09_graphiques_avances.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e50d5af5-477e-4178-8e14-03f464fc7cb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "62c58b56-7988-4336-aee2-810a3d73d830",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"data.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52dc8d9e-3783-44af-9bf4-55ff4fc919e2",
   "metadata": {},
   "source": [
    "# Ajouter des colonnes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f4a89a16-6f6b-403c-948a-9523c05c055f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(subset=[\"tax\"], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "20ae8a2e-3ab9-4a5b-9cb5-53bbcf3ee6f1",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>email</th>\n",
       "      <th>gender</th>\n",
       "      <th>ip_address</th>\n",
       "      <th>country</th>\n",
       "      <th>price_paid</th>\n",
       "      <th>tax</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>03/17/2021</td>\n",
       "      <td>Erl</td>\n",
       "      <td>Kilminster</td>\n",
       "      <td>ekilminster2@etsy.com</td>\n",
       "      <td>Male</td>\n",
       "      <td>213.8.101.145</td>\n",
       "      <td>United States</td>\n",
       "      <td>$3.73</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>03/19/2021</td>\n",
       "      <td>Grata</td>\n",
       "      <td>Brantl</td>\n",
       "      <td>gbrantl3@umn.edu</td>\n",
       "      <td>Female</td>\n",
       "      <td>5.140.237.101</td>\n",
       "      <td>United States</td>\n",
       "      <td>$3.70</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>03/24/2021</td>\n",
       "      <td>Kanya</td>\n",
       "      <td>Beasant</td>\n",
       "      <td>kbeasant4@jigsy.com</td>\n",
       "      <td>Male</td>\n",
       "      <td>106.252.162.233</td>\n",
       "      <td>Morocco</td>\n",
       "      <td>$9.24</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>03/08/2021</td>\n",
       "      <td>Codi</td>\n",
       "      <td>Feasley</td>\n",
       "      <td>cfeasley7@ed.gov</td>\n",
       "      <td>Male</td>\n",
       "      <td>26.190.191.249</td>\n",
       "      <td>France</td>\n",
       "      <td>$3.01</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>03/09/2021</td>\n",
       "      <td>Waylon</td>\n",
       "      <td>Heersema</td>\n",
       "      <td>wheersema8@tumblr.com</td>\n",
       "      <td>Male</td>\n",
       "      <td>63.242.174.112</td>\n",
       "      <td>Canada</td>\n",
       "      <td>$3.70</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>992</td>\n",
       "      <td>03/07/2021</td>\n",
       "      <td>Elihu</td>\n",
       "      <td>Crush</td>\n",
       "      <td>ecrushrj@berkeley.edu</td>\n",
       "      <td>Male</td>\n",
       "      <td>174.38.173.53</td>\n",
       "      <td>Morocco</td>\n",
       "      <td>$5.05</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>995</td>\n",
       "      <td>03/17/2021</td>\n",
       "      <td>Carolyne</td>\n",
       "      <td>Bruntjen</td>\n",
       "      <td>cbruntjenrm@reference.com</td>\n",
       "      <td>Female</td>\n",
       "      <td>7.29.168.78</td>\n",
       "      <td>France</td>\n",
       "      <td>$5.68</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>997</td>\n",
       "      <td>03/17/2021</td>\n",
       "      <td>Ame</td>\n",
       "      <td>Rastall</td>\n",
       "      <td>arastallro@toplist.cz</td>\n",
       "      <td>Female</td>\n",
       "      <td>188.219.12.109</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$4.59</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>998</td>\n",
       "      <td>03/13/2021</td>\n",
       "      <td>Betty</td>\n",
       "      <td>Stickels</td>\n",
       "      <td>bstickelsrp@cloudflare.com</td>\n",
       "      <td>Male</td>\n",
       "      <td>199.80.60.87</td>\n",
       "      <td>United States</td>\n",
       "      <td>$7.54</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1000</td>\n",
       "      <td>03/23/2021</td>\n",
       "      <td>Rochelle</td>\n",
       "      <td>Pringuer</td>\n",
       "      <td>rpringuerrr@house.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>170.193.249.83</td>\n",
       "      <td>Canada</td>\n",
       "      <td>$8.01</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>654 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id        date first_name   last_name                       email  \\\n",
       "2       3  03/17/2021        Erl  Kilminster       ekilminster2@etsy.com   \n",
       "3       4  03/19/2021      Grata      Brantl            gbrantl3@umn.edu   \n",
       "4       5  03/24/2021      Kanya     Beasant         kbeasant4@jigsy.com   \n",
       "7       8  03/08/2021       Codi     Feasley            cfeasley7@ed.gov   \n",
       "8       9  03/09/2021     Waylon    Heersema       wheersema8@tumblr.com   \n",
       "..    ...         ...        ...         ...                         ...   \n",
       "991   992  03/07/2021      Elihu       Crush       ecrushrj@berkeley.edu   \n",
       "994   995  03/17/2021   Carolyne    Bruntjen   cbruntjenrm@reference.com   \n",
       "996   997  03/17/2021        Ame     Rastall       arastallro@toplist.cz   \n",
       "997   998  03/13/2021      Betty    Stickels  bstickelsrp@cloudflare.com   \n",
       "999  1000  03/23/2021   Rochelle    Pringuer       rpringuerrr@house.gov   \n",
       "\n",
       "     gender       ip_address        country price_paid   tax  \n",
       "2      Male    213.8.101.145  United States      $3.73  20.0  \n",
       "3    Female    5.140.237.101  United States      $3.70  20.0  \n",
       "4      Male  106.252.162.233        Morocco      $9.24  20.0  \n",
       "7      Male   26.190.191.249         France      $3.01  20.0  \n",
       "8      Male   63.242.174.112         Canada      $3.70  20.0  \n",
       "..      ...              ...            ...        ...   ...  \n",
       "991    Male    174.38.173.53        Morocco      $5.05  20.0  \n",
       "994  Female      7.29.168.78         France      $5.68  20.0  \n",
       "996  Female   188.219.12.109            NaN      $4.59  20.0  \n",
       "997    Male     199.80.60.87  United States      $7.54  20.0  \n",
       "999     NaN   170.193.249.83         Canada      $8.01  20.0  \n",
       "\n",
       "[654 rows x 10 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ffc09c83-4884-4f26-b524-438eeba68744",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id              int64\n",
       "date           object\n",
       "first_name     object\n",
       "last_name      object\n",
       "email          object\n",
       "gender         object\n",
       "ip_address     object\n",
       "country        object\n",
       "price_paid    float64\n",
       "tax           float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.price_paid = df.price_paid.apply(lambda x: x.replace(\"$\", \"\"))\n",
    "df.price_paid = df.price_paid.astype(float)\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "45dcbced-3dc8-4c09-ba1f-f8cea34c7418",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"price_total\"] = df[\"price_paid\"] * (1 - df[\"tax\"] / 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6af470d6-f294-49d0-a4fc-3fde15e74f23",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>03/17/2021</td>\n",
       "      <td>Erl</td>\n",
       "      <td>Kilminster</td>\n",
       "      <td>ekilminster2@etsy.com</td>\n",
       "      <td>Male</td>\n",
       "      <td>213.8.101.145</td>\n",
       "      <td>United States</td>\n",
       "      <td>3.73</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.984</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>03/19/2021</td>\n",
       "      <td>Grata</td>\n",
       "      <td>Brantl</td>\n",
       "      <td>gbrantl3@umn.edu</td>\n",
       "      <td>Female</td>\n",
       "      <td>5.140.237.101</td>\n",
       "      <td>United States</td>\n",
       "      <td>3.70</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>03/24/2021</td>\n",
       "      <td>Kanya</td>\n",
       "      <td>Beasant</td>\n",
       "      <td>kbeasant4@jigsy.com</td>\n",
       "      <td>Male</td>\n",
       "      <td>106.252.162.233</td>\n",
       "      <td>Morocco</td>\n",
       "      <td>9.24</td>\n",
       "      <td>20.0</td>\n",
       "      <td>7.392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>03/08/2021</td>\n",
       "      <td>Codi</td>\n",
       "      <td>Feasley</td>\n",
       "      <td>cfeasley7@ed.gov</td>\n",
       "      <td>Male</td>\n",
       "      <td>26.190.191.249</td>\n",
       "      <td>France</td>\n",
       "      <td>3.01</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>03/09/2021</td>\n",
       "      <td>Waylon</td>\n",
       "      <td>Heersema</td>\n",
       "      <td>wheersema8@tumblr.com</td>\n",
       "      <td>Male</td>\n",
       "      <td>63.242.174.112</td>\n",
       "      <td>Canada</td>\n",
       "      <td>3.70</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>992</td>\n",
       "      <td>03/07/2021</td>\n",
       "      <td>Elihu</td>\n",
       "      <td>Crush</td>\n",
       "      <td>ecrushrj@berkeley.edu</td>\n",
       "      <td>Male</td>\n",
       "      <td>174.38.173.53</td>\n",
       "      <td>Morocco</td>\n",
       "      <td>5.05</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4.040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>995</td>\n",
       "      <td>03/17/2021</td>\n",
       "      <td>Carolyne</td>\n",
       "      <td>Bruntjen</td>\n",
       "      <td>cbruntjenrm@reference.com</td>\n",
       "      <td>Female</td>\n",
       "      <td>7.29.168.78</td>\n",
       "      <td>France</td>\n",
       "      <td>5.68</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4.544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>997</td>\n",
       "      <td>03/17/2021</td>\n",
       "      <td>Ame</td>\n",
       "      <td>Rastall</td>\n",
       "      <td>arastallro@toplist.cz</td>\n",
       "      <td>Female</td>\n",
       "      <td>188.219.12.109</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.59</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>998</td>\n",
       "      <td>03/13/2021</td>\n",
       "      <td>Betty</td>\n",
       "      <td>Stickels</td>\n",
       "      <td>bstickelsrp@cloudflare.com</td>\n",
       "      <td>Male</td>\n",
       "      <td>199.80.60.87</td>\n",
       "      <td>United States</td>\n",
       "      <td>7.54</td>\n",
       "      <td>20.0</td>\n",
       "      <td>6.032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1000</td>\n",
       "      <td>03/23/2021</td>\n",
       "      <td>Rochelle</td>\n",
       "      <td>Pringuer</td>\n",
       "      <td>rpringuerrr@house.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>170.193.249.83</td>\n",
       "      <td>Canada</td>\n",
       "      <td>8.01</td>\n",
       "      <td>20.0</td>\n",
       "      <td>6.408</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>654 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id        date first_name   last_name                       email  \\\n",
       "2       3  03/17/2021        Erl  Kilminster       ekilminster2@etsy.com   \n",
       "3       4  03/19/2021      Grata      Brantl            gbrantl3@umn.edu   \n",
       "4       5  03/24/2021      Kanya     Beasant         kbeasant4@jigsy.com   \n",
       "7       8  03/08/2021       Codi     Feasley            cfeasley7@ed.gov   \n",
       "8       9  03/09/2021     Waylon    Heersema       wheersema8@tumblr.com   \n",
       "..    ...         ...        ...         ...                         ...   \n",
       "991   992  03/07/2021      Elihu       Crush       ecrushrj@berkeley.edu   \n",
       "994   995  03/17/2021   Carolyne    Bruntjen   cbruntjenrm@reference.com   \n",
       "996   997  03/17/2021        Ame     Rastall       arastallro@toplist.cz   \n",
       "997   998  03/13/2021      Betty    Stickels  bstickelsrp@cloudflare.com   \n",
       "999  1000  03/23/2021   Rochelle    Pringuer       rpringuerrr@house.gov   \n",
       "\n",
       "     gender       ip_address        country  price_paid   tax  price_total  \n",
       "2      Male    213.8.101.145  United States        3.73  20.0        2.984  \n",
       "3    Female    5.140.237.101  United States        3.70  20.0        2.960  \n",
       "4      Male  106.252.162.233        Morocco        9.24  20.0        7.392  \n",
       "7      Male   26.190.191.249         France        3.01  20.0        2.408  \n",
       "8      Male   63.242.174.112         Canada        3.70  20.0        2.960  \n",
       "..      ...              ...            ...         ...   ...          ...  \n",
       "991    Male    174.38.173.53        Morocco        5.05  20.0        4.040  \n",
       "994  Female      7.29.168.78         France        5.68  20.0        4.544  \n",
       "996  Female   188.219.12.109            NaN        4.59  20.0        3.672  \n",
       "997    Male     199.80.60.87  United States        7.54  20.0        6.032  \n",
       "999     NaN   170.193.249.83         Canada        8.01  20.0        6.408  \n",
       "\n",
       "[654 rows x 11 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d6f76a3e-1f50-449e-b818-ba89ef5b3535",
   "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>date</th>\n",
       "      <th>gender</th>\n",
       "      <th>country</th>\n",
       "      <th>price_paid</th>\n",
       "      <th>tax</th>\n",
       "      <th>price_total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>03/17/2021</td>\n",
       "      <td>Male</td>\n",
       "      <td>United States</td>\n",
       "      <td>3.73</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>03/19/2021</td>\n",
       "      <td>Female</td>\n",
       "      <td>United States</td>\n",
       "      <td>3.70</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>03/24/2021</td>\n",
       "      <td>Male</td>\n",
       "      <td>Morocco</td>\n",
       "      <td>9.24</td>\n",
       "      <td>20.0</td>\n",
       "      <td>7.392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>03/08/2021</td>\n",
       "      <td>Male</td>\n",
       "      <td>France</td>\n",
       "      <td>3.01</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>03/09/2021</td>\n",
       "      <td>Male</td>\n",
       "      <td>Canada</td>\n",
       "      <td>3.70</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>03/07/2021</td>\n",
       "      <td>Male</td>\n",
       "      <td>Morocco</td>\n",
       "      <td>5.05</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4.040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>03/17/2021</td>\n",
       "      <td>Female</td>\n",
       "      <td>France</td>\n",
       "      <td>5.68</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4.544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>03/17/2021</td>\n",
       "      <td>Female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.59</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>03/13/2021</td>\n",
       "      <td>Male</td>\n",
       "      <td>United States</td>\n",
       "      <td>7.54</td>\n",
       "      <td>20.0</td>\n",
       "      <td>6.032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>03/23/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Canada</td>\n",
       "      <td>8.01</td>\n",
       "      <td>20.0</td>\n",
       "      <td>6.408</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>654 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           date  gender        country  price_paid   tax  price_total\n",
       "2    03/17/2021    Male  United States        3.73  20.0        2.984\n",
       "3    03/19/2021  Female  United States        3.70  20.0        2.960\n",
       "4    03/24/2021    Male        Morocco        9.24  20.0        7.392\n",
       "7    03/08/2021    Male         France        3.01  20.0        2.408\n",
       "8    03/09/2021    Male         Canada        3.70  20.0        2.960\n",
       "..          ...     ...            ...         ...   ...          ...\n",
       "991  03/07/2021    Male        Morocco        5.05  20.0        4.040\n",
       "994  03/17/2021  Female         France        5.68  20.0        4.544\n",
       "996  03/17/2021  Female            NaN        4.59  20.0        3.672\n",
       "997  03/13/2021    Male  United States        7.54  20.0        6.032\n",
       "999  03/23/2021     NaN         Canada        8.01  20.0        6.408\n",
       "\n",
       "[654 rows x 6 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop([\"first_name\", \"last_name\", \"email\", \"ip_address\", \"id\"], axis=1, inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "342ac69c-9def-41e3-b65e-f0bb0dc9c373",
   "metadata": {},
   "source": [
    "# Analyser des données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "40c06511-278e-4675-8318-0fd262d9670d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='country'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(\"country\")[\"price_total\"].sum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "fb3093cf-c5d2-4063-a604-455654f2d172",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='country'>"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(\"country\")[\"price_paid\"].sum().plot.bar(rot=45, legend=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "0c208d17-43da-43f6-a5b4-ba0e361a4b01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='gender'>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[\"gender\"].value_counts(normalize=True).plot.pie(legend=True, figsize=(7, 7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "712905ac-1e61-4b51-8857-46b85ae06871",
   "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": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}