{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0eefb67b-5399-44fa-9c1c-7724ec1c7cd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "import s3fs\n",
    "import warnings\n",
    "from datetime import date, timedelta, datetime\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37977b4e-42e7-4d8e-8b9a-6843292fd128",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import KPI construction functions\n",
    "exec(open('0_KPI_functions.py').read())\n",
    "# exec(open('../0_KPI_functions.py').read())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "cca62d72-f809-41a9-bb06-1be7d6b09307",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['projet-bdc2324-team1/0_Input/Company_10/campaigns_information.csv',\n",
       " 'projet-bdc2324-team1/0_Input/Company_10/customerplus_cleaned.csv',\n",
       " 'projet-bdc2324-team1/0_Input/Company_10/products_purchased_reduced.csv',\n",
       " 'projet-bdc2324-team1/0_Input/Company_10/target_information.csv']"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create filesystem object\n",
    "S3_ENDPOINT_URL = \"https://\" + os.environ[\"AWS_S3_ENDPOINT\"]\n",
    "fs = s3fs.S3FileSystem(client_kwargs={'endpoint_url': S3_ENDPOINT_URL})\n",
    "\n",
    "BUCKET = \"projet-bdc2324-team1/0_Input/Company_10\"\n",
    "fs.ls(BUCKET)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "68fb54f3-8eb3-4cd0-966b-000876912fb5",
   "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>customer_id</th>\n",
       "      <th>street_id</th>\n",
       "      <th>structure_id</th>\n",
       "      <th>mcp_contact_id</th>\n",
       "      <th>fidelity</th>\n",
       "      <th>tenant_id</th>\n",
       "      <th>is_partner</th>\n",
       "      <th>deleted_at</th>\n",
       "      <th>gender</th>\n",
       "      <th>is_email_true</th>\n",
       "      <th>...</th>\n",
       "      <th>max_price</th>\n",
       "      <th>ticket_sum</th>\n",
       "      <th>average_price</th>\n",
       "      <th>average_purchase_delay</th>\n",
       "      <th>average_price_basket</th>\n",
       "      <th>average_ticket_basket</th>\n",
       "      <th>total_price</th>\n",
       "      <th>purchase_count</th>\n",
       "      <th>first_buying_date</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>821538</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>809126</td>\n",
       "      <td>1063</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11005</td>\n",
       "      <td>1063</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>17663</td>\n",
       "      <td>12731</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>38100</td>\n",
       "      <td>12395</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</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",
       "      <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>98789</th>\n",
       "      <td>766266</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181304.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98790</th>\n",
       "      <td>766336</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>178189.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98791</th>\n",
       "      <td>766348</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>178141.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98792</th>\n",
       "      <td>766363</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>176807.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98793</th>\n",
       "      <td>766366</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>176788.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>98794 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       customer_id  street_id  structure_id  mcp_contact_id  fidelity  \\\n",
       "0           821538        139           NaN             NaN         0   \n",
       "1           809126       1063           NaN             NaN         0   \n",
       "2            11005       1063           NaN             NaN         0   \n",
       "3            17663      12731           NaN             NaN         0   \n",
       "4            38100      12395           NaN             NaN         0   \n",
       "...            ...        ...           ...             ...       ...   \n",
       "98789       766266        139           NaN        181304.0         0   \n",
       "98790       766336        139           NaN        178189.0         0   \n",
       "98791       766348        139           NaN        178141.0         0   \n",
       "98792       766363        139           NaN        176807.0         0   \n",
       "98793       766366        139           NaN        176788.0         0   \n",
       "\n",
       "       tenant_id  is_partner  deleted_at  gender  is_email_true  ...  \\\n",
       "0            875       False         NaN       2           True  ...   \n",
       "1            875       False         NaN       2           True  ...   \n",
       "2            875       False         NaN       2          False  ...   \n",
       "3            875       False         NaN       0          False  ...   \n",
       "4            875       False         NaN       0           True  ...   \n",
       "...          ...         ...         ...     ...            ...  ...   \n",
       "98789        875       False         NaN       2           True  ...   \n",
       "98790        875       False         NaN       2           True  ...   \n",
       "98791        875       False         NaN       2           True  ...   \n",
       "98792        875       False         NaN       2           True  ...   \n",
       "98793        875       False         NaN       2           True  ...   \n",
       "\n",
       "       max_price ticket_sum  average_price  average_purchase_delay  \\\n",
       "0            NaN          0            NaN                     NaN   \n",
       "1            NaN          0            NaN                     NaN   \n",
       "2            NaN          0            0.0                     NaN   \n",
       "3            NaN          0            0.0                     NaN   \n",
       "4            NaN          0            0.0                     NaN   \n",
       "...          ...        ...            ...                     ...   \n",
       "98789        NaN          0            NaN                     NaN   \n",
       "98790        NaN          0            NaN                     NaN   \n",
       "98791        NaN          0            NaN                     NaN   \n",
       "98792        NaN          0            NaN                     NaN   \n",
       "98793        NaN          0            NaN                     NaN   \n",
       "\n",
       "       average_price_basket  average_ticket_basket  total_price  \\\n",
       "0                       NaN                    NaN          0.0   \n",
       "1                       NaN                    NaN          0.0   \n",
       "2                       NaN                    NaN          NaN   \n",
       "3                       NaN                    NaN          NaN   \n",
       "4                       NaN                    NaN          NaN   \n",
       "...                     ...                    ...          ...   \n",
       "98789                   NaN                    NaN          0.0   \n",
       "98790                   NaN                    NaN          0.0   \n",
       "98791                   NaN                    NaN          0.0   \n",
       "98792                   NaN                    NaN          0.0   \n",
       "98793                   NaN                    NaN          0.0   \n",
       "\n",
       "       purchase_count  first_buying_date  country  \n",
       "0                   0                NaN      NaN  \n",
       "1                   0                NaN       fr  \n",
       "2                  14                NaN       fr  \n",
       "3                   1                NaN       fr  \n",
       "4                   1                NaN       fr  \n",
       "...               ...                ...      ...  \n",
       "98789               0                NaN      NaN  \n",
       "98790               0                NaN      NaN  \n",
       "98791               0                NaN      NaN  \n",
       "98792               0                NaN      NaN  \n",
       "98793               0                NaN      NaN  \n",
       "\n",
       "[98794 rows x 22 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customerplus_cleaned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "0e1ce56c-2e50-456c-ba97-ed4a699cc8d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "BUCKET = \"projet-bdc2324-team1\"\n",
    "FILE_KEY_S3 = \"0_Input/Company_10/customerplus_cleaned.csv\"\n",
    "FILE_PATH_S3 = BUCKET + \"/\" + FILE_KEY_S3\n",
    "\n",
    "with fs.open(FILE_PATH_S3, mode=\"rb\") as file_in:\n",
    "    df_customerplus_cleaned = pd.read_csv(file_in, sep=\",\")\n",
    " \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "bcdba447-90f7-450c-b4a3-6da656e38493",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_438/3710670046.py:6: FutureWarning: The argument 'date_parser' is deprecated and will be removed in a future version. Please use 'date_format' instead, or read your data in as 'object' dtype and then call 'to_datetime'.\n",
      "  purchases = pd.read_csv(file_in, sep=\",\", parse_dates = ['purchase_date'], date_parser=custom_date_parser)\n"
     ]
    }
   ],
   "source": [
    "BUCKET = \"projet-bdc2324-team1\"\n",
    "FILE_KEY_S3 = \"0_Input/Company_10/products_purchased_reduced.csv\"\n",
    "FILE_PATH_S3 = BUCKET + \"/\" + FILE_KEY_S3\n",
    "\n",
    "with fs.open(FILE_PATH_S3, mode=\"rb\") as file_in:\n",
    "    purchases = pd.read_csv(file_in, sep=\",\", parse_dates = ['purchase_date'], date_parser=custom_date_parser)\n",
    " \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "637aa400-f49a-4d8d-802a-868b241f8a9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "dic_base=['campaigns_information','customerplus_cleaned','products_purchased_reduced','target_information']\n",
    "for nom_base in dic_base:\n",
    "    FILE_PATH_S3_fanta = 'projet-bdc2324-team1/0_Input/Company_10/' + nom_base + '.csv'\n",
    "    with fs.open(FILE_PATH_S3_fanta, mode=\"rb\") as file_in:\n",
    "        globals()[nom_base] = pd.read_csv(file_in, sep=\",\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "e60529b5-986f-4685-91e1-782c2b022e09",
   "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>id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_type_is_import</th>\n",
       "      <th>target_type_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1165098</td>\n",
       "      <td>618562</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1165100</td>\n",
       "      <td>618559</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1165101</td>\n",
       "      <td>618561</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1165102</td>\n",
       "      <td>618560</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1165103</td>\n",
       "      <td>618558</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69253</th>\n",
       "      <td>1698158</td>\n",
       "      <td>18580</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69254</th>\n",
       "      <td>1698159</td>\n",
       "      <td>18569</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69255</th>\n",
       "      <td>1698160</td>\n",
       "      <td>2962</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69256</th>\n",
       "      <td>1698161</td>\n",
       "      <td>3825</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69257</th>\n",
       "      <td>1698162</td>\n",
       "      <td>5731</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>69258 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            id  customer_id           target_name  target_type_is_import  \\\n",
       "0      1165098       618562  Newsletter mensuelle                  False   \n",
       "1      1165100       618559  Newsletter mensuelle                  False   \n",
       "2      1165101       618561  Newsletter mensuelle                  False   \n",
       "3      1165102       618560  Newsletter mensuelle                  False   \n",
       "4      1165103       618558  Newsletter mensuelle                  False   \n",
       "...        ...          ...                   ...                    ...   \n",
       "69253  1698158        18580  Newsletter mensuelle                  False   \n",
       "69254  1698159        18569  Newsletter mensuelle                  False   \n",
       "69255  1698160         2962  Newsletter mensuelle                  False   \n",
       "69256  1698161         3825  Newsletter mensuelle                  False   \n",
       "69257  1698162         5731  Newsletter mensuelle                  False   \n",
       "\n",
       "           target_type_name  \n",
       "0      manual_static_filter  \n",
       "1      manual_static_filter  \n",
       "2      manual_static_filter  \n",
       "3      manual_static_filter  \n",
       "4      manual_static_filter  \n",
       "...                     ...  \n",
       "69253  manual_static_filter  \n",
       "69254  manual_static_filter  \n",
       "69255  manual_static_filter  \n",
       "69256  manual_static_filter  \n",
       "69257  manual_static_filter  \n",
       "\n",
       "[69258 rows x 5 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target_information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "6ece1bb3-5a2d-41f8-be96-eb70697881dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:27: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\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>customer_id</th>\n",
       "      <th>nb_campaigns</th>\n",
       "      <th>nb_campaigns_opened</th>\n",
       "      <th>time_to_open</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>39</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0 days 05:16:38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>41</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0 days 01:12:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>44</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57138</th>\n",
       "      <td>827940</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57139</th>\n",
       "      <td>827941</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57140</th>\n",
       "      <td>827942</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57141</th>\n",
       "      <td>827943</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57142</th>\n",
       "      <td>827944</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>57143 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       customer_id  nb_campaigns  nb_campaigns_opened    time_to_open\n",
       "0               29             4                  NaN             NaT\n",
       "1               37             3                  NaN             NaT\n",
       "2               39             4                  1.0 0 days 05:16:38\n",
       "3               41             4                  1.0 0 days 01:12:29\n",
       "4               44             4                  NaN             NaT\n",
       "...            ...           ...                  ...             ...\n",
       "57138       827940             1                  NaN             NaT\n",
       "57139       827941             1                  NaN             NaT\n",
       "57140       827942             1                  NaN             NaT\n",
       "57141       827943             1                  NaN             NaT\n",
       "57142       827944             1                  NaN             NaT\n",
       "\n",
       "[57143 rows x 4 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "campaigns_kpi_function(campaigns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "8c42f4a3-bdbc-44fe-a873-3192b983410d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# KPI sur le comportement d'achat\n",
    "df_tickets_kpi = tickets_kpi_function(purchases)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "df124880-1e4f-4eaf-b0ef-72bb4f840d45",
   "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>customer_id</th>\n",
       "      <th>nb_tickets</th>\n",
       "      <th>nb_purchases</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>nb_suppliers</th>\n",
       "      <th>vente_internet_max</th>\n",
       "      <th>purchase_date_min</th>\n",
       "      <th>purchase_date_max</th>\n",
       "      <th>time_between_purchase</th>\n",
       "      <th>nb_tickets_internet</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19482</td>\n",
       "      <td>88</td>\n",
       "      <td>29</td>\n",
       "      <td>872.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2643.092500</td>\n",
       "      <td>718.149398</td>\n",
       "      <td>1924.943102</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19484</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>62.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1745.021736</td>\n",
       "      <td>1743.045035</td>\n",
       "      <td>1.976701</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19485</td>\n",
       "      <td>131</td>\n",
       "      <td>21</td>\n",
       "      <td>1878.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2649.044745</td>\n",
       "      <td>85.240845</td>\n",
       "      <td>2563.803900</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19486</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>96.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1944.077604</td>\n",
       "      <td>1742.794225</td>\n",
       "      <td>201.283380</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19487</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>33.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1742.877766</td>\n",
       "      <td>1742.877766</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26100</th>\n",
       "      <td>824877</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-12.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.956111</td>\n",
       "      <td>5.956111</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26101</th>\n",
       "      <td>824878</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.956921</td>\n",
       "      <td>5.956921</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26102</th>\n",
       "      <td>824879</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>-38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.226238</td>\n",
       "      <td>5.226238</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26103</th>\n",
       "      <td>824991</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>-100.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.021539</td>\n",
       "      <td>3.017222</td>\n",
       "      <td>0.004317</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26104</th>\n",
       "      <td>824998</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.072720</td>\n",
       "      <td>0.072720</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>26105 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       customer_id  nb_tickets  nb_purchases  total_amount  nb_suppliers  \\\n",
       "0            19482          88            29         872.0             2   \n",
       "1            19484           3             2          62.0             1   \n",
       "2            19485         131            21        1878.0             2   \n",
       "3            19486          10             4          96.0             1   \n",
       "4            19487           2             1          33.0             1   \n",
       "...            ...         ...           ...           ...           ...   \n",
       "26100       824877           1             1         -12.0             1   \n",
       "26101       824878           1             1          12.0             1   \n",
       "26102       824879           2             1         -38.0             1   \n",
       "26103       824991          14             3        -100.0             1   \n",
       "26104       824998           1             1          25.0             1   \n",
       "\n",
       "       vente_internet_max  purchase_date_min  purchase_date_max  \\\n",
       "0                       1        2643.092500         718.149398   \n",
       "1                       0        1745.021736        1743.045035   \n",
       "2                       1        2649.044745          85.240845   \n",
       "3                       0        1944.077604        1742.794225   \n",
       "4                       0        1742.877766        1742.877766   \n",
       "...                   ...                ...                ...   \n",
       "26100                   0           5.956111           5.956111   \n",
       "26101                   0           5.956921           5.956921   \n",
       "26102                   0           5.226238           5.226238   \n",
       "26103                   0           3.021539           3.017222   \n",
       "26104                   0           0.072720           0.072720   \n",
       "\n",
       "       time_between_purchase  nb_tickets_internet  \n",
       "0                1924.943102                  8.0  \n",
       "1                   1.976701                  0.0  \n",
       "2                2563.803900                 84.0  \n",
       "3                 201.283380                  0.0  \n",
       "4                   0.000000                  0.0  \n",
       "...                      ...                  ...  \n",
       "26100               0.000000                  0.0  \n",
       "26101               0.000000                  0.0  \n",
       "26102               0.000000                  0.0  \n",
       "26103               0.004317                  0.0  \n",
       "26104               0.000000                  0.0  \n",
       "\n",
       "[26105 rows x 10 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tickets_kpi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "4e8c0d75-117f-4400-8d55-b3ae3f43501b",
   "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>customer_id</th>\n",
       "      <th>street_id</th>\n",
       "      <th>structure_id</th>\n",
       "      <th>mcp_contact_id</th>\n",
       "      <th>fidelity</th>\n",
       "      <th>tenant_id</th>\n",
       "      <th>is_partner</th>\n",
       "      <th>deleted_at</th>\n",
       "      <th>gender</th>\n",
       "      <th>is_email_true</th>\n",
       "      <th>...</th>\n",
       "      <th>total_price</th>\n",
       "      <th>purchase_count</th>\n",
       "      <th>first_buying_date</th>\n",
       "      <th>country</th>\n",
       "      <th>gender_label</th>\n",
       "      <th>gender_female</th>\n",
       "      <th>gender_male</th>\n",
       "      <th>gender_other</th>\n",
       "      <th>country_fr</th>\n",
       "      <th>has_tags</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>821538</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>other</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>809126</td>\n",
       "      <td>1063</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "      <td>other</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11005</td>\n",
       "      <td>1063</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "      <td>other</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>17663</td>\n",
       "      <td>12731</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>38100</td>\n",
       "      <td>12395</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</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",
       "      <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>98789</th>\n",
       "      <td>766266</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181304.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>other</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98790</th>\n",
       "      <td>766336</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>178189.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>other</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98791</th>\n",
       "      <td>766348</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>178141.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>other</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98792</th>\n",
       "      <td>766363</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>176807.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>other</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98793</th>\n",
       "      <td>766366</td>\n",
       "      <td>139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>176788.0</td>\n",
       "      <td>0</td>\n",
       "      <td>875</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>other</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>98794 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       customer_id  street_id  structure_id  mcp_contact_id  fidelity  \\\n",
       "0           821538        139           NaN             NaN         0   \n",
       "1           809126       1063           NaN             NaN         0   \n",
       "2            11005       1063           NaN             NaN         0   \n",
       "3            17663      12731           NaN             NaN         0   \n",
       "4            38100      12395           NaN             NaN         0   \n",
       "...            ...        ...           ...             ...       ...   \n",
       "98789       766266        139           NaN        181304.0         0   \n",
       "98790       766336        139           NaN        178189.0         0   \n",
       "98791       766348        139           NaN        178141.0         0   \n",
       "98792       766363        139           NaN        176807.0         0   \n",
       "98793       766366        139           NaN        176788.0         0   \n",
       "\n",
       "       tenant_id  is_partner  deleted_at  gender  is_email_true  ...  \\\n",
       "0            875       False         NaN       2           True  ...   \n",
       "1            875       False         NaN       2           True  ...   \n",
       "2            875       False         NaN       2          False  ...   \n",
       "3            875       False         NaN       0          False  ...   \n",
       "4            875       False         NaN       0           True  ...   \n",
       "...          ...         ...         ...     ...            ...  ...   \n",
       "98789        875       False         NaN       2           True  ...   \n",
       "98790        875       False         NaN       2           True  ...   \n",
       "98791        875       False         NaN       2           True  ...   \n",
       "98792        875       False         NaN       2           True  ...   \n",
       "98793        875       False         NaN       2           True  ...   \n",
       "\n",
       "       total_price purchase_count  first_buying_date  country  gender_label  \\\n",
       "0              0.0              0                NaN      NaN         other   \n",
       "1              0.0              0                NaN       fr         other   \n",
       "2              NaN             14                NaN       fr         other   \n",
       "3              NaN              1                NaN       fr        female   \n",
       "4              NaN              1                NaN       fr        female   \n",
       "...            ...            ...                ...      ...           ...   \n",
       "98789          0.0              0                NaN      NaN         other   \n",
       "98790          0.0              0                NaN      NaN         other   \n",
       "98791          0.0              0                NaN      NaN         other   \n",
       "98792          0.0              0                NaN      NaN         other   \n",
       "98793          0.0              0                NaN      NaN         other   \n",
       "\n",
       "       gender_female  gender_male  gender_other  country_fr  has_tags  \n",
       "0                  0            0             1         NaN         0  \n",
       "1                  0            0             1         1.0         0  \n",
       "2                  0            0             1         1.0         0  \n",
       "3                  1            0             0         1.0         0  \n",
       "4                  1            0             0         1.0         0  \n",
       "...              ...          ...           ...         ...       ...  \n",
       "98789              0            0             1         NaN         0  \n",
       "98790              0            0             1         NaN         0  \n",
       "98791              0            0             1         NaN         0  \n",
       "98792              0            0             1         NaN         0  \n",
       "98793              0            0             1         NaN         0  \n",
       "\n",
       "[98794 rows x 28 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " # KPI sur les données socio-démographiques\n",
    "df_customerplus_clean = customerplus_kpi_function(df_customerplus_cleaned)\n",
    " \n",
    "df_customerplus_clean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "484979cc-d4a4-4d9d-9701-71a4f353a372",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_438/1359829443.py:6: FutureWarning: The argument 'date_parser' is deprecated and will be removed in a future version. Please use 'date_format' instead, or read your data in as 'object' dtype and then call 'to_datetime'.\n",
      "  campaigns = pd.read_csv(file_in, sep=\",\", parse_dates = [\"opened_at\", \"sent_at\", \"delivered_at\"], date_parser=custom_date_parser)\n"
     ]
    }
   ],
   "source": [
    "BUCKET = \"projet-bdc2324-team1\"\n",
    "FILE_KEY_S3 = \"0_Input/Company_10/campaigns_information.csv\"\n",
    "FILE_PATH_S3 = BUCKET + \"/\" + FILE_KEY_S3\n",
    "\n",
    "with fs.open(FILE_PATH_S3, mode=\"rb\") as file_in:\n",
    "    campaigns = pd.read_csv(file_in, sep=\",\", parse_dates = [\"opened_at\", \"sent_at\", \"delivered_at\"], date_parser=custom_date_parser)\n",
    " \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "553ca2e7-ead4-4508-8247-fcc602abd249",
   "metadata": {},
   "outputs": [],
   "source": [
    "BUCKET = \"projet-bdc2324-team1\"\n",
    "FILE_KEY_S3 = \"0_Input/Company_10/target_information.csv\"\n",
    "FILE_PATH_S3 = BUCKET + \"/\" + FILE_KEY_S3\n",
    "\n",
    "with fs.open(FILE_PATH_S3, mode=\"rb\") as file_in:\n",
    "    targets = pd.read_csv(file_in, sep=\",\")\n",
    " \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "17b89ca1-deea-4139-a6c0-7822cc4e7a90",
   "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>id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_type_is_import</th>\n",
       "      <th>target_type_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1165098</td>\n",
       "      <td>618562</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1165100</td>\n",
       "      <td>618559</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1165101</td>\n",
       "      <td>618561</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1165102</td>\n",
       "      <td>618560</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1165103</td>\n",
       "      <td>618558</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69253</th>\n",
       "      <td>1698158</td>\n",
       "      <td>18580</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69254</th>\n",
       "      <td>1698159</td>\n",
       "      <td>18569</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69255</th>\n",
       "      <td>1698160</td>\n",
       "      <td>2962</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69256</th>\n",
       "      <td>1698161</td>\n",
       "      <td>3825</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69257</th>\n",
       "      <td>1698162</td>\n",
       "      <td>5731</td>\n",
       "      <td>Newsletter mensuelle</td>\n",
       "      <td>False</td>\n",
       "      <td>manual_static_filter</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>69258 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            id  customer_id           target_name  target_type_is_import  \\\n",
       "0      1165098       618562  Newsletter mensuelle                  False   \n",
       "1      1165100       618559  Newsletter mensuelle                  False   \n",
       "2      1165101       618561  Newsletter mensuelle                  False   \n",
       "3      1165102       618560  Newsletter mensuelle                  False   \n",
       "4      1165103       618558  Newsletter mensuelle                  False   \n",
       "...        ...          ...                   ...                    ...   \n",
       "69253  1698158        18580  Newsletter mensuelle                  False   \n",
       "69254  1698159        18569  Newsletter mensuelle                  False   \n",
       "69255  1698160         2962  Newsletter mensuelle                  False   \n",
       "69256  1698161         3825  Newsletter mensuelle                  False   \n",
       "69257  1698162         5731  Newsletter mensuelle                  False   \n",
       "\n",
       "           target_type_name  \n",
       "0      manual_static_filter  \n",
       "1      manual_static_filter  \n",
       "2      manual_static_filter  \n",
       "3      manual_static_filter  \n",
       "4      manual_static_filter  \n",
       "...                     ...  \n",
       "69253  manual_static_filter  \n",
       "69254  manual_static_filter  \n",
       "69255  manual_static_filter  \n",
       "69256  manual_static_filter  \n",
       "69257  manual_static_filter  \n",
       "\n",
       "[69258 rows x 5 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "targets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "c90d94ab-cf0e-4d18-9d5e-cb1d22f4d58b",
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "f-string: expecting '}' (1665996669.py, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  Cell \u001b[0;32mIn[40], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m    BUCKET_OUT = f'projet-bdc2324-team1/Generalization/{'musee'}'\u001b[0m\n\u001b[0m                                                         ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m f-string: expecting '}'\n"
     ]
    }
   ],
   "source": [
    "BUCKET_OUT = f'projet-bdc2324-team1/Generalization/{'musee'}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6767ba6-94ef-43f9-8f67-15ecdb41a70b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}