.5      22.0          2.5      18.764        8.598        0.784   \n",
       "\n",
       "   Cholestrl_(mg)  Normalized_Protein  Normalized_Fat  Norm_Nutr_Index  \n",
       "0           215.0            0.009624          0.8111        -0.589077  \n",
       "1           219.0            0.009624          0.8111        -0.589077  \n",
       "2           256.0            0.003170          0.9948        -0.739759  \n",
       "3            75.0            0.242301          0.2874         0.269051  \n",
       "4            94.0            0.263134          0.2968         0.303668  \n",
       "\n",
       "[5 rows x 39 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# création de la colonne \"Normalized_Protein\" via normalized_protein\n",
    "\n",
    "food_info[\"Normalized_Protein\"] = normalized_protein\n",
    "\n",
    "# création de la colonne \"Normalized_fat\" via normalized_fat\n",
    "\n",
    "food_info[\"Normalized_Fat\"] = normalized_fat\n",
    "\n",
    "food_info.head()\n",
    "# D'origine .head() affiche les 5 premiers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Créer un indice nutritionnel normalisé"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Score = 2 x Normalized_Protein - 0.75 x Normalized_Fat\n",
    "\n",
    "Utiliser les colonnes Normalized_Protein et Normalized_Fat avec cette formule pour créer une nouvelle colonne qu'on nommera Norm_Nutr_Index.\n",
    "\n",
    "Afficher le DataFrame food_info ( Les 3 premieres lignes )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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>NDB_No</th>\n",
       "      <th>Shrt_Desc</th>\n",
       "      <th>Water_(g)</th>\n",
       "      <th>Energ_Kcal</th>\n",
       "      <th>Protein_(g)</th>\n",
       "      <th>Lipid_Tot_(g)</th>\n",
       "      <th>Ash_(g)</th>\n",
       "      <th>Carbohydrt_(g)</th>\n",
       "      <th>Fiber_TD_(g)</th>\n",
       "      <th>Sugar_Tot_(g)</th>\n",
       "      <th>...</th>\n",
       "      <th>Vit_D_mcg</th>\n",
       "      <th>Vit_D_IU</th>\n",
       "      <th>Vit_K_(mcg)</th>\n",
       "      <th>FA_Sat_(g)</th>\n",
       "      <th>FA_Mono_(g)</th>\n",
       "      <th>FA_Poly_(g)</th>\n",
       "      <th>Cholestrl_(mg)</th>\n",
       "      <th>Normalized_Protein</th>\n",
       "      <th>Normalized_Fat</th>\n",
       "      <th>Norm_Nutr_Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>BUTTER WITH SALT</td>\n",
       "      <td>15.87</td>\n",
       "      <td>717</td>\n",
       "      <td>0.85</td>\n",
       "      <td>81.11</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>...</td>\n",
       "      <td>1.5</td>\n",
       "      <td>60.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>51.368</td>\n",
       "      <td>21.021</td>\n",
       "      <td>3.043</td>\n",
       "      <td>215.0</td>\n",
       "      <td>0.009624</td>\n",
       "      <td>0.8111</td>\n",
       "      <td>-0.589077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>BUTTER WHIPPED WITH SALT</td>\n",
       "      <td>15.87</td>\n",
       "      <td>717</td>\n",
       "      <td>0.85</td>\n",
       "      <td>81.11</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>...</td>\n",
       "      <td>1.5</td>\n",
       "      <td>60.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>50.489</td>\n",
       "      <td>23.426</td>\n",
       "      <td>3.012</td>\n",
       "      <td>219.0</td>\n",
       "      <td>0.009624</td>\n",
       "      <td>0.8111</td>\n",
       "      <td>-0.589077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>BUTTER OIL ANHYDROUS</td>\n",
       "      <td>0.24</td>\n",
       "      <td>876</td>\n",
       "      <td>0.28</td>\n",
       "      <td>99.48</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>73.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>61.924</td>\n",
       "      <td>28.732</td>\n",
       "      <td>3.694</td>\n",
       "      <td>256.0</td>\n",
       "      <td>0.003170</td>\n",
       "      <td>0.9948</td>\n",
       "      <td>-0.739759</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   NDB_No                 Shrt_Desc  Water_(g)  Energ_Kcal  Protein_(g)  \\\n",
       "0    1001          BUTTER WITH SALT      15.87         717         0.85   \n",
       "1    1002  BUTTER WHIPPED WITH SALT      15.87         717         0.85   \n",
       "2    1003      BUTTER OIL ANHYDROUS       0.24         876         0.28   \n",
       "\n",
       "   Lipid_Tot_(g)  Ash_(g)  Carbohydrt_(g)  Fiber_TD_(g)  Sugar_Tot_(g)  ...  \\\n",
       "0          81.11     2.11            0.06           0.0           0.06  ...   \n",
       "1          81.11     2.11            0.06           0.0           0.06  ...   \n",
       "2          99.48     0.00            0.00           0.0           0.00  ...   \n",
       "\n",
       "   Vit_D_mcg  Vit_D_IU  Vit_K_(mcg)  FA_Sat_(g)  FA_Mono_(g)  FA_Poly_(g)  \\\n",
       "0        1.5      60.0          7.0      51.368       21.021        3.043   \n",
       "1        1.5      60.0          7.0      50.489       23.426        3.012   \n",
       "2        1.8      73.0          8.6      61.924       28.732        3.694   \n",
       "\n",
       "   Cholestrl_(mg)  Normalized_Protein  Normalized_Fat  Norm_Nutr_Index  \n",
       "0           215.0            0.009624          0.8111        -0.589077  \n",
       "1           219.0            0.009624          0.8111        -0.589077  \n",
       "2           256.0            0.003170          0.9948        -0.739759  \n",
       "\n",
       "[3 rows x 39 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "food_info[\"Norm_Nutr_Index\"] = 2 * food_info[\"Normalized_Protein\"] + (-0.75) * food_info[\"Normalized_Fat\"]\n",
    "food_info.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trier un DataFrame (pratique)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Remplacer le DataFrame food_info en triant par rapport à la colonne Norm_Nutr_Index de façon decroissante (du plus grand au plus petit).\n",
    "\n",
    "- Afficher les 3 premiéres lignes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "food_info.sort_values(\"Norm_Nutr_Index\", inplace=True, ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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>NDB_No</th>\n",
       "      <th>Shrt_Desc</th>\n",
       "      <th>Water_(g)</th>\n",
       "      <th>Energ_Kcal</th>\n",
       "      <th>Protein_(g)</th>\n",
       "      <th>Lipid_Tot_(g)</th>\n",
       "      <th>Ash_(g)</th>\n",
       "      <th>Carbohydrt_(g)</th>\n",
       "      <th>Fiber_TD_(g)</th>\n",
       "      <th>Sugar_Tot_(g)</th>\n",
       "      <th>...</th>\n",
       "      <th>Vit_D_mcg</th>\n",
       "      <th>Vit_D_IU</th>\n",
       "      <th>Vit_K_(mcg)</th>\n",
       "      <th>FA_Sat_(g)</th>\n",
       "      <th>FA_Mono_(g)</th>\n",
       "      <th>FA_Poly_(g)</th>\n",
       "      <th>Cholestrl_(mg)</th>\n",
       "      <th>Normalized_Protein</th>\n",
       "      <th>Normalized_Fat</th>\n",
       "      <th>Norm_Nutr_Index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4991</th>\n",
       "      <td>16423</td>\n",
       "      <td>SOY PROT ISOLATE K TYPE CRUDE PROT BASIS</td>\n",
       "      <td>4.98</td>\n",
       "      <td>321</td>\n",
       "      <td>88.32</td>\n",
       "      <td>0.53</td>\n",
       "      <td>3.58</td>\n",
       "      <td>2.59</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.066</td>\n",
       "      <td>0.101</td>\n",
       "      <td>0.258</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>1.996025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6155</th>\n",
       "      <td>19177</td>\n",
       "      <td>GELATINS DRY PDR UNSWTND</td>\n",
       "      <td>13.00</td>\n",
       "      <td>335</td>\n",
       "      <td>85.60</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.30</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.070</td>\n",
       "      <td>0.060</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.969203</td>\n",
       "      <td>0.0010</td>\n",
       "      <td>1.937656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>1258</td>\n",
       "      <td>EGG WHITE DRIED STABILIZED GLUCOSE RED</td>\n",
       "      <td>6.53</td>\n",
       "      <td>362</td>\n",
       "      <td>84.63</td>\n",
       "      <td>0.48</td>\n",
       "      <td>3.63</td>\n",
       "      <td>4.72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.147</td>\n",
       "      <td>0.173</td>\n",
       "      <td>0.070</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.958220</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>1.912840</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      NDB_No                                 Shrt_Desc  Water_(g)  Energ_Kcal  \\\n",
       "4991   16423  SOY PROT ISOLATE K TYPE CRUDE PROT BASIS       4.98         321   \n",
       "6155   19177                  GELATINS DRY PDR UNSWTND      13.00         335   \n",
       "216     1258    EGG WHITE DRIED STABILIZED GLUCOSE RED       6.53         362   \n",
       "\n",
       "      Protein_(g)  Lipid_Tot_(g)  Ash_(g)  Carbohydrt_(g)  Fiber_TD_(g)  \\\n",
       "4991        88.32           0.53     3.58            2.59           2.0   \n",
       "6155        85.60           0.10     1.30            0.00           0.0   \n",
       "216         84.63           0.48     3.63            4.72           0.0   \n",
       "\n",
       "      Sugar_Tot_(g)  ...  Vit_D_mcg  Vit_D_IU  Vit_K_(mcg)  FA_Sat_(g)  \\\n",
       "4991            0.0  ...        0.0       0.0          0.0       0.066   \n",
       "6155            0.0  ...        0.0       0.0          0.0       0.070   \n",
       "216             0.0  ...        0.0       0.0          0.0       0.147   \n",
       "\n",
       "      FA_Mono_(g)  FA_Poly_(g)  Cholestrl_(mg)  Normalized_Protein  \\\n",
       "4991        0.101        0.258             0.0            1.000000   \n",
       "6155        0.060        0.010             0.0            0.969203   \n",
       "216         0.173        0.070            20.0            0.958220   \n",
       "\n",
       "      Normalized_Fat  Norm_Nutr_Index  \n",
       "4991          0.0053         1.996025  \n",
       "6155          0.0010         1.937656  \n",
       "216           0.0048         1.912840  \n",
       "\n",
       "[3 rows x 39 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "food_info.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trouver les valeurs manquantes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lire le DataSet titanic_survival.csv.\n",
    "\n",
    "Assigner titanic_survival au DataSet titanic_survival.csv\n",
    "\n",
    "Compter le nombre de valeurs dans la colonne \"age\" possédant des valeurs manquantes:\n",
    "\n",
    "Assigner à la variable age la colonne des \"age\" du DataFrame titanic_survival.\n",
    "\n",
    "Utiliser la Series résultante pour sélectionner seulement les élements de la colonne \"age\" qui sont nuls(NaN) et assigner le résultat à la variable age_null.\n",
    "\n",
    "Assigner le nombre de valeur manquantes de age_null à la variale age_null_count (fonction len())\n",
    "\n",
    "-Afficher age_null_count pour voir le nombre de valeurs manquante de la colonne \"age\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10    47.0\n",
      "11    18.0\n",
      "12    24.0\n",
      "13    26.0\n",
      "14    80.0\n",
      "15     NaN\n",
      "16    24.0\n",
      "17    50.0\n",
      "18    32.0\n",
      "19    36.0\n",
      "20    37.0\n",
      "21    47.0\n",
      "22    26.0\n",
      "23    42.0\n",
      "24    29.0\n",
      "25    25.0\n",
      "Name: age, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "titanic_survival = pd.read_csv(\"titanic_survival.csv\")\n",
    "\n",
    "age = titanic_survival[\"age\"]\n",
    "print(age.loc[10:25])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       False\n",
       "1       False\n",
       "2       False\n",
       "3       False\n",
       "4       False\n",
       "        ...  \n",
       "1305     True\n",
       "1306    False\n",
       "1307    False\n",
       "1308    False\n",
       "1309     True\n",
       "Name: age, Length: 1310, dtype: bool"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age_is_null = pd.isnull(age)\n",
    "# Création de la variable age_is_null \n",
    "\n",
    "age_is_null\n",
    "# Nous voila avec une liste de boolens "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15     NaN\n",
       "37     NaN\n",
       "40     NaN\n",
       "46     NaN\n",
       "59     NaN\n",
       "        ..\n",
       "1297   NaN\n",
       "1302   NaN\n",
       "1303   NaN\n",
       "1305   NaN\n",
       "1309   NaN\n",
       "Name: age, Length: 264, dtype: float64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age_null = age[age_is_null]\n",
    "# Nous utilisons notre \"fonction\" age_is_null sur la variable age (colonne \"age\")\n",
    "\n",
    "age_null\n",
    "# Voici la liste des valeurs NaN de la colonne \"age\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "264\n"
     ]
    }
   ],
   "source": [
    "age_null_count = len(age_null)\n",
    "# Utilisation de la fonction len() pour compter les NaN\n",
    "\n",
    "print(age_null_count)\n",
    "# Nous avons donc 264 valeurs Nan dans notre colonne \"age\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calcul de la moyenne du prix (\"fare\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Assigner la moyenne de la colonne \"fare\" à la variable mean_fare et afficher le resultat."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33.29547928134572\n"
     ]
    }
   ],
   "source": [
    "mean_fare = titanic_survival[\"fare\"].mean()\n",
    "\n",
    "print(mean_fare)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculer des statistiques de prix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Créer un dictionnaire vide qu'on nommera fares_by_class.\n",
    "\n",
    "- Créer la liste passenger_classes qui contient les éléments [1, 2, 3].\n",
    "\n",
    "- Utiliser une boucle for pour parcourir la liste passenger_classes:\n",
    "\n",
    "Selectionner juste les lignes de titanic_survival pour lesquelles la colonne pclass est égale à la variable temporaire (l'itérateur) de la boucle for, c'est à dire correspondant au numéro de classe (1, 2 ou 3)\n",
    "\n",
    "Selectionner seulement la colonne \"fare\" pour ce sous-ensemble de lignes (correspondant à la classe)\n",
    "\n",
    "Utiliser la methode Series.mean() pour calculer la moyenne de ce sous-ensemble.\n",
    "\n",
    "Ajouter cette moyenne calculée de la classe au dictionnaire fares_by_class avec comme clé, le numero de la classe (et donc comme valeur la moyenne du prix du billet d'embarquement)\n",
    "\n",
    "- Une fois la boucle achevée, le dictionnaire fares_by_class devrait avoir 1, 2 et 3 comme clés avec en valeur les moyennes correspondantes.\n",
    "\n",
    "Il suffit d'afficher le résultat pour finir."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1: 87.50899164086687, 2: 21.1791963898917, 3: 13.302888700564957}\n"
     ]
    }
   ],
   "source": [
    "fares_by_class = {}\n",
    "# dictionnaire vide\n",
    "\n",
    "passenger_classes = [1, 2, 3]\n",
    "# liste des classes [1, 2, 3]\n",
    "\n",
    "for this_class in passenger_classes:\n",
    "    pclass_rows = titanic_survival[titanic_survival[\"pclass\"] == this_class]\n",
    "    \n",
    "    pclass_fares = pclass_rows[\"fare\"]\n",
    "    fare_for_class = pclass_fares.mean()\n",
    "    \n",
    "    fares_by_class[this_class] = fare_for_class\n",
    "    \n",
    "print(fares_by_class)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Eliminer les valeurs manquantes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Supprimer toutes les lignes de titanic_survival pour lesquelles les colonnes \"age\" ou \"sex\" ont des valeurs manquantes et assigner le resultat à la variable new_titanic_survival.\n",
    "\n",
    "Comparer le nombre de lignes qu'il reste avec l'attribut shape."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# les colonnes \"age\" et \"sex\" ne presenteront aucunes valeurs manquantes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Iloc pour accéder à des lignes (pratique)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nous utiliserons titanic_survival de la pratique precedente.\n",
    "\n",
    "Assigner les 10 premieres lignes de titanic_survival à la variable first_ten_rows.\n",
    "\n",
    "Assigner la 5eme ligne de titanic_survival à la variable row_position_fifth.\n",
    "\n",
    "Assigner la ligne dont l'intitulé d'index est 25 pour titanic_survival à la variable row_index_25."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}