{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c4205b5d-e052-4863-a46b-20e4757052a7",
   "metadata": {},
   "source": [
    "# Business Data Challenge - Team 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ae3af8e6-ced8-4994-8877-fa98d4297cc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd3184e7-54a1-4463-af42-5850d9517a41",
   "metadata": {},
   "source": [
    "Configuration de l'accès aux données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b6035982-9ff4-4013-9792-2d50e10db3d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['bdc2324-data/1/1campaign_stats.csv',\n",
       " 'bdc2324-data/1/1campaigns.csv',\n",
       " 'bdc2324-data/1/1categories.csv',\n",
       " 'bdc2324-data/1/1countries.csv',\n",
       " 'bdc2324-data/1/1currencies.csv',\n",
       " 'bdc2324-data/1/1customer_target_mappings.csv',\n",
       " 'bdc2324-data/1/1customersplus.csv',\n",
       " 'bdc2324-data/1/1event_types.csv',\n",
       " 'bdc2324-data/1/1events.csv',\n",
       " 'bdc2324-data/1/1facilities.csv',\n",
       " 'bdc2324-data/1/1link_stats.csv',\n",
       " 'bdc2324-data/1/1pricing_formulas.csv',\n",
       " 'bdc2324-data/1/1product_packs.csv',\n",
       " 'bdc2324-data/1/1products.csv',\n",
       " 'bdc2324-data/1/1products_groups.csv',\n",
       " 'bdc2324-data/1/1purchases.csv',\n",
       " 'bdc2324-data/1/1representation_category_capacities.csv',\n",
       " 'bdc2324-data/1/1representations.csv',\n",
       " 'bdc2324-data/1/1seasons.csv',\n",
       " 'bdc2324-data/1/1structure_tag_mappings.csv',\n",
       " 'bdc2324-data/1/1suppliers.csv',\n",
       " 'bdc2324-data/1/1tags.csv',\n",
       " 'bdc2324-data/1/1target_types.csv',\n",
       " 'bdc2324-data/1/1targets.csv',\n",
       " 'bdc2324-data/1/1tickets.csv',\n",
       " 'bdc2324-data/1/1type_of_categories.csv',\n",
       " 'bdc2324-data/1/1type_of_pricing_formulas.csv',\n",
       " 'bdc2324-data/1/1type_ofs.csv']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "import s3fs\n",
    "# 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 = \"bdc2324-data/1\"\n",
    "fs.ls(BUCKET)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b86c935d-124f-453f-80dd-83ea6770d09c",
   "metadata": {},
   "outputs": [],
   "source": [
    "dic_base=['campaign_stats','campaigns','categories','countries','currencies','customer_target_mappings','customersplus','event_types','events','facilities','link_stats','pricing_formulas','product_packs','products','products_groups','purchases','representation_category_capacities','representations','seasons','structure_tag_mappings','suppliers','tags','target_types','targets','tickets','type_of_categories','type_of_pricing_formulas','type_ofs']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f6d0b27c-0ecd-406b-b042-6c3802dd68fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_447/1008972637.py:5: DtypeWarning: Columns (1) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  globals()[nom_base] = pd.read_csv(file_in, sep=\",\")\n"
     ]
    }
   ],
   "source": [
    "dic_base=['campaign_stats','campaigns','categories','countries','currencies','customer_target_mappings','customersplus','event_types','events','facilities','link_stats','pricing_formulas','product_packs','products','products_groups','purchases','representation_category_capacities','representations','seasons','structure_tag_mappings','suppliers','tags','target_types','targets','tickets','type_of_categories','type_of_pricing_formulas','type_ofs']\n",
    "for nom_base in dic_base:\n",
    "    FILE_PATH_S3_fanta = 'bdc2324-data/1/1' + 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": 5,
   "id": "2a6b5e22-3370-457f-83b7-dd1e13663229",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'bdc2324-data/1/1type_ofs.csv'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FILE_PATH_S3_fanta"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79012186-ea51-4252-843e-36a9bbe3847e",
   "metadata": {},
   "source": [
    "# Analyse exploratoire "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a365f29-4766-47d8-9796-24a5271867b2",
   "metadata": {},
   "source": [
    "## I. Base  type_of_pricing_formulas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcc14f93-2289-44eb-816b-a51049b258df",
   "metadata": {},
   "source": [
    "## Detection des valeur manquantes"
   ]
  },
  {
   "cell_type": "raw",
   "id": "ab2ec4c4-9d38-4aeb-8202-9116df3cdd66",
   "metadata": {},
   "source": [
    "dic_prod_princing=['type_of_pricing_formulas','products_groups','pricing_formulas','product_packs','products']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88759b4a-2633-478d-abce-29abeac376d1",
   "metadata": {},
   "source": [
    "def verifier_donnees_manquantes(base):\n",
    "    donnees_manquantes = base.isna().sum()\n",
    "    print(\"Données manquantes pour la base :\")\n",
    "    print(donnees_manquantes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df3075b4-1490-4cf2-a3fe-c6d4e2144ae3",
   "metadata": {},
   "source": [
    "for nom_base in dic_prod_princing:\n",
    "    verifier_donnees_manquantes(nom_base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e0c67c01-e837-4772-b070-d1be0d895a36",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                    0\n",
       "type_of_id            0\n",
       "pricing_formula_id    0\n",
       "created_at            0\n",
       "updated_at            0\n",
       "identifier            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#detection des Nan d\n",
    "\n",
    "type_of_pricing_formulas.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3eaffaa6-1164-4ee9-a671-8b5eb3df797d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>type_of_id</th>\n",
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       "      <th>updated_at</th>\n",
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       "      <td>127</td>\n",
       "      <td>2021-01-05 11:55:51.226960+01:00</td>\n",
       "      <td>2021-01-05 11:55:51.226960+01:00</td>\n",
       "      <td>cf2918b25e6dcf8c30798ca05c8ec8ed</td>\n",
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       "      <td>2c8ee3f7c1487d792b6c946314e681f2</td>\n",
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       "      <th>2</th>\n",
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       "      <td>1</td>\n",
       "      <td>2937</td>\n",
       "      <td>2021-01-05 11:55:51.240114+01:00</td>\n",
       "      <td>2021-01-05 11:55:51.240114+01:00</td>\n",
       "      <td>44e55c85e4eb59b3c3c01c137a6b25fc</td>\n",
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       "      <td>48</td>\n",
       "      <td>2021-01-05 11:55:51.244638+01:00</td>\n",
       "      <td>2021-01-05 11:55:51.244638+01:00</td>\n",
       "      <td>ee3bb93b7e2217cd86a49d547fedf6c6</td>\n",
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       "      <td>2021-01-05 11:55:51.249409+01:00</td>\n",
       "      <td>2021-01-05 11:55:51.249409+01:00</td>\n",
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       "      <td>564</td>\n",
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       "      <td>2022-02-18 16:15:58.872249+01:00</td>\n",
       "      <td>2022-02-18 16:15:58.872249+01:00</td>\n",
       "      <td>f669824cdca9de9697f07ff3ba365a8d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564</th>\n",
       "      <td>565</td>\n",
       "      <td>4</td>\n",
       "      <td>6607</td>\n",
       "      <td>2022-02-18 16:15:59.231018+01:00</td>\n",
       "      <td>2022-02-18 16:15:59.231018+01:00</td>\n",
       "      <td>6421c8146a598758139153b0e7b921ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565</th>\n",
       "      <td>566</td>\n",
       "      <td>4</td>\n",
       "      <td>6700</td>\n",
       "      <td>2022-02-18 16:15:59.724812+01:00</td>\n",
       "      <td>2022-02-18 16:15:59.724812+01:00</td>\n",
       "      <td>6823f6d4d80b322fbfb8b83545a9f96d</td>\n",
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       "    <tr>\n",
       "      <th>566</th>\n",
       "      <td>567</td>\n",
       "      <td>4</td>\n",
       "      <td>8118</td>\n",
       "      <td>2022-02-18 16:16:00.163381+01:00</td>\n",
       "      <td>2022-02-18 16:16:00.163381+01:00</td>\n",
       "      <td>35cfc12584b4d1b94795d97fd0aa56e8</td>\n",
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       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>569</td>\n",
       "      <td>7</td>\n",
       "      <td>48157</td>\n",
       "      <td>2023-03-13 11:30:29.480161+01:00</td>\n",
       "      <td>2023-03-13 11:30:29.480161+01:00</td>\n",
       "      <td>55863541f33fd229ac9b54d9ec1f4874</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>568 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  type_of_id  pricing_formula_id                        created_at  \\\n",
       "0      1           1                 127  2021-01-05 11:55:51.226960+01:00   \n",
       "1      2           1                2425  2021-01-05 11:55:51.235606+01:00   \n",
       "2      3           1                2937  2021-01-05 11:55:51.240114+01:00   \n",
       "3      4           1                  48  2021-01-05 11:55:51.244638+01:00   \n",
       "4      5           1                   7  2021-01-05 11:55:51.249409+01:00   \n",
       "..   ...         ...                 ...                               ...   \n",
       "563  564           4                6656  2022-02-18 16:15:58.872249+01:00   \n",
       "564  565           4                6607  2022-02-18 16:15:59.231018+01:00   \n",
       "565  566           4                6700  2022-02-18 16:15:59.724812+01:00   \n",
       "566  567           4                8118  2022-02-18 16:16:00.163381+01:00   \n",
       "567  569           7               48157  2023-03-13 11:30:29.480161+01:00   \n",
       "\n",
       "                           updated_at                        identifier  \n",
       "0    2021-01-05 11:55:51.226960+01:00  cf2918b25e6dcf8c30798ca05c8ec8ed  \n",
       "1    2021-01-05 11:55:51.235606+01:00  2c8ee3f7c1487d792b6c946314e681f2  \n",
       "2    2021-01-05 11:55:51.240114+01:00  44e55c85e4eb59b3c3c01c137a6b25fc  \n",
       "3    2021-01-05 11:55:51.244638+01:00  ee3bb93b7e2217cd86a49d547fedf6c6  \n",
       "4    2021-01-05 11:55:51.249409+01:00  ae701668574f1a653d2b21ddfd250620  \n",
       "..                                ...                               ...  \n",
       "563  2022-02-18 16:15:58.872249+01:00  f669824cdca9de9697f07ff3ba365a8d  \n",
       "564  2022-02-18 16:15:59.231018+01:00  6421c8146a598758139153b0e7b921ea  \n",
       "565  2022-02-18 16:15:59.724812+01:00  6823f6d4d80b322fbfb8b83545a9f96d  \n",
       "566  2022-02-18 16:16:00.163381+01:00  35cfc12584b4d1b94795d97fd0aa56e8  \n",
       "567  2023-03-13 11:30:29.480161+01:00  55863541f33fd229ac9b54d9ec1f4874  \n",
       "\n",
       "[568 rows x 6 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type_of_pricing_formulas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "57298669-8d55-40d5-a5aa-4c5df984eec7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                     int64\n",
       "type_of_id             int64\n",
       "pricing_formula_id     int64\n",
       "created_at            object\n",
       "updated_at            object\n",
       "identifier            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#type des variables\n",
    "\n",
    "type_of_pricing_formulas.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c11850cb-8833-44c0-a11d-9695d620a42b",
   "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>type_of_id</th>\n",
       "      <th>pricing_formula_id</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "      <th>identifier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [id, type_of_id, pricing_formula_id, created_at, updated_at, identifier]\n",
       "Index: []"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Identification des doublons\n",
    "type_of_pricing_formulas.loc[type_of_pricing_formulas['id'].duplicated(keep=False),:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a40de03-5e18-4d3d-a0f8-da960c29fad8",
   "metadata": {},
   "source": [
    "## II.products_groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "89909175-6734-4e8e-8632-d6f8ca812388",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                    0\n",
       "percent_price         0\n",
       "max_price             0\n",
       "min_price             0\n",
       "category_id           0\n",
       "pricing_formula_id    0\n",
       "representation_id     0\n",
       "created_at            0\n",
       "updated_at            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#detection des Nan \n",
    "\n",
    "products_groups.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6a187170-96c4-48d2-9568-b270f67e2c27",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                      int64\n",
       "percent_price         float64\n",
       "max_price             float64\n",
       "min_price             float64\n",
       "category_id             int64\n",
       "pricing_formula_id      int64\n",
       "representation_id       int64\n",
       "created_at             object\n",
       "updated_at             object\n",
       "dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#type des variables\n",
    "\n",
    "products_groups.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2fba2cb0-a6a4-43b2-a854-3be07939c28b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>percent_price</th>\n",
       "      <th>max_price</th>\n",
       "      <th>min_price</th>\n",
       "      <th>category_id</th>\n",
       "      <th>pricing_formula_id</th>\n",
       "      <th>representation_id</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [id, percent_price, max_price, min_price, category_id, pricing_formula_id, representation_id, created_at, updated_at]\n",
       "Index: []"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Identification des doublons\n",
    "products_groups.loc[products_groups[['id','pricing_formula_id','representation_id']].duplicated(keep=False),:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5312ac13-8fbd-4c3f-a98a-8c28f079a599",
   "metadata": {},
   "source": [
    "## III.pricing_formulas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3383a773-0817-4b23-84e7-8d5d0c74b179",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "      <th>extra_field</th>\n",
       "      <th>identifier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41909</td>\n",
       "      <td>visite mécènes 1h30</td>\n",
       "      <td>2022-07-08 07:08:26.802266+02:00</td>\n",
       "      <td>2022-07-08 07:08:26.802266+02:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21d4b0043c12b21952b0797d140991a1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>502</td>\n",
       "      <td>entree mucem tp( expo picasso)</td>\n",
       "      <td>2020-09-03 13:43:59.816765+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>223b09e6c3f1f75dbf8df019af97a555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>504</td>\n",
       "      <td>nombre de personnes cinema</td>\n",
       "      <td>2020-09-03 13:43:59.818198+02:00</td>\n",
       "      <td>2021-01-25 19:16:05.187114+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ba33b7b6d225a75d713a356b49c4d915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>117</td>\n",
       "      <td>spectacle tarif e famille tr</td>\n",
       "      <td>2020-09-03 13:21:21.400249+02:00</td>\n",
       "      <td>2023-03-13 11:30:29.525335+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a00b61ad933518856f86e63ca91a5750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1496</td>\n",
       "      <td>billet nb famille mecene 1a</td>\n",
       "      <td>2020-09-03 14:29:33.320952+02:00</td>\n",
       "      <td>2021-01-25 19:23:06.816402+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7f6013803c242253a5ccde80f780984f</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>551</th>\n",
       "      <td>529</td>\n",
       "      <td>billet nb expo gr</td>\n",
       "      <td>2020-09-03 13:43:59.835944+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7d888e42abe101fc8b21dc88948c8b74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>3153</td>\n",
       "      <td>nb pers visite scolaire rep</td>\n",
       "      <td>2020-09-03 16:32:37.068864+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3cf21731c25eee650d5b232ee4780563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553</th>\n",
       "      <td>5847</td>\n",
       "      <td>visite scolaire rep1h00</td>\n",
       "      <td>2021-06-09 18:10:49.742531+02:00</td>\n",
       "      <td>2022-02-18 15:55:03.576236+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a7bb5a6892d55f0d5ee4ce5786ae5fc6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>5840</td>\n",
       "      <td>france billet - entree ts</td>\n",
       "      <td>2021-06-09 18:10:49.737576+02:00</td>\n",
       "      <td>2022-02-18 16:16:00.199543+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4c53016fc65847646f600eff853593e5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555</th>\n",
       "      <td>5863</td>\n",
       "      <td>france billet - entree tp</td>\n",
       "      <td>2021-06-09 18:12:49.269924+02:00</td>\n",
       "      <td>2022-02-18 16:16:00.199543+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90e642c0e1ef6bc9f2bc43089798de00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>556 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id                            name                        created_at  \\\n",
       "0    41909             visite mécènes 1h30  2022-07-08 07:08:26.802266+02:00   \n",
       "1      502  entree mucem tp( expo picasso)  2020-09-03 13:43:59.816765+02:00   \n",
       "2      504      nombre de personnes cinema  2020-09-03 13:43:59.818198+02:00   \n",
       "3      117    spectacle tarif e famille tr  2020-09-03 13:21:21.400249+02:00   \n",
       "4     1496     billet nb famille mecene 1a  2020-09-03 14:29:33.320952+02:00   \n",
       "..     ...                             ...                               ...   \n",
       "551    529               billet nb expo gr  2020-09-03 13:43:59.835944+02:00   \n",
       "552   3153     nb pers visite scolaire rep  2020-09-03 16:32:37.068864+02:00   \n",
       "553   5847         visite scolaire rep1h00  2021-06-09 18:10:49.742531+02:00   \n",
       "554   5840       france billet - entree ts  2021-06-09 18:10:49.737576+02:00   \n",
       "555   5863       france billet - entree tp  2021-06-09 18:12:49.269924+02:00   \n",
       "\n",
       "                           updated_at  extra_field  \\\n",
       "0    2022-07-08 07:08:26.802266+02:00          NaN   \n",
       "1    2022-02-18 15:57:55.792581+01:00          NaN   \n",
       "2    2021-01-25 19:16:05.187114+01:00          NaN   \n",
       "3    2023-03-13 11:30:29.525335+01:00          NaN   \n",
       "4    2021-01-25 19:23:06.816402+01:00          NaN   \n",
       "..                                ...          ...   \n",
       "551  2022-02-18 15:57:55.792581+01:00          NaN   \n",
       "552  2022-02-18 15:57:55.792581+01:00          NaN   \n",
       "553  2022-02-18 15:55:03.576236+01:00          NaN   \n",
       "554  2022-02-18 16:16:00.199543+01:00          NaN   \n",
       "555  2022-02-18 16:16:00.199543+01:00          NaN   \n",
       "\n",
       "                           identifier  \n",
       "0    21d4b0043c12b21952b0797d140991a1  \n",
       "1    223b09e6c3f1f75dbf8df019af97a555  \n",
       "2    ba33b7b6d225a75d713a356b49c4d915  \n",
       "3    a00b61ad933518856f86e63ca91a5750  \n",
       "4    7f6013803c242253a5ccde80f780984f  \n",
       "..                                ...  \n",
       "551  7d888e42abe101fc8b21dc88948c8b74  \n",
       "552  3cf21731c25eee650d5b232ee4780563  \n",
       "553  a7bb5a6892d55f0d5ee4ce5786ae5fc6  \n",
       "554  4c53016fc65847646f600eff853593e5  \n",
       "555  90e642c0e1ef6bc9f2bc43089798de00  \n",
       "\n",
       "[556 rows x 6 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pricing_formulas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d8130c73-6c5f-45b1-93ae-db7679c8ca56",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id             0.0\n",
       "name           0.0\n",
       "created_at     0.0\n",
       "updated_at     0.0\n",
       "extra_field    1.0\n",
       "identifier     0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#detection des Nan \n",
    "\n",
    "pricing_formulas.isna().sum()/pricing_formulas.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "44f1dbfd-c3cf-464b-9877-f37fcc61da92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id               int64\n",
       "name            object\n",
       "created_at      object\n",
       "updated_at      object\n",
       "extra_field    float64\n",
       "identifier      object\n",
       "dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#type des variables\n",
    "\n",
    "pricing_formulas.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6784b41b-da74-4fae-832e-16641ae710c1",
   "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>name</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "      <th>extra_field</th>\n",
       "      <th>identifier</th>\n",
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       "Empty DataFrame\n",
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       "Index: []"
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     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Identification des doublons\n",
    "pricing_formulas.loc[pricing_formulas[['id']].duplicated(keep=False),:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2145b0a4-b73d-4530-8c12-a78b1cf86eae",
   "metadata": {},
   "source": [
    "## IV. product_packs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e36b07a7-4f0b-4711-86a0-12a1d8158eef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id            0.0\n",
       "name          1.0\n",
       "type_of       0.0\n",
       "created_at    0.0\n",
       "updated_at    0.0\n",
       "identifier    0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#detection des Nan \n",
    "\n",
    "product_packs.isna().sum()/product_packs.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8707396a-f86b-476d-a9f9-c39f8de1d02e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id              int64\n",
       "name          float64\n",
       "type_of         int64\n",
       "created_at     object\n",
       "updated_at     object\n",
       "identifier     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#type des variables\n",
    "\n",
    "product_packs.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4b102bd3-924b-43da-8915-be7664c23f97",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\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>name</th>\n",
       "      <th>type_of</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "      <th>identifier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
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       "Empty DataFrame\n",
       "Columns: [id, name, type_of, created_at, updated_at, identifier]\n",
       "Index: []"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Identification des doublons\n",
    "product_packs.loc[product_packs[['id']].duplicated(keep=False),:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfe0c525-896b-4731-b38e-306ff6ea0c65",
   "metadata": {},
   "source": [
    "## V.products"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "968beb24-f70c-4eb6-8b1e-4b04bc7fe9c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                    0.0\n",
       "amount                0.0\n",
       "is_full_price         0.0\n",
       "representation_id     0.0\n",
       "pricing_formula_id    0.0\n",
       "created_at            0.0\n",
       "updated_at            0.0\n",
       "category_id           0.0\n",
       "apply_price           0.0\n",
       "products_group_id     0.0\n",
       "product_pack_id       0.0\n",
       "extra_field           1.0\n",
       "amount_consumption    1.0\n",
       "identifier            0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#detection des Nan \n",
    "\n",
    "products.isna().sum()/products.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "15bc6ac6-67e8-4e2c-9641-7ee8bb2581a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                      int64\n",
       "amount                float64\n",
       "is_full_price            bool\n",
       "representation_id       int64\n",
       "pricing_formula_id      int64\n",
       "created_at             object\n",
       "updated_at             object\n",
       "category_id             int64\n",
       "apply_price           float64\n",
       "products_group_id       int64\n",
       "product_pack_id         int64\n",
       "extra_field           float64\n",
       "amount_consumption    float64\n",
       "identifier             object\n",
       "dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#type des variables\n",
    "\n",
    "products.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7daa4f1a-e429-4daf-a2e1-1e311b487e09",
   "metadata": {},
   "outputs": [],
   "source": [
    "#dic_prod_princing=['type_of_pricing_formulas','products_groups','pricing_formulas','product_packs','products']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "dc12b746-6708-4708-826a-acb5a8e665a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>41909</td>\n",
       "      <td>visite mécènes 1h30</td>\n",
       "      <td>2022-07-08 07:08:26.802266+02:00</td>\n",
       "      <td>2022-07-08 07:08:26.802266+02:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21d4b0043c12b21952b0797d140991a1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>502</td>\n",
       "      <td>entree mucem tp( expo picasso)</td>\n",
       "      <td>2020-09-03 13:43:59.816765+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>223b09e6c3f1f75dbf8df019af97a555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>504</td>\n",
       "      <td>nombre de personnes cinema</td>\n",
       "      <td>2020-09-03 13:43:59.818198+02:00</td>\n",
       "      <td>2021-01-25 19:16:05.187114+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ba33b7b6d225a75d713a356b49c4d915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>117</td>\n",
       "      <td>spectacle tarif e famille tr</td>\n",
       "      <td>2020-09-03 13:21:21.400249+02:00</td>\n",
       "      <td>2023-03-13 11:30:29.525335+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a00b61ad933518856f86e63ca91a5750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1496</td>\n",
       "      <td>billet nb famille mecene 1a</td>\n",
       "      <td>2020-09-03 14:29:33.320952+02:00</td>\n",
       "      <td>2021-01-25 19:23:06.816402+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7f6013803c242253a5ccde80f780984f</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>551</th>\n",
       "      <td>529</td>\n",
       "      <td>billet nb expo gr</td>\n",
       "      <td>2020-09-03 13:43:59.835944+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7d888e42abe101fc8b21dc88948c8b74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>3153</td>\n",
       "      <td>nb pers visite scolaire rep</td>\n",
       "      <td>2020-09-03 16:32:37.068864+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3cf21731c25eee650d5b232ee4780563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553</th>\n",
       "      <td>5847</td>\n",
       "      <td>visite scolaire rep1h00</td>\n",
       "      <td>2021-06-09 18:10:49.742531+02:00</td>\n",
       "      <td>2022-02-18 15:55:03.576236+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a7bb5a6892d55f0d5ee4ce5786ae5fc6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>5840</td>\n",
       "      <td>france billet - entree ts</td>\n",
       "      <td>2021-06-09 18:10:49.737576+02:00</td>\n",
       "      <td>2022-02-18 16:16:00.199543+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4c53016fc65847646f600eff853593e5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555</th>\n",
       "      <td>5863</td>\n",
       "      <td>france billet - entree tp</td>\n",
       "      <td>2021-06-09 18:12:49.269924+02:00</td>\n",
       "      <td>2022-02-18 16:16:00.199543+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90e642c0e1ef6bc9f2bc43089798de00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>556 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id                            name                        created_at  \\\n",
       "0    41909             visite mécènes 1h30  2022-07-08 07:08:26.802266+02:00   \n",
       "1      502  entree mucem tp( expo picasso)  2020-09-03 13:43:59.816765+02:00   \n",
       "2      504      nombre de personnes cinema  2020-09-03 13:43:59.818198+02:00   \n",
       "3      117    spectacle tarif e famille tr  2020-09-03 13:21:21.400249+02:00   \n",
       "4     1496     billet nb famille mecene 1a  2020-09-03 14:29:33.320952+02:00   \n",
       "..     ...                             ...                               ...   \n",
       "551    529               billet nb expo gr  2020-09-03 13:43:59.835944+02:00   \n",
       "552   3153     nb pers visite scolaire rep  2020-09-03 16:32:37.068864+02:00   \n",
       "553   5847         visite scolaire rep1h00  2021-06-09 18:10:49.742531+02:00   \n",
       "554   5840       france billet - entree ts  2021-06-09 18:10:49.737576+02:00   \n",
       "555   5863       france billet - entree tp  2021-06-09 18:12:49.269924+02:00   \n",
       "\n",
       "                           updated_at  extra_field  \\\n",
       "0    2022-07-08 07:08:26.802266+02:00          NaN   \n",
       "1    2022-02-18 15:57:55.792581+01:00          NaN   \n",
       "2    2021-01-25 19:16:05.187114+01:00          NaN   \n",
       "3    2023-03-13 11:30:29.525335+01:00          NaN   \n",
       "4    2021-01-25 19:23:06.816402+01:00          NaN   \n",
       "..                                ...          ...   \n",
       "551  2022-02-18 15:57:55.792581+01:00          NaN   \n",
       "552  2022-02-18 15:57:55.792581+01:00          NaN   \n",
       "553  2022-02-18 15:55:03.576236+01:00          NaN   \n",
       "554  2022-02-18 16:16:00.199543+01:00          NaN   \n",
       "555  2022-02-18 16:16:00.199543+01:00          NaN   \n",
       "\n",
       "                           identifier  \n",
       "0    21d4b0043c12b21952b0797d140991a1  \n",
       "1    223b09e6c3f1f75dbf8df019af97a555  \n",
       "2    ba33b7b6d225a75d713a356b49c4d915  \n",
       "3    a00b61ad933518856f86e63ca91a5750  \n",
       "4    7f6013803c242253a5ccde80f780984f  \n",
       "..                                ...  \n",
       "551  7d888e42abe101fc8b21dc88948c8b74  \n",
       "552  3cf21731c25eee650d5b232ee4780563  \n",
       "553  a7bb5a6892d55f0d5ee4ce5786ae5fc6  \n",
       "554  4c53016fc65847646f600eff853593e5  \n",
       "555  90e642c0e1ef6bc9f2bc43089798de00  \n",
       "\n",
       "[556 rows x 6 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pricing_formulas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46aad10f-8530-410e-872b-bb253c553a46",
   "metadata": {},
   "source": [
    "# jointure entre les bases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a4c3edd1-6d58-4c57-b3e4-0ef3529f6b8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#dic_prod_princing=['type_of_pricing_formulas','products_groups','pricing_formulas','product_packs','products']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "eac537e1-bbad-45bc-a85c-12b675da1088",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Merge1 entre products et pricing_formulas\n",
    "base1=products.merge(pricing_formulas, how='left', left_on= 'pricing_formula_id', right_on= 'id',  suffixes = (\"_products\", \"_pricing_formula\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "7dd0bdae-c1c5-44ba-a446-42b28def2343",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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_products</th>\n",
       "      <th>amount</th>\n",
       "      <th>is_full_price</th>\n",
       "      <th>representation_id</th>\n",
       "      <th>pricing_formula_id</th>\n",
       "      <th>created_at_products</th>\n",
       "      <th>updated_at_products</th>\n",
       "      <th>category_id</th>\n",
       "      <th>apply_price</th>\n",
       "      <th>products_group_id</th>\n",
       "      <th>product_pack_id</th>\n",
       "      <th>extra_field_products</th>\n",
       "      <th>amount_consumption</th>\n",
       "      <th>identifier_products</th>\n",
       "      <th>id_pricing_formula</th>\n",
       "      <th>name</th>\n",
       "      <th>created_at_pricing_formula</th>\n",
       "      <th>updated_at_pricing_formula</th>\n",
       "      <th>extra_field_pricing_formula</th>\n",
       "      <th>identifier_pricing_formula</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10682</td>\n",
       "      <td>9.0</td>\n",
       "      <td>False</td>\n",
       "      <td>914</td>\n",
       "      <td>114</td>\n",
       "      <td>2020-09-03 14:09:43.119798+02:00</td>\n",
       "      <td>2020-09-03 14:09:43.119798+02:00</td>\n",
       "      <td>41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10655</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35c88f2db8a63d7474e46eb8ca9260e7</td>\n",
       "      <td>114</td>\n",
       "      <td>visite guidée indiv tr</td>\n",
       "      <td>2020-09-03 13:21:21.397923+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>039003ae0b0cd2df183786804b713470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>478</td>\n",
       "      <td>9.5</td>\n",
       "      <td>False</td>\n",
       "      <td>273</td>\n",
       "      <td>131</td>\n",
       "      <td>2020-09-03 13:21:22.711773+02:00</td>\n",
       "      <td>2020-09-03 13:21:22.711773+02:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>471</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8a179671ab198e570e6a104c4451379f</td>\n",
       "      <td>131</td>\n",
       "      <td>billet mucem tp - picasso</td>\n",
       "      <td>2020-09-03 13:21:21.410521+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>916c92362b8e7767715bc966de43e32b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20873</td>\n",
       "      <td>11.5</td>\n",
       "      <td>False</td>\n",
       "      <td>275</td>\n",
       "      <td>137</td>\n",
       "      <td>2020-09-03 14:46:33.589030+02:00</td>\n",
       "      <td>2020-09-03 14:46:33.589030+02:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20825</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ee83779ce29e67ad251e40234b426d6a</td>\n",
       "      <td>137</td>\n",
       "      <td>billet mucem tp - pic. + guide</td>\n",
       "      <td>2020-09-03 13:21:21.414922+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91dd2ee46f5f2d78af989019ebd60a60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>157142</td>\n",
       "      <td>8.0</td>\n",
       "      <td>False</td>\n",
       "      <td>82519</td>\n",
       "      <td>9</td>\n",
       "      <td>2022-01-28 19:29:23.525722+01:00</td>\n",
       "      <td>2022-01-28 19:29:23.525722+01:00</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>156773</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d865383579314b791aa4bcf3fb418f17</td>\n",
       "      <td>9</td>\n",
       "      <td>billet mucem ts</td>\n",
       "      <td>2020-09-03 13:11:23.997074+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37532348a1f1ef1cb916c55ebaf8345c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1341</td>\n",
       "      <td>8.5</td>\n",
       "      <td>False</td>\n",
       "      <td>9</td>\n",
       "      <td>93</td>\n",
       "      <td>2020-09-03 13:29:30.773089+02:00</td>\n",
       "      <td>2020-09-03 13:29:30.773089+02:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1175</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f1c4689bc47dee6f60b56d74b593dd46</td>\n",
       "      <td>93</td>\n",
       "      <td>billet mucem tr + guide</td>\n",
       "      <td>2020-09-03 13:21:21.382586+02:00</td>\n",
       "      <td>2022-02-18 15:57:55.792581+01:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>722a8610e4391c27f2ec6f1224b42b3d</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id_products  amount  is_full_price  representation_id  pricing_formula_id  \\\n",
       "0        10682     9.0          False                914                 114   \n",
       "1          478     9.5          False                273                 131   \n",
       "2        20873    11.5          False                275                 137   \n",
       "3       157142     8.0          False              82519                   9   \n",
       "4         1341     8.5          False                  9                  93   \n",
       "\n",
       "                created_at_products               updated_at_products  \\\n",
       "0  2020-09-03 14:09:43.119798+02:00  2020-09-03 14:09:43.119798+02:00   \n",
       "1  2020-09-03 13:21:22.711773+02:00  2020-09-03 13:21:22.711773+02:00   \n",
       "2  2020-09-03 14:46:33.589030+02:00  2020-09-03 14:46:33.589030+02:00   \n",
       "3  2022-01-28 19:29:23.525722+01:00  2022-01-28 19:29:23.525722+01:00   \n",
       "4  2020-09-03 13:29:30.773089+02:00  2020-09-03 13:29:30.773089+02:00   \n",
       "\n",
       "   category_id  apply_price  products_group_id  product_pack_id  \\\n",
       "0           41          0.0              10655                1   \n",
       "1            1          0.0                471                1   \n",
       "2            1          0.0              20825                1   \n",
       "3            5          0.0             156773                1   \n",
       "4            1          0.0               1175                1   \n",
       "\n",
       "   extra_field_products  amount_consumption               identifier_products  \\\n",
       "0                   NaN                 NaN  35c88f2db8a63d7474e46eb8ca9260e7   \n",
       "1                   NaN                 NaN  8a179671ab198e570e6a104c4451379f   \n",
       "2                   NaN                 NaN  ee83779ce29e67ad251e40234b426d6a   \n",
       "3                   NaN                 NaN  d865383579314b791aa4bcf3fb418f17   \n",
       "4                   NaN                 NaN  f1c4689bc47dee6f60b56d74b593dd46   \n",
       "\n",
       "   id_pricing_formula                            name  \\\n",
       "0                 114          visite guidée indiv tr   \n",
       "1                 131       billet mucem tp - picasso   \n",
       "2                 137  billet mucem tp - pic. + guide   \n",
       "3                   9                 billet mucem ts   \n",
       "4                  93         billet mucem tr + guide   \n",
       "\n",
       "         created_at_pricing_formula        updated_at_pricing_formula  \\\n",
       "0  2020-09-03 13:21:21.397923+02:00  2022-02-18 15:57:55.792581+01:00   \n",
       "1  2020-09-03 13:21:21.410521+02:00  2022-02-18 15:57:55.792581+01:00   \n",
       "2  2020-09-03 13:21:21.414922+02:00  2022-02-18 15:57:55.792581+01:00   \n",
       "3  2020-09-03 13:11:23.997074+02:00  2022-02-18 15:57:55.792581+01:00   \n",
       "4  2020-09-03 13:21:21.382586+02:00  2022-02-18 15:57:55.792581+01:00   \n",
       "\n",
       "   extra_field_pricing_formula        identifier_pricing_formula  \n",
       "0                          NaN  039003ae0b0cd2df183786804b713470  \n",
       "1                          NaN  916c92362b8e7767715bc966de43e32b  \n",
       "2                          NaN  91dd2ee46f5f2d78af989019ebd60a60  \n",
       "3                          NaN  37532348a1f1ef1cb916c55ebaf8345c  \n",
       "4                          NaN  722a8610e4391c27f2ec6f1224b42b3d  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "base1.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "d8ef07cf-29a3-40fb-a3d7-bf32a729c053",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                    0\n",
       "percent_price         0\n",
       "max_price             0\n",
       "min_price             0\n",
       "category_id           0\n",
       "pricing_formula_id    0\n",
       "representation_id     0\n",
       "created_at            0\n",
       "updated_at            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products_groups.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "75be3a30-3114-432d-87d6-697533c3c871",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Merge2 entre base1 et products_groups\n",
    "base2=base1.merge(products_groups, how='left', left_on= 'id_pricing_formula', right_on= 'id',  suffixes = (\"_merge2\", \"_product_group\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "34a169c6-07a8-4ac3-a9e1-d7e7461f7310",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Merge3 entre base2 et type_of_pricing_formulas\n",
    "base3=base2.merge(type_of_pricing_formulas, how='left', left_on= 'id_pricing_formula', right_on= 'pricing_formula_id',  suffixes = (\"_merge3\", \"_type_of_pricing_f\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "508a8082-da34-4d2f-bfa9-9ca7703c3fda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                    0\n",
       "type_of_id            0\n",
       "pricing_formula_id    0\n",
       "created_at            0\n",
       "updated_at            0\n",
       "identifier            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type_of_pricing_formulas.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "0e255d11-57eb-47ca-afd3-31f59b8d8822",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                        0\n",
       "amount                    0\n",
       "is_full_price             0\n",
       "representation_id         0\n",
       "pricing_formula_id        0\n",
       "created_at                0\n",
       "updated_at                0\n",
       "category_id               0\n",
       "apply_price               0\n",
       "products_group_id         0\n",
       "product_pack_id           0\n",
       "extra_field           94803\n",
       "amount_consumption    94803\n",
       "identifier                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "3f034e65-1b33-4908-b7e6-60660ef251c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id            0\n",
       "name          1\n",
       "type_of       0\n",
       "created_at    0\n",
       "updated_at    0\n",
       "identifier    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "product_packs.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "f44f40d2-5304-4931-b7e6-fcc06b2657b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Merge4 entre base3 et type_of_pricing_formulas\n",
    "base4=base3.merge(product_packs, how='left', left_on= 'product_pack_id', right_on= 'id',  suffixes = (\"_merge4\", \"_product_pack\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "a28772c3-7bc1-46b4-acc8-1388dc60ec98",
   "metadata": {},
   "outputs": [
    {
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       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   id_products  amount  is_full_price  representation_id_merge2  \\\n",
       "0        10682     9.0          False                       914   \n",
       "1          478     9.5          False                       273   \n",
       "2        20873    11.5          False                       275   \n",
       "3       157142     8.0          False                     82519   \n",
       "4         1341     8.5          False                         9   \n",
       "\n",
       "   pricing_formula_id_merge2               created_at_products  \\\n",
       "0                        114  2020-09-03 14:09:43.119798+02:00   \n",
       "1                        131  2020-09-03 13:21:22.711773+02:00   \n",
       "2                        137  2020-09-03 14:46:33.589030+02:00   \n",
       "3                          9  2022-01-28 19:29:23.525722+01:00   \n",
       "4                         93  2020-09-03 13:29:30.773089+02:00   \n",
       "\n",
       "                updated_at_products  category_id_merge2  apply_price  \\\n",
       "0  2020-09-03 14:09:43.119798+02:00                  41          0.0   \n",
       "1  2020-09-03 13:21:22.711773+02:00                   1          0.0   \n",
       "2  2020-09-03 14:46:33.589030+02:00                   1          0.0   \n",
       "3  2022-01-28 19:29:23.525722+01:00                   5          0.0   \n",
       "4  2020-09-03 13:29:30.773089+02:00                   1          0.0   \n",
       "\n",
       "   products_group_id  ...  pricing_formula_id  \\\n",
       "0              10655  ...               114.0   \n",
       "1                471  ...               131.0   \n",
       "2              20825  ...               137.0   \n",
       "3             156773  ...                 9.0   \n",
       "4               1175  ...                93.0   \n",
       "\n",
       "       created_at_type_of_pricing_f      updated_at_type_of_pricing_f  \\\n",
       "0  2021-02-15 17:02:27.395376+01:00  2021-02-15 17:02:27.395376+01:00   \n",
       "1  2021-02-05 11:52:05.923905+01:00  2021-02-05 11:52:05.923905+01:00   \n",
       "2  2021-02-05 11:52:05.939898+01:00  2021-02-05 11:52:05.939898+01:00   \n",
       "3  2021-02-05 11:52:06.107939+01:00  2021-02-05 11:52:06.107939+01:00   \n",
       "4  2021-02-05 11:52:06.004162+01:00  2021-02-05 11:52:06.004162+01:00   \n",
       "\n",
       "                  identifier_merge4  id name_product_pack type_of  \\\n",
       "0  3706121eb9f43b635bef1433c06f679c   1               NaN       0   \n",
       "1  0aceb248607671792298436004b95275   1               NaN       0   \n",
       "2  93002d4637331edd81ffc28b6e8e89c0   1               NaN       0   \n",
       "3  7d0b25bdfff9f366da8be820608c8191   1               NaN       0   \n",
       "4  1dbb0795e8f47cb75ba7cdb08c06be5f   1               NaN       0   \n",
       "\n",
       "                         created_at                        updated_at  \\\n",
       "0  2020-09-03 13:11:24.501197+02:00  2020-09-03 13:11:24.501197+02:00   \n",
       "1  2020-09-03 13:11:24.501197+02:00  2020-09-03 13:11:24.501197+02:00   \n",
       "2  2020-09-03 13:11:24.501197+02:00  2020-09-03 13:11:24.501197+02:00   \n",
       "3  2020-09-03 13:11:24.501197+02:00  2020-09-03 13:11:24.501197+02:00   \n",
       "4  2020-09-03 13:11:24.501197+02:00  2020-09-03 13:11:24.501197+02:00   \n",
       "\n",
       "            identifier_product_pack  \n",
       "0  a764b4bf13a360c7ac2a35ec4ca96c95  \n",
       "1  a764b4bf13a360c7ac2a35ec4ca96c95  \n",
       "2  a764b4bf13a360c7ac2a35ec4ca96c95  \n",
       "3  a764b4bf13a360c7ac2a35ec4ca96c95  \n",
       "4  a764b4bf13a360c7ac2a35ec4ca96c95  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "base4.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "03442997-806f-4285-a139-3bad46bb4522",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d22a0d75-53c5-4b54-9060-c9e7c307fb13",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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