wtj_scrapping_clean.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Les librairies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium import webdriver\n",
    "from selenium.webdriver.chrome.service import Service\n",
    "from selenium.webdriver.common.by import By\n",
    "from selenium.webdriver.common.keys import Keys\n",
    "from selenium.webdriver.support.ui import WebDriverWait\n",
    "from selenium.webdriver.support import expected_conditions as EC\n",
    "import time\n",
    "import random\n",
    "from datetime import date\n",
    "from datetime import datetime\n",
    "\n",
    "import pandas as pd\n",
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import json\n",
    "import re\n",
    "\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mes fonctions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "metadata": {},
   "outputs": [],
   "source": [
    "############## Mes fonctions ####################################\n",
    "\n",
    "### ajouter un delay\n",
    "def random_delay():\n",
    "    time.sleep(random.uniform(2, 5))\n",
    "\n",
    "\n",
    "### enlever les baslises html\n",
    "def remove_html_tags(text_col):\n",
    "    if text_col is None:\n",
    "        return None\n",
    "    else:\n",
    "        clean = re.compile('<.*?>')\n",
    "        return re.sub(clean,\"\", text_col)\n",
    "    \n",
    "\n",
    "### convertir l'année de création en année\n",
    "def convert_year_to_date(value):\n",
    "    try:\n",
    "        # Convertir la valeur en int, puis en string et enfin en datetime avec le format %Y\n",
    "        year_str = str(int(value))\n",
    "        return pd.to_datetime(year_str, format='%Y').strftime('%Y')\n",
    "    except:                                                                       # Je retourne la valeur originale si ce n'est pas une date\n",
    "      return value\n",
    "\n",
    "\n",
    "### changer le format de la date de publication %Y-%m-%d\n",
    "def convert_publication_date(value):\n",
    "    try:\n",
    "        # Convertir la valeur en int, puis en string et enfin en datetime avec le format %Y\n",
    "        return pd.to_datetime(value).strftime('%Y-%m-%d')\n",
    "    except:                                                                       # Je retourne la valeur originale si ce n'est pas une date\n",
    "      return value\n",
    "\n",
    "\n",
    "### remplacer les catégories de niveau d'expérience\n",
    "def experience_replace(experience):\n",
    "    lower_exp = experience.lower()\n",
    "    small_exp = lower_exp.replace(\"_\", \" \")\n",
    "    return(small_exp)\n",
    "\n",
    "# ### décompacter les tools et les skills\n",
    "# # note : j'enregistre les tools et les skills dans une même liste que je vais ensuite mettre dans une colonne en appelant la fonction jtools\n",
    "# # puis je droperai la colonne des skills qui reprendra la même liste en doublon\n",
    "\n",
    "# skills = []                                            # je crée un liste pour stocker mes outils et mes skills\n",
    "# def jtools_extractor(tools_list):\n",
    "                                     \n",
    "#     if isinstance(tools_list, list):                   # je vérifie que tools_list est une liste\n",
    "#         for dicos in tools_list:                       # je parcours chaque dictionnaire dans la liste des outils\n",
    "#             for key, tool in dicos.items():             # dans le duo key/value de mes items de chaque dico\n",
    "#                 if key == \"name\":                       # si la clé est = à name\n",
    "#                     skills.append(dicos[\"name\"])          # je stocke l'outil dans la liste\n",
    "#             if skills:  # je vérifie si des outils ont été ajoutées à la liste\n",
    "#                 return skills\n",
    "#         else:\n",
    "#             return None  # je retourne None si aucun outil n'a été trouvé\n",
    "\n",
    "\n",
    "# ### décompacter les skills\n",
    "# def jskills_extractor(skills_list):\n",
    "#                                             # je crée une liste pour stocker les compétences\n",
    "#     if isinstance(skills_list, list):                   # je vérifie que skills_list est une liste\n",
    "#         for dictos in skills_list:                      # je parcours chaque dictionnaire dans la liste des compétences\n",
    "#             if 'name' in dictos:                        # je vérifie que la clé 'name' existe dans le dictionnaire\n",
    "#                 value = dictos['name']\n",
    "#                 if 'fr' in value:                       # je vérifie que la clé 'fr' existe dans le sous-dictionnaire 'name'\n",
    "#                     skills.append(value['fr'])          # je stocke la compétence dans la liste\n",
    "#             if skills:                                  # je vérifie si des compétences ont été ajoutées à la liste\n",
    "#                 return skills\n",
    "#         else:\n",
    "#             return None                                 # je retourne None si aucune compétence en français n'a été trouvée\n",
    "#     else:\n",
    "#         return None                                     # je retourne None si skills_list n'est pas une liste\n",
    "\n",
    "def extract_competences(row):\n",
    "    skills_col = 'job.skills'                            # je définis les colonnes sur lesquelles je vais passer ma fonction\n",
    "    tools_col = 'job.tools'                              # directement dans la fonction pour pouvoir la passer sur les 2\n",
    "    competences = []                                     # j'initialise la liste où je vais enregistrer le tout\n",
    "    \n",
    "    # Extraire les outils\n",
    "    tools_list = row[tools_col]\n",
    "    if isinstance(tools_list, list):                           # je vérifie que tools_list est une liste\n",
    "        for dicos in tools_list:                               # je parcours chaque dictionnaire dans la liste des outils\n",
    "            for key, tool in dicos.items():                    # dans le duo key/value de mes items de chaque dico\n",
    "                if key == \"name\":                              # si la clé est = à name\n",
    "                    competences.append(dicos[\"name\"])          # je stocke l'outil dans la liste\n",
    "    \n",
    "    # Extraire les compétences\n",
    "    skills_list = row[skills_col]\n",
    "    if isinstance(skills_list, list):                           # je vérifie que skills_list est une liste\n",
    "        for dictos in skills_list:                              # je parcours chaque dictionnaire dans la liste des compétences\n",
    "            if 'name' in dictos:                        # je vérifie que la clé 'name' existe dans le dictionnaire\n",
    "                value = dictos['name']\n",
    "                if 'fr' in value:                       # je vérifie que la clé 'fr' existe dans le sous-dictionnaire 'name'\n",
    "                    competences.append(value['fr'])          # je stocke la compétence dans la liste\n",
    "    \n",
    "    return competences if competences else None         # je vérifie si des compétences ont été ajoutées à la liste\n",
    "    \n",
    "### décompacter les urls des annonces\n",
    "def jurls_extractor(urls_list):\n",
    "    if isinstance(urls_list, list):                        # je vérifie que urls_list est une liste\n",
    "        for dics in urls_list:                             # je parcours chaque dictionnaire dans la liste\n",
    "            if isinstance(dics, dict) and 'href' in dics:  # je vérifie que dics est un dictionnaire et contient 'href'\n",
    "                return dics['href']                        # je retourne l'URL\n",
    "    return None                                            # Retourne None si aucun URL n'a été trouvée\n",
    "\n",
    "### décompacter les secteurs\n",
    "def sector_extractor(sectors_list):\n",
    "    sectors = []                                      # je crée un liste pour stocker mes outils\n",
    "    if isinstance(sectors_list, list):                   # je vérifie que tools_list est une liste\n",
    "        for dictos in sectors_list:                       # je parcours chaque dictionnaire dans la liste des outils\n",
    "            for key, sector in dictos.items():             # dans le duo key/value de mes items de chaque dico\n",
    "                if key == \"name\" or key == \"parent_name\":                       # si la clé est = à name\n",
    "                    sectors.append(dictos[\"name\", \"parent_name\"])          # je stocke l'outil dans la liste\n",
    "            if sectors:  # je vérifie si des outils ont été ajoutées à la liste\n",
    "                return sectors\n",
    "        else:\n",
    "            return None  # je retourne None si aucun outil n'a été trouvé\n",
    "\n",
    "### récupérer ce qui est obligatoire pour la candidature\n",
    "# def appli_mandatory_extractor(mandatory_list):\n",
    "#     applications = []                                           # je crée un liste pour stocker mes éléments mandatory\n",
    "#     if isinstance(mandatory_list, list):                        # je vérifie que skills_list est une liste\n",
    "#         for dicts in mandatory_list:                            # je vais chercher chaque dico contenu dans cette liste\n",
    "#             for key, value in dicts.items():                    # dans le duo key/value de mes items de chaque dico\n",
    "#                 if value == \"mandatory\":                        # si une value est = à mandatory\n",
    "#                     applications.append(dicts[\"name\"])          # alors je stocke chaque clé correspondante à name\n",
    "#             if applications:  # je vérifie si des outils ont été ajoutées à la liste\n",
    "#                 return applications\n",
    "#         else:\n",
    "#             return None  # je retourne None si aucun outil n'a été trouvé\n",
    "#     return(applications) \n",
    "\n",
    "### Remplacer les noms anglais de CDI/CDD\n",
    "types_contrats = {'full_time': 'CDI', 'temporary': 'CDD'}\n",
    "\n",
    "# get est une méthode de dict. elle va chercher la clé passée en argument de la fonction\n",
    "# si pas égal alors retourne la clé elle-même (d'où le double contrat)\n",
    "def contract_corrector(contrat):\n",
    "    return types_contrats.get(contrat, contrat)                 \n",
    "\n",
    "\n",
    "### Récupérer les départements\n",
    "def dpt_extractor(zipcode):\n",
    "    departement = re.search(r\"\\A\\d{2}\", zipcode)                # 2 {2}    premiers \\A    chiffres \\d - le r permet de ne pas prendre \\ pour un échappement\n",
    "    return departement.group(0) if departement else None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Procèdure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Aller sur la page de résultats avec selenium\n",
    "2. Récupérer les URL pour aller de page en page\n",
    "3. Faire une fonction pour aller récupérer les URL de chaque annonce sur chaque page\n",
    "4. Couper les URL en relatif puis les reconcatener pour les passer dans l'API\n",
    "5. Itérer pour requêter l'API avec chaque URL récupérée sur chaque page de résultats\n",
    "6. Transformer en dataframe, décompacter et dropper ce qui doit l'être\n",
    "7. Exporter en CSV avant l'EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Récupération des URL des pages et des jobs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Je commence par lancer le code pour récupérer les pages de résultats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "J'ai 34 pages\n",
      "['https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=1', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=2', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=3', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=4', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=5', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=6', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=7', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=8', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=9', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=10', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=11', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=12', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=13', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=14', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=15', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=16', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=17', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=18', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=19', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=20', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=21', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=22', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=23', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=24', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=25', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=26', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=27', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=28', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=29', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=30', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=31', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=32', 'https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=33']\n",
      "['https://www.welcometothejungle.com/fr/companies/esri/jobs/esri-france-data-scientist-specialise-analyse-spatiale-et-geomarketing-f-h_meudon?q=4143f6f511597ce85a131a249d7dce4f&o=60953789-64cb-4951-a2f6-ba1a20858ed1', 'https://www.welcometothejungle.com/fr/companies/sport-heroes-group/jobs/senior-data-analyst-head-of-data_paris?q=4143f6f511597ce85a131a249d7dce4f&o=dcb9d6c5-bb31-46aa-8c35-6e9f0168b3e2', 'https://www.welcometothejungle.com/fr/companies/carrefour/jobs/data-analyst-f-h_evry_CARRE_NPVOZeo?q=4143f6f511597ce85a131a249d7dce4f&o=ee9b39cd-deef-40d5-988b-57748c7c8132', 'https://www.welcometothejungle.com/fr/companies/hublo/jobs/senior-data-analyst-f-h-n_paris_HUBLO_bR85090?q=4143f6f511597ce85a131a249d7dce4f&o=0b5d40e8-64f9-4643-969b-752d0fd2582c', 'https://www.welcometothejungle.com/fr/companies/toucan-toco/jobs/data-analyst-engineer-revenue-operations_paris?q=4143f6f511597ce85a131a249d7dce4f&o=acf940dd-2e9c-4ef2-935b-30c2caf6b34f', 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      "['https://www.welcometothejungle.com/fr/companies/datascientest/jobs/data-analyst-bi-h-f-cdi_puteaux_DATAS_omkDNwM?q=753614a977f31063630fe7b13a7d1b49&o=cc84ecde-c01b-42a2-b15f-24aedf5d5a3c', 'https://www.welcometothejungle.com/fr/companies/grant-thornton/jobs/consultant-data-analytics-public-banque-neuilly-h-f_neuilly-sur-seine_GT_d8KYaJk?q=753614a977f31063630fe7b13a7d1b49&o=996d2fc1-67b8-4d2d-ab9f-4ce584a48d33', 'https://www.welcometothejungle.com/fr/companies/thales/jobs/data-manager-projets-et-ingenierie-h-f_velizy-villacoublay?q=753614a977f31063630fe7b13a7d1b49&o=7d44d4ad-a7a4-41da-800c-846db5c15c85', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/data-analyst-f-h-cdi_malakoff?q=753614a977f31063630fe7b13a7d1b49&o=a80f9927-da5b-4e53-887f-750c274dec67', 'https://www.welcometothejungle.com/fr/companies/free/jobs/data-analyst-esg-h-f_paris-8e-arrondissement?q=753614a977f31063630fe7b13a7d1b49&o=cccb9f19-695f-4000-a2a8-cd483fde4973', 'https://www.welcometothejungle.com/fr/companies/stride-up/jobs/data-tracking-specialist_paris?q=753614a977f31063630fe7b13a7d1b49&o=61f5c54e-f6bc-4819-bad9-4c201c312004', 'https://www.welcometothejungle.com/fr/companies/thelio/jobs/consultant-transformation-data?q=753614a977f31063630fe7b13a7d1b49&o=b1a139bf-4ceb-4133-938f-e3520507fd4f', 'https://www.welcometothejungle.com/fr/companies/ekkiden/jobs/data-analyst-h-f_paris?q=753614a977f31063630fe7b13a7d1b49&o=654c8535-c1e9-4d82-9d42-27c13e4711e0', 'https://www.welcometothejungle.com/fr/companies/betclic/jobs/senior-gaming-data-analyst-h-f_bordeaux?q=753614a977f31063630fe7b13a7d1b49&o=e3ca3399-9d84-4119-9522-1c8ee7c36b44', 'https://www.welcometothejungle.com/fr/companies/betclic/jobs/gaming-data-analyst-h-f_bordeaux_BG_9jx6XW1?q=753614a977f31063630fe7b13a7d1b49&o=30e1bab9-9797-4be0-8489-2965717adbe5', 'https://www.welcometothejungle.com/fr/companies/ey/jobs/consultant-experimente-manager-en-data-analyst-bi-secteur-financier-h-f_paris_EY_9wGMlP0?q=753614a977f31063630fe7b13a7d1b49&o=e6518f8e-47af-4de4-a5db-df102aaf6c9c', 'https://www.welcometothejungle.com/fr/companies/stockly/jobs/data-product-owner-cdi-paris_paris?q=753614a977f31063630fe7b13a7d1b49&o=f5a8ed00-2843-4cb4-8b36-2bf1302eb5f5', 'https://www.welcometothejungle.com/fr/companies/ey/jobs/consultant-senior-manager-en-data-consulting-secteur-financier-h-f_paris_EY_JDLN378?q=753614a977f31063630fe7b13a7d1b49&o=addc94bf-e0b6-4784-8f43-97ec3291f766', 'https://www.welcometothejungle.com/fr/companies/lelynx-fr/jobs/data-analyst-senior-h-f-x_paris?q=753614a977f31063630fe7b13a7d1b49&o=1a80715d-c8c1-4d5d-9a9b-f69e372c073b', 'https://www.welcometothejungle.com/fr/companies/leasecom/jobs/data-analyst-h-f_paris_LEASE_P0Vk1A2?q=753614a977f31063630fe7b13a7d1b49&o=594649ff-1d7e-4137-8846-0464f0c75691', 'https://www.welcometothejungle.com/fr/companies/leasecom/jobs/data-analyst-h-f_paris_LEASE_kGj883z?q=753614a977f31063630fe7b13a7d1b49&o=8aabac1a-b092-4d9b-b126-ce47525e6273', 'https://www.welcometothejungle.com/fr/companies/foxintelligence/jobs/quality-data-analyst_paris?q=753614a977f31063630fe7b13a7d1b49&o=38777919-68ef-4357-9b2f-e8ac19569ffd', 'https://www.welcometothejungle.com/fr/companies/foxintelligence/jobs/lead-data-analyst_paris?q=753614a977f31063630fe7b13a7d1b49&o=dce4cd73-a888-4cd6-89be-e24ef8d4f364', 'https://www.welcometothejungle.com/fr/companies/adone/jobs/consultant-senior-data-bi-h-f_paris_AC_bNz65g0?q=753614a977f31063630fe7b13a7d1b49&o=823e76d1-9e76-4b00-9bfc-c499f1c7c0ee', 'https://www.welcometothejungle.com/fr/companies/wigroup/jobs/consutlant-senior-data-analyst_paris?q=753614a977f31063630fe7b13a7d1b49&o=357a262d-64b0-488a-b9f8-81cf752456db', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/business-data-analyst_puteaux_AXA_08JMYkl?q=753614a977f31063630fe7b13a7d1b49&o=4f797d11-b914-4863-892e-75af4592091d', 'https://www.welcometothejungle.com/fr/companies/vo2-group/jobs/vo2-data-data-analyst-dataiku_paris?q=753614a977f31063630fe7b13a7d1b49&o=6e2e2b8b-b9e1-476a-a284-85e736d92bd5', 'https://www.welcometothejungle.com/fr/companies/vo2-group/jobs/vo2-data-data-project-manager_paris?q=753614a977f31063630fe7b13a7d1b49&o=f2e1304c-6100-4f26-9838-01b70acdad12', 'https://www.welcometothejungle.com/fr/companies/dailymotion/jobs/data-product-manager-analytics-all-genders_paris?q=753614a977f31063630fe7b13a7d1b49&o=b49628b1-0e09-4d60-8c2a-c02d1f14e057', 'https://www.welcometothejungle.com/fr/companies/setec/jobs/bim-et-data-manager-confirme-h-f_paris_SETEC_DjeG4PN?q=753614a977f31063630fe7b13a7d1b49&o=3197cbde-ea15-4447-ad2c-50235138c109', 'https://www.welcometothejungle.com/fr/companies/allianz/jobs/data-officer-h-f_puteaux?q=753614a977f31063630fe7b13a7d1b49&o=755468e7-f1e8-4427-af88-2bede27025ba', 'https://www.welcometothejungle.com/fr/companies/setec-batiment/jobs/bim-et-data-manager-confirme-h-f_paris_SB_eoYd2w7?q=753614a977f31063630fe7b13a7d1b49&o=b938ae7d-4d02-4a0e-a324-420eaf378181']\n",
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'https://www.welcometothejungle.com/fr/companies/groupe-micropole/jobs/consultant-data-quality-f-h_nantes?q=67de8d45e3e227088aa6ac399f26d723&o=f1d3b0c3-37bc-48bd-919c-ab2b1f154cf1', 'https://www.welcometothejungle.com/fr/companies/foodcheri/jobs/lead-data-scientist_paris?q=67de8d45e3e227088aa6ac399f26d723&o=ff793833-4ef8-4497-9978-863b2c71356b', 'https://www.welcometothejungle.com/fr/companies/wigroup/jobs/data-product-manager_paris?q=67de8d45e3e227088aa6ac399f26d723&o=c2e6c807-682a-4824-8da5-970679040078', 'https://www.welcometothejungle.com/fr/companies/qonto/jobs/data-analyst-team-lead-finance_paris?q=67de8d45e3e227088aa6ac399f26d723&o=27fea736-7dd3-4b0d-aacc-bc8a13edeb54']\n",
      "['https://www.welcometothejungle.com/fr/companies/quadratic-fr/jobs/data-viz-analyst-senior-h-f-cdi-paris_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=ccfd49ee-4b3c-49cb-bbee-8a9365e9acf0', 'https://www.welcometothejungle.com/fr/companies/younited/jobs/data-analyst_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=2a8e4eab-d996-419a-a967-0c80e7d62298', 'https://www.welcometothejungle.com/fr/companies/unique-heritage-media/jobs/data-analyst_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=65e5dc54-68b2-49e6-be7d-927476fd993e', 'https://www.welcometothejungle.com/fr/companies/publicis-france-1/jobs/manager-data-analyst-h-f_paris_PF_qozdyYj?q=6e01e8fb6cc442886f1104a3a1af2b29&o=a8385961-d120-4eac-9baa-0535d5feb5f0', 'https://www.welcometothejungle.com/fr/companies/publicis-sapient/jobs/manager-data-analyst-h-f_paris_PS_wJVVP0D?q=6e01e8fb6cc442886f1104a3a1af2b29&o=ad2f11b0-fb71-411d-b264-8720f52ebc57', 'https://www.welcometothejungle.com/fr/companies/groupe-etam/jobs/data-analyst-undiz-cdi-h-f_clichy?q=6e01e8fb6cc442886f1104a3a1af2b29&o=7dd69f22-8a70-4cd6-a95d-36ea00f701e9', 'https://www.welcometothejungle.com/fr/companies/groupe-etam/jobs/data-value-manager-cdi-h-f_clichy?q=6e01e8fb6cc442886f1104a3a1af2b29&o=16481c09-861f-4680-9604-108e8f93ee93', 'https://www.welcometothejungle.com/fr/companies/sancare/jobs/data-steward_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=95553cd8-5c3c-4669-adfd-f4942d400e9a', 'https://www.welcometothejungle.com/fr/companies/vestiaire-collective/jobs/senior-data-product-analyst_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=b40dabd1-0ca9-44be-aa9f-7b227ac7720a', 'https://www.welcometothejungle.com/fr/companies/ioda/jobs/consultant-data-analyst-experimente_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=09a1ba99-d5a1-4f2b-974e-64accee8a1ab', 'https://www.welcometothejungle.com/fr/companies/saegus/jobs/manager-senior-manager-smart-data_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=fba803f9-b028-4fcb-a317-cd7165a29582', 'https://www.welcometothejungle.com/fr/companies/fichorga/jobs/data-manager-dba-h-f_templemars?q=6e01e8fb6cc442886f1104a3a1af2b29&o=78330193-d209-41f1-a96e-63ca03afd122', 'https://www.welcometothejungle.com/fr/companies/health-data-hub/jobs/data-product-owner-h-f_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=21135e19-9f99-4180-ae56-ca645cfeff11', 'https://www.welcometothejungle.com/fr/companies/skiils/jobs/data-analyst-expert-tableau-h-f_suresnes?q=6e01e8fb6cc442886f1104a3a1af2b29&o=69a8018f-4624-468a-b551-3884ece81088', 'https://www.welcometothejungle.com/fr/companies/skiils/jobs/data-analyst-retail_suresnes?q=6e01e8fb6cc442886f1104a3a1af2b29&o=1508655a-4a9b-48b5-92f4-0e044b56fcf2', 'https://www.welcometothejungle.com/fr/companies/oresys/jobs/consultant-data_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=90b38f1e-0bcb-4967-a56a-ccacf40c97a0', 'https://www.welcometothejungle.com/fr/companies/evoteo/jobs/data-analyst-confirme-h-f-lyon_lyon?q=6e01e8fb6cc442886f1104a3a1af2b29&o=eb3a0bbc-af0e-4d3b-a5f6-a28a661a8201', 'https://www.welcometothejungle.com/fr/companies/kanbios/jobs/consultant-digital-manager-data-senior-data-manager_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=2aaa5888-3b86-404d-bc59-01bb38537216', 'https://www.welcometothejungle.com/fr/companies/groupm/jobs/global-data-tech-lead-wavemaker-f-h_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=0a154055-071e-4063-8df6-39e83a890614', 'https://www.welcometothejungle.com/fr/companies/getaround/jobs/data-analyst_paris_GED_OygqaL5?q=6e01e8fb6cc442886f1104a3a1af2b29&o=2927d4a9-064b-465f-82bc-ff45c86d2d93', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/senior-data-analyst-people-f-m-d_croix?q=6e01e8fb6cc442886f1104a3a1af2b29&o=a1db10c3-78a6-4c55-84cb-468494dda6e7', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/senior-data-analyst-people-f-m-d_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=d63bd70b-3e46-4217-86a5-473490e144dc', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/data-product-manager-people-f-m-d_paris?q=6e01e8fb6cc442886f1104a3a1af2b29&o=11962763-02c0-42af-a6ed-762de30f7278', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/data-product-manager-people-f-m-d_croix?q=6e01e8fb6cc442886f1104a3a1af2b29&o=3b3690a5-8e8e-4b5a-bcdf-042e8643e91d']\n",
      "['https://www.welcometothejungle.com/fr/companies/extia/jobs/data-analyst-h-f_lille_EXTIA_Wkk1ym0?q=11c460bb4c84adbbf8152fbba4b8e309&o=26fec8da-027f-4a4e-9531-2fa90ded98fd', 'https://www.welcometothejungle.com/fr/companies/groupe-vyv/jobs/data-analyst-etudes-marketing-h-f_rennes_GV_Wap59GA?q=11c460bb4c84adbbf8152fbba4b8e309&o=54186845-ec84-4ea3-a18c-b0f1b3a8ad00', 'https://www.welcometothejungle.com/fr/companies/capgemini/jobs/ingenieur-data-manager-pau_pau_CAPGE_GbQYy3z?q=11c460bb4c84adbbf8152fbba4b8e309&o=5dc7601a-6bb6-4d78-8391-59d281f037d8', 'https://www.welcometothejungle.com/fr/companies/octopus-energy/jobs/data-analyst-h-f_paris?q=11c460bb4c84adbbf8152fbba4b8e309&o=284b5ff7-d708-44d8-a9ce-583e1cf77d39', 'https://www.welcometothejungle.com/fr/companies/boursorama/jobs/data-analyst-acquisition-clients-h-f_boulogne-billancourt?q=11c460bb4c84adbbf8152fbba4b8e309&o=0193e07c-7e70-40f4-8ec2-be72dc5094e9', 'https://www.welcometothejungle.com/fr/companies/boursorama/jobs/data-analyst-service-clients_boulogne-billancourt?q=11c460bb4c84adbbf8152fbba4b8e309&o=d8a6dcd8-8c84-4426-88a5-1d40f2513ed7', 'https://www.welcometothejungle.com/fr/companies/hermes/jobs/cdi-data-domain-owner-h-f_pantin?q=11c460bb4c84adbbf8152fbba4b8e309&o=48bb6087-e077-4a0f-bf78-da336b90cda2', 'https://www.welcometothejungle.com/fr/companies/ricardo-france/jobs/head-of-data-services_valbonne?q=11c460bb4c84adbbf8152fbba4b8e309&o=d46f29ad-ff50-4bda-bc00-9233d082d305', 'https://www.welcometothejungle.com/fr/companies/orano/jobs/analyste-process-data-management-f-h_bagnols-sur-ceze_ORANO_Y9pO3K1?q=11c460bb4c84adbbf8152fbba4b8e309&o=306cc24b-cdde-457f-975c-f923c96ec669', 'https://www.welcometothejungle.com/fr/companies/trax/jobs/lead-data-h-f_paris?q=11c460bb4c84adbbf8152fbba4b8e309&o=650ad621-a86f-4fd1-88d6-6e2a1d99314a', 'https://www.welcometothejungle.com/fr/companies/keyrus/jobs/data-analyst-h-f-nb_aix-en-provence?q=11c460bb4c84adbbf8152fbba4b8e309&o=da141244-397b-4c98-869c-961fd27bb4fa', 'https://www.welcometothejungle.com/fr/companies/cenova/jobs/data-analyst-lille_marcq-en-baroeul?q=11c460bb4c84adbbf8152fbba4b8e309&o=e9114981-1bc0-4db2-9791-d5fe1d76b7fd', 'https://www.welcometothejungle.com/fr/companies/cenova/jobs/data-steward-lille_marcq-en-baroeul?q=11c460bb4c84adbbf8152fbba4b8e309&o=4eb323a7-c39e-4737-86a1-65ae20e94803', 'https://www.welcometothejungle.com/fr/companies/fairly-made/jobs/senior-data-analyst_paris?q=11c460bb4c84adbbf8152fbba4b8e309&o=419fd280-09e5-48a7-9410-540f89ef959e', 'https://www.welcometothejungle.com/fr/companies/ey/jobs/consultant-debutant-data-analyst-en-cdi-paris-septembre-2024-f-h-fy25_paris_EY_MmpARpe?q=11c460bb4c84adbbf8152fbba4b8e309&o=c87647e7-c44d-4131-b912-3759d06367e2', 'https://www.welcometothejungle.com/fr/companies/treezor/jobs/data-analyst-h-f_paris?q=11c460bb4c84adbbf8152fbba4b8e309&o=6b421893-c729-4ae3-b810-2e784a656f98', 'https://www.welcometothejungle.com/fr/companies/harry-hope/jobs/data-analyst-h-f_nancy_HH_D98Oqk8?q=11c460bb4c84adbbf8152fbba4b8e309&o=8262dd37-bc24-456a-a0d6-e29ad5729fe9', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/data-analyst-junior-f-h_suresnes_AXA_OPq26db?q=11c460bb4c84adbbf8152fbba4b8e309&o=e299596e-7b7d-4465-bca5-f4557a23ddea', 'https://www.welcometothejungle.com/fr/companies/octo-technology/jobs/consultant-data-geek-confirme-senior-a-toulouse-f-h-n_toulouse?q=11c460bb4c84adbbf8152fbba4b8e309&o=7cd62551-8bc0-4fe6-814f-297dce4bcb4c', 'https://www.welcometothejungle.com/fr/companies/lelynx-fr/jobs/data-analyst-scientist_paris?q=11c460bb4c84adbbf8152fbba4b8e309&o=60046a4d-c94d-467a-9814-e68ca2be0639', 'https://www.welcometothejungle.com/fr/companies/teale/jobs/data-analyst_paris_TEALE_aNLd9Ko?q=11c460bb4c84adbbf8152fbba4b8e309&o=07d36305-3f80-43fc-a450-d368a90e7a57', 'https://www.welcometothejungle.com/fr/companies/azira/jobs/business-data-analyst_paris?q=11c460bb4c84adbbf8152fbba4b8e309&o=61350d21-38bb-473d-af2b-b6525742864d', 'https://www.welcometothejungle.com/fr/companies/wewyse/jobs/data-analyst_paris_WEWYS_awa6O5O?q=11c460bb4c84adbbf8152fbba4b8e309&o=b97fe6c6-79a1-4bdb-ba69-e49b79166ac1', 'https://www.welcometothejungle.com/fr/companies/bial-x/jobs/data-analyst-power-bi?q=11c460bb4c84adbbf8152fbba4b8e309&o=6435d9fc-f9a5-44e3-b3b6-29fa8827448c', 'https://www.welcometothejungle.com/fr/companies/inoweeno/jobs/data-scientist_nantes?q=11c460bb4c84adbbf8152fbba4b8e309&o=7a40a217-46a7-4279-8d2a-44cc621d9ca2', 'https://www.welcometothejungle.com/fr/companies/hsbc/jobs/data-et-analytics-h-f_courbevoie?q=11c460bb4c84adbbf8152fbba4b8e309&o=eff1ce84-17be-4859-9741-211a40dea708', 'https://www.welcometothejungle.com/fr/companies/blablacar/jobs/confirmed-data-analyst-blablacar-daily_paris?q=11c460bb4c84adbbf8152fbba4b8e309&o=ca1864bd-3e3c-436d-8a95-4c3f08b2bf08']\n",
      "['https://www.welcometothejungle.com/fr/companies/stago/jobs/data-analyst-data-scientist-h-f_gennevilliers_STAGO_6KoyNwq?q=5c5802c3b1f498d199cc51fb1e58edbd&o=f1553bbc-3576-42be-8b3f-8e9e16fd4297', 'https://www.welcometothejungle.com/fr/companies/francetvpub/jobs/data-analyst-yield-numerique_boulogne-billancourt?q=5c5802c3b1f498d199cc51fb1e58edbd&o=5fe79064-37fa-4c38-8dce-469ee0351222', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/data-privacy-analyst-f-h_paris?q=5c5802c3b1f498d199cc51fb1e58edbd&o=fe4f163b-370b-4b19-b825-0c9ff6786ad3', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/data-strategic-analyst-cdd_paris?q=5c5802c3b1f498d199cc51fb1e58edbd&o=bfbdb94f-9ce5-4928-8265-049f9ff0c02c', 'https://www.welcometothejungle.com/fr/companies/orange-1/jobs/data-analyste-powerbi-f-h_villeneuve-d-ascq?q=5c5802c3b1f498d199cc51fb1e58edbd&o=d3dee9cd-f06e-4931-a6e0-8fae1e100977', 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      "['https://www.welcometothejungle.com/fr/companies/square-management/jobs/manager-expert-data-gouvernance-f-h_neuilly-sur-seine_SM_lMpWLMX?q=436e4b9a68cdf410f9bd8113605497fd&o=46d4e5fa-0132-47bf-9b68-ac9174d96148', 'https://www.welcometothejungle.com/fr/companies/jakala/jobs/data-digital-product-owner-senior-consultant-paris_paris?q=436e4b9a68cdf410f9bd8113605497fd&o=bba7668f-945e-4baa-8cf8-faf065b2542c', 'https://www.welcometothejungle.com/fr/companies/safran-aircraft-engines/jobs/data-steward-engineering-mro-f-h_evry?q=436e4b9a68cdf410f9bd8113605497fd&o=2ed32bd4-22b9-4d60-8a8e-a328bf83c2d8', 'https://www.welcometothejungle.com/fr/companies/le-wagon/jobs/data-product-manager-content_paris?q=436e4b9a68cdf410f9bd8113605497fd&o=840e0119-d7c0-48c3-9445-a90685e5f078', 'https://www.welcometothejungle.com/fr/companies/skiils/jobs/product-owner-data-h-f?q=436e4b9a68cdf410f9bd8113605497fd&o=2f8cef43-4468-4c33-a06e-3ebcb6b9805a', 'https://www.welcometothejungle.com/fr/companies/hove/jobs/data-analyst-senior-h-f_paris?q=436e4b9a68cdf410f9bd8113605497fd&o=9f5af8b4-7db7-4f21-ae13-a8991c7f52a0', 'https://www.welcometothejungle.com/fr/companies/bial-x/jobs/data-analyst-confirme-qliksense?q=436e4b9a68cdf410f9bd8113605497fd&o=3ac8c31e-59d8-4ac3-8a16-3eadded35cf1', 'https://www.welcometothejungle.com/fr/companies/ividata-group/jobs/clinical-data-manager-sas-programmer-f-h_levallois-perret?q=436e4b9a68cdf410f9bd8113605497fd&o=9a99e68b-93ad-4102-b317-b905a8d58188', 'https://www.welcometothejungle.com/fr/companies/skiils/jobs/data-analyst-expert-tableau-h-f_suresnes_SKIIL_z7bmWN3?q=436e4b9a68cdf410f9bd8113605497fd&o=8b73bf3a-d6af-4934-b886-f0308196ed1c', 'https://www.welcometothejungle.com/fr/companies/exalt/jobs/data-analyst_lille?q=436e4b9a68cdf410f9bd8113605497fd&o=0ac4b66b-29df-4a4c-99d7-21f8e038ba49', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/senior-market-data-analyst_puteaux?q=436e4b9a68cdf410f9bd8113605497fd&o=45df4362-19a0-4cd6-8063-779b0b53ac4b', 'https://www.welcometothejungle.com/fr/companies/cgr-comptoir-general-de-robinetterie/jobs/data-analyst-manager-h-f_tinqueux?q=436e4b9a68cdf410f9bd8113605497fd&o=382aa7ad-a6ef-4bbd-9791-31bf7c165f3d', 'https://www.welcometothejungle.com/fr/companies/aircall/jobs/principal-growth-data-analyst_paris?q=436e4b9a68cdf410f9bd8113605497fd&o=e7217ebc-3bb0-4a6d-9729-96945986330e', 'https://www.welcometothejungle.com/fr/companies/auto1/jobs/business-data-analyst-intern-h-f-fluent-in-french_chatillon?q=436e4b9a68cdf410f9bd8113605497fd&o=05a7c1d0-839d-47f2-996b-571f39151b9f', 'https://www.welcometothejungle.com/fr/companies/ekimetrics/jobs/manager-data-engineer-architect-h-f-n-paris_paris?q=436e4b9a68cdf410f9bd8113605497fd&o=f9b4128b-fd84-48eb-af62-52d9839e2978', 'https://www.welcometothejungle.com/fr/companies/freepro/jobs/data-operations-analyst-h-f_marseille?q=436e4b9a68cdf410f9bd8113605497fd&o=63ba386a-3f6b-46c6-b401-da0baf478f3c', 'https://www.welcometothejungle.com/fr/companies/natixis/jobs/senior-data-quality-advisor-f-h_paris?q=436e4b9a68cdf410f9bd8113605497fd&o=43f726ba-70b9-42c2-92f2-375229d8659e', 'https://www.welcometothejungle.com/fr/companies/allianz/jobs/alternance-12-mois-data-analyst-h-f_courbevoie?q=436e4b9a68cdf410f9bd8113605497fd&o=7be8bcf6-7a27-442e-9411-708ae4c8108c', 'https://www.welcometothejungle.com/fr/companies/technip-energies/jobs/apprenticeship-hr-data-analyst-f-h_nanterre?q=436e4b9a68cdf410f9bd8113605497fd&o=f1a7a398-12f8-4858-9ed5-e6ecf8d20409', 'https://www.welcometothejungle.com/fr/companies/technip-energies/jobs/vendor-data-coordinator-h-f_nanterre?q=436e4b9a68cdf410f9bd8113605497fd&o=a1978c29-0664-4f72-85d5-08c9450d4cc2', 'https://www.welcometothejungle.com/fr/companies/office-international-de-l-eau/jobs/charge-de-donnees_limoges_OIDL_1goDLRw?q=436e4b9a68cdf410f9bd8113605497fd&o=f524a4c8-a681-498f-8104-f8d1c628136b', 'https://www.welcometothejungle.com/fr/companies/dailymotion/jobs/data-analyst-operations-insights-all-genders_paris_DAILY_5xwl77a?q=436e4b9a68cdf410f9bd8113605497fd&o=5c25890c-5168-47c8-ac20-96fba46dd545']\n",
      "['https://www.welcometothejungle.com/fr/companies/orano/jobs/analyste-process-data-management-f-h_cherbourg-en-cotentin_ORANO_KAlKN5j?q=0a6ac56faa1b67bb1eb698a809381a83&o=2106d405-e37b-42f0-9535-60bb307e8ca8', 'https://www.welcometothejungle.com/fr/companies/littlebigcode/jobs/data-product-owner-h-f_neuilly-sur-seine_LITTL_VZzrk3W?q=0a6ac56faa1b67bb1eb698a809381a83&o=c8044885-a486-471f-b35f-7a025a7ea530', 'https://www.welcometothejungle.com/fr/companies/ey/jobs/data-analyst-experimente-h-f_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=11a09777-052d-4eff-b9f7-53697b9e18a1', 'https://www.welcometothejungle.com/fr/companies/ey/jobs/data-strategist-experimente-h-f_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=97b7f3f3-8079-4137-984d-bd31a3574056', 'https://www.welcometothejungle.com/fr/companies/ey/jobs/consultant-data-gouvernance-data-management-h-f_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=ddb8f953-a0ae-42c2-a688-2b32de1e3e9b', 'https://www.welcometothejungle.com/fr/companies/hager-group/jobs/data-bi-analyst-iot-h-f_pessac?q=0a6ac56faa1b67bb1eb698a809381a83&o=280ba50d-fcd8-4e6c-8f29-edf3fb322ea9', 'https://www.welcometothejungle.com/fr/companies/helloasso/jobs/data-analyst_begles_HELLO_mDL138N?q=0a6ac56faa1b67bb1eb698a809381a83&o=7c9ce005-99d8-4b90-8888-5e8ee4148899', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/data-manager-du-domaine-epargne-retraite-et-prevoyance-individuelle-f-h_nanterre?q=0a6ac56faa1b67bb1eb698a809381a83&o=296f3584-7ba6-4daa-bb30-2bb04ba557e2', 'https://www.welcometothejungle.com/fr/companies/groupe-micropole/jobs/consultant-data-management-f-h_villeurbanne?q=0a6ac56faa1b67bb1eb698a809381a83&o=a12750ec-8ce5-45f8-b256-7f099a554d0b', 'https://www.welcometothejungle.com/fr/companies/jakala/jobs/data-analyst-senior-cdi-paris-ou-caen?q=0a6ac56faa1b67bb1eb698a809381a83&o=f0e9d2ab-be03-4267-b8de-72e174e97f43', 'https://www.welcometothejungle.com/fr/companies/elevate/jobs/consultant-e-data-marketing-h-f-cdi_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=ff41f174-3932-4490-86d5-1d2e1753fe7a', 'https://www.welcometothejungle.com/fr/companies/skiils/jobs/data-analyst-retail-h-f?q=0a6ac56faa1b67bb1eb698a809381a83&o=8d00e210-e1f8-4a72-b27f-a14913c32de5', 'https://www.welcometothejungle.com/fr/companies/converteo/jobs/data-product-manager-h-f-cdi_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=cb61ea62-b8d5-4388-aa57-ac2736daf08d', 'https://www.welcometothejungle.com/fr/companies/tak/jobs/data-governance-coach_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=8764b3da-46de-4d3b-94c1-995bbd06cea3', 'https://www.welcometothejungle.com/fr/companies/pwc/jobs/data-analyste-pwc-montpellier-cdi-h-f_montpellier_PF_b6aelL0?q=0a6ac56faa1b67bb1eb698a809381a83&o=2eb64c25-a8ca-4c18-9938-0e7a5284c3f6', 'https://www.welcometothejungle.com/fr/companies/cbre-3/jobs/gestionnaire-de-l-information-bdd-data-quality-h-f_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=c9fc2b5e-9c8a-4c54-b259-4950dfc0fc3b', 'https://www.welcometothejungle.com/fr/companies/arcane/jobs/consultant-data-analyst-scientist-stage-fe-h-f_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=de8076d3-fb21-4622-909e-1073ca7fb539', 'https://www.welcometothejungle.com/fr/companies/exotec/jobs/r-d-data-analyst_lyon?q=0a6ac56faa1b67bb1eb698a809381a83&o=9dc193f9-c325-4b2f-8de4-b3b4483c5c96', 'https://www.welcometothejungle.com/fr/companies/exotec/jobs/r-d-data-analyst_lille?q=0a6ac56faa1b67bb1eb698a809381a83&o=fe860253-e91b-41de-a374-f37aa1ee219d', 'https://www.welcometothejungle.com/fr/companies/baw-business-at-work/jobs/data-engineer-h-f_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=e8605ebc-031c-4253-a8d7-d954477436d7', 'https://www.welcometothejungle.com/fr/companies/thales/jobs/data-analyst-confirme-h-f_toulouse?q=0a6ac56faa1b67bb1eb698a809381a83&o=999c5314-70c2-4b65-86d9-1c915b786ea6', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/senior-claims-controller-h-f_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=44860588-2e1a-43aa-8419-6752546b0f7a', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/senior-data-analyst-value-chain-f-m-d_croix?q=0a6ac56faa1b67bb1eb698a809381a83&o=12f16a45-7f11-49c5-806b-a82444ff4504', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/senior-data-analyst-value-chain-f-m-d_paris?q=0a6ac56faa1b67bb1eb698a809381a83&o=59845287-2e8b-4991-89bf-6bc62a2abad7']\n",
      "['https://www.welcometothejungle.com/fr/companies/allianz/jobs/data-product-owner-f-h_puteaux?q=426f857f51f3d03871b1d3686087b2ac&o=7e274b73-d212-4f1d-b6cb-22c024fdb05f', 'https://www.welcometothejungle.com/fr/companies/groupe-vyv/jobs/data-steward-f-h_paris?q=426f857f51f3d03871b1d3686087b2ac&o=4ce060c0-9f59-43a2-ac7d-0eb673ceaf90', 'https://www.welcometothejungle.com/fr/companies/datagalaxy/jobs/data-governance-consultant-h-f_paris?q=426f857f51f3d03871b1d3686087b2ac&o=0557f383-cb50-4477-954a-1929ead0639a', 'https://www.welcometothejungle.com/fr/companies/securitesociale/jobs/data-analyst-marketing-f-h_lille?q=426f857f51f3d03871b1d3686087b2ac&o=f82827e7-12c7-4519-a0d9-ee893eac8d28', 'https://www.welcometothejungle.com/fr/companies/homeserve/jobs/data-analyst-senior-homeserve-h-f_lyon-7eme-arrondissement_HOMES_JG4QVP4?q=426f857f51f3d03871b1d3686087b2ac&o=6e253d2e-f748-4346-ad74-68147491889d', 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      "['https://www.welcometothejungle.com/fr/companies/apside/jobs/data-analyst_sophia-antipolis?q=344dd5b552149fde41224bf23c2f2bec&o=5c9fd179-b53c-4484-ba6b-3d204bab35ad', 'https://www.welcometothejungle.com/fr/companies/ministere-de-l-interieur/jobs/pn-dcsp-dnsp-dn-75-data-analyste-sic_paris?q=344dd5b552149fde41224bf23c2f2bec&o=b77fadda-65f9-434e-9477-938745f0425c', 'https://www.welcometothejungle.com/fr/companies/52-entertainment/jobs/52-paris-game-data-analyst_boulogne-billancourt?q=344dd5b552149fde41224bf23c2f2bec&o=bd06a8bd-985c-4a60-b024-de514cb227b3', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/referent-data-et-actuariat-assurance-inclusive-f-h_nanterre?q=344dd5b552149fde41224bf23c2f2bec&o=614beb81-2d41-4c4b-8b99-de30033112f0', 'https://www.welcometothejungle.com/fr/companies/ey/jobs/consultant-junior-en-data-analytics-pour-le-secteur-financier_paris_EY_3NXMO4d?q=344dd5b552149fde41224bf23c2f2bec&o=73e3bdc0-02fd-4dcd-b7b4-46f7e3f8f458', 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      "['https://www.welcometothejungle.com/fr/companies/ministere-de-l-interieur/jobs/data-analyst-production-et-analyse-statistiques-politiques-publiques-insecurite-et-delinquance_paris?q=e660b722592c8b58182b0e46a5dd377d&o=ac358fff-1ab9-4c05-810b-820786fa7420', 'https://www.welcometothejungle.com/fr/companies/ministere-de-l-interieur/jobs/data-analyst-responsable-de-la-refonte-de-la-diffusion-statistique-interne_paris?q=e660b722592c8b58182b0e46a5dd377d&o=35246450-5f10-47b5-b799-55bbde5da260', 'https://www.welcometothejungle.com/fr/companies/dgse/jobs/data-owner-donnees-heterogenes-h-f_paris?q=e660b722592c8b58182b0e46a5dd377d&o=68cafd0f-d351-4c6c-886d-c60035f0e227', 'https://www.welcometothejungle.com/fr/companies/dgse/jobs/data-owner-donnees-heterogenes-h-f_paris_DGDLSE_1zzGzyx?q=e660b722592c8b58182b0e46a5dd377d&o=d8362666-efb5-4d55-af95-16bf7679e42b', 'https://www.welcometothejungle.com/fr/companies/doctolib/jobs/data-excellence-senior-associate-x-f-m_paris?q=e660b722592c8b58182b0e46a5dd377d&o=13209e1a-20e4-4756-9cfc-602d245a49c7', 'https://www.welcometothejungle.com/fr/companies/tata-consultancy-services/jobs/data-practice-head_puteaux?q=e660b722592c8b58182b0e46a5dd377d&o=91fc57b9-5119-4a6b-8c1c-f8f8346eccd8', 'https://www.welcometothejungle.com/fr/companies/devoteam-digital-impulse/jobs/consultants-data-management_levallois-perret?q=e660b722592c8b58182b0e46a5dd377d&o=bf5c2033-3d57-4b71-8f4a-1e822dce2761', 'https://www.welcometothejungle.com/fr/companies/bial-x/jobs/data-analyst-confirme?q=e660b722592c8b58182b0e46a5dd377d&o=21fabe1b-935a-4d16-9d85-f39ebe33a989', 'https://www.welcometothejungle.com/fr/companies/axa-climate/jobs/insurance-operations-data-analyst_paris?q=e660b722592c8b58182b0e46a5dd377d&o=ab2cdad1-5889-401b-aef4-27d69439da2c', 'https://www.welcometothejungle.com/fr/companies/pagegroup/jobs/responsable-data-h-f_brest?q=e660b722592c8b58182b0e46a5dd377d&o=fc0eb739-4267-4983-ab1a-86ecfdc78222', 'https://www.welcometothejungle.com/fr/companies/pennylane/jobs/data-analyst_paris_PENNY_gMP9M7N?q=e660b722592c8b58182b0e46a5dd377d&o=2947228c-5ca5-481c-9b19-2d496be467b8', 'https://www.welcometothejungle.com/fr/companies/better-stronger/jobs/data-analyst-expert-gcp-sql_lyon?q=e660b722592c8b58182b0e46a5dd377d&o=9446cd9a-ec23-4de3-8790-b5540edf310d', 'https://www.welcometothejungle.com/fr/companies/octo-technology/jobs/manager-offre-data-ia-senior-f-h-n_toulouse_OT_moq61da?q=e660b722592c8b58182b0e46a5dd377d&o=0c9c4570-977a-4c1d-83b5-742db2cf040c', 'https://www.welcometothejungle.com/fr/companies/natixis/jobs/business-analyst-client-data-lake-f-h_paris_NATIX_7gxkzgA?q=e660b722592c8b58182b0e46a5dd377d&o=e679bb66-bfbb-44b4-89eb-aaf498258d07', 'https://www.welcometothejungle.com/fr/companies/neoxam/jobs/business-analyst-financial-data-management-h-f-paris_paris-2e-arrondissement_NEOXA_brO5D4q?q=e660b722592c8b58182b0e46a5dd377d&o=f45ef220-01f2-45e3-857a-5c74b9b0af5c', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/business-analyst-master-data-f-h_nanterre?q=e660b722592c8b58182b0e46a5dd377d&o=c0f81e98-e8fa-4bd5-bfc7-5874d2210426', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/data-bi-business-analyst_paris?q=e660b722592c8b58182b0e46a5dd377d&o=a2d187fb-b205-4853-b4c0-80a423bd30e0', 'https://www.welcometothejungle.com/fr/companies/natixis/jobs/business-analyst-client-data-lake-f-h_paris_NATIX_Lp7k0G9?q=e660b722592c8b58182b0e46a5dd377d&o=3f0e8e8b-e301-4db9-9ddb-0040be719e64', 'https://www.welcometothejungle.com/fr/companies/axa/jobs/investment-data-platform-pisquare-analyst-m-f_puteaux?q=e660b722592c8b58182b0e46a5dd377d&o=204b0377-4082-4acb-a6dc-6ae40dea19cb', 'https://www.welcometothejungle.com/fr/companies/allianz/jobs/analyste-reporting-financier-et-data-h-f_courbevoie_AF_JzbWg0g?q=e660b722592c8b58182b0e46a5dd377d&o=0de14c79-c35c-4091-bea6-d4e3b4634700', 'https://www.welcometothejungle.com/fr/companies/ey/jobs/consultant-experimente-manager-en-data-intelligent-process-automation-secteur-financier_paris_EY_wo11RDb?q=e660b722592c8b58182b0e46a5dd377d&o=2d462d8b-f376-4046-9b57-282b30599d9a']\n",
      "['https://www.welcometothejungle.com/fr/companies/deloitte/jobs/manager-senior-manager-data-viz-bi-f-h_paris-la-defense?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=eb694ed4-4fca-46b2-a312-e2bf5ea5810d', 'https://www.welcometothejungle.com/fr/companies/biir/jobs/consultant-data-bi-h-f_lormont?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=f273857e-fe6f-4285-91a1-5f6a616ff96d', 'https://www.welcometothejungle.com/fr/companies/adjuvoo/jobs/consultant-finance-data-analyse_lyon?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=9cca632d-ba67-451d-9fe4-970e6f6048fa', 'https://www.welcometothejungle.com/fr/companies/thelio/jobs/consultant-data-confirme-h-f_lyon?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=ae6565f2-1494-4ee1-819e-4fb5705a5719', 'https://www.welcometothejungle.com/fr/companies/thelio/jobs/consultant-data-confirme-h-f_bordeaux?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=a32f6f7b-395c-4268-9a08-1b3a22345786', 'https://www.welcometothejungle.com/fr/companies/safran-seats-1/jobs/responsable-moe-bi-data-finance-hybride-f-h_plaisir?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=4dcab0fb-e0f0-46ac-a729-055f09a91c2b', 'https://www.welcometothejungle.com/fr/companies/keyrus/jobs/consultant-sap-data-services-business-object-h-f-nb_levallois-perret?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=b532fe78-972d-49b7-aa06-0f50eedf7eea', 'https://www.welcometothejungle.com/fr/companies/converteo/jobs/consultant-junior-digital-data_paris?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=108ae255-3062-458d-b3a5-e5c50643bf97', 'https://www.welcometothejungle.com/fr/companies/converteo/jobs/consultant-senior-digital-data-cdi_paris?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=1c304a06-b0c3-4b76-a478-65c01fd03993', 'https://www.welcometothejungle.com/fr/companies/hager-group/jobs/product-data-processes-specialist-h-f-x_obernai?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=840bf3e3-fe8c-4125-b87f-fa39cce09d28', 'https://www.welcometothejungle.com/fr/companies/groupe-micropole/jobs/ingenieur-d-affaires-data-h-f_levallois-perret?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=332978e1-1be1-4256-934c-1388e490d413', 'https://www.welcometothejungle.com/fr/companies/meritis/jobs/sophia-data-bi-h-f_biot_MERIT_GQZrNQd?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=6a3db8e6-3aef-4add-b090-3409f21f4f41', 'https://www.welcometothejungle.com/fr/companies/deloitte/jobs/manager-data-et-analytics-economic-advisory-f-h_paris-la-defense?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=3af19498-9373-46ee-9beb-1095839ee4cf', 'https://www.welcometothejungle.com/fr/companies/asi/jobs/consultant-bi-data-intelligence-confirme-h-f_lyon_ASI_aQ2jX8Y?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=a9fc3bcf-cb4b-43b6-9050-2e877852ad46', 'https://www.welcometothejungle.com/fr/companies/bearingpoint-france/jobs/consultant-junior-data-analytics-h-f_courbevoie?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=cdd6e5d3-0d99-4745-8ac7-b367ff8cfa9f', 'https://www.welcometothejungle.com/fr/companies/julhiet-sterwen/jobs/consultant-experimente-data-analytics-h-f_neuilly-sur-seine_JS_Y1DzYP1?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=6879e3b1-ae1a-4389-939d-59204f75b39c', 'https://www.welcometothejungle.com/fr/companies/ekimetrics/jobs/senior-consultant-data-scientist-f-m-n-paris_paris?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=d21f991f-3273-4b06-a317-c3917dd411b1', 'https://www.welcometothejungle.com/fr/companies/dream-catcher-sales/jobs/ingenieur-d-affaires-international-data-cybersecurite-de-6-ans-d-xp_paris?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=62ec5425-721f-4b06-802c-bb561a265d48', 'https://www.welcometothejungle.com/fr/companies/claravista/jobs/data-scientist-senior_paris?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=1bc863b3-1d4b-4c74-9446-4ebe0c0bf295']\n",
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      "['https://www.welcometothejungle.com/fr/companies/kelerian-group/jobs/consultants-en-pilotage-de-la-performance-data-et-mise-en-place-de-solutions-anaplan_paris?q=e0ac87b0f03c35ae2c0a82f3e2fbe504&o=3807d66c-2c34-4ed3-b2a3-13b63ea57d79', 'https://www.welcometothejungle.com/fr/companies/viginum/jobs/data-scientist-h-f_paris_VIGIN_ko31rGe?q=e0ac87b0f03c35ae2c0a82f3e2fbe504&o=7880400c-fa6a-45ad-b9ed-1aedb2e13d4d']\n",
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      "['https://www.welcometothejungle.com/fr/companies/cgi/jobs/consultant-data-virtualisation-f-h_toulouse?q=23362db91f197708a3fdc410385f8899&o=6d187451-7b67-4000-ba12-adfb58cc8de0', 'https://www.welcometothejungle.com/fr/companies/cgi/jobs/consultant-data-virtualisation-f-h_toulouse_CGI_9mP5kM0?q=23362db91f197708a3fdc410385f8899&o=44e00a67-8727-43e2-9e3b-820c8df0f02a', 'https://www.welcometothejungle.com/fr/companies/mydral/jobs/manager-data-analytics-h-f_paris_MYDRA_dAKkogr?q=23362db91f197708a3fdc410385f8899&o=f7c49c69-4b71-48fa-9dbc-45f2ce9a5aa0', 'https://www.welcometothejungle.com/fr/companies/groupe-micropole/jobs/consultant-data-gouvernance-f-h_villeurbanne?q=23362db91f197708a3fdc410385f8899&o=d1079b30-af3b-47b1-9669-cfd5b3177eb7', 'https://www.welcometothejungle.com/fr/companies/groupe-micropole/jobs/consultant-conseil-data-governance-f-h_levallois-perret?q=23362db91f197708a3fdc410385f8899&o=e9fad836-641e-4fba-9d98-a63bc1347ea9', 'https://www.welcometothejungle.com/fr/companies/quadratic-fr/jobs/data-scientist-analyse-junior-h-f-cdi-paris_paris?q=23362db91f197708a3fdc410385f8899&o=9062bf63-2d1a-434a-a4ed-43744d87e4a9', 'https://www.welcometothejungle.com/fr/companies/quadratic-fr/jobs/consultant-data-scientist-analyst-senior_paris?q=23362db91f197708a3fdc410385f8899&o=fd63795f-3fa6-4492-b6a6-79e1c2f68efd', 'https://www.welcometothejungle.com/fr/companies/kp-consulting/jobs/consultant-data-gouvernance_levallois-perret?q=23362db91f197708a3fdc410385f8899&o=77e28eda-6e57-4f68-ae37-3672327def61', 'https://www.welcometothejungle.com/fr/companies/kp-consulting/jobs/consultant-data-gouvernance_aix-en-provence?q=23362db91f197708a3fdc410385f8899&o=e752eb9c-24b9-48d8-bc5c-040b9d6e440b', 'https://www.welcometothejungle.com/fr/companies/airbus-1/jobs/data-integration-platforms-specialist-h-f_toulouse?q=23362db91f197708a3fdc410385f8899&o=9792a934-8dae-4b71-95fa-2f5a937bd8c0', 'https://www.welcometothejungle.com/fr/companies/ogury/jobs/vp-data-science-analytics_paris?q=23362db91f197708a3fdc410385f8899&o=3da63d80-0cc3-4f9a-9c32-76044a956af5', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/data-science-and-analytics-manager-f-m-d_lille?q=23362db91f197708a3fdc410385f8899&o=bec5c2d7-6a78-4a55-9ca0-a78303d9a8d1', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/data-science-and-analytics-manager-f-m-d_paris?q=23362db91f197708a3fdc410385f8899&o=72c434a6-2637-4a3f-9d4b-9ce9416fb9bc', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/senior-bw-data-engineer-sap-analytics-f-m-d_paris?q=23362db91f197708a3fdc410385f8899&o=811d077a-8b4f-4b0c-8cdf-6764a3b93d64', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/senior-bw-data-engineer-sap-analytics-f-m-d_croix?q=23362db91f197708a3fdc410385f8899&o=37802054-8ded-46c1-9078-3aab2a63117b', 'https://www.welcometothejungle.com/fr/companies/ekimetrics/jobs/manager-in-marketing-analytics-data-science-new-york_new-york?q=23362db91f197708a3fdc410385f8899&o=b38153f7-a27a-4afa-b1e7-3090949543b2', 'https://www.welcometothejungle.com/fr/companies/ekimetrics/jobs/manager-en-data-science-marketing-analytics-h-f-n_paris?q=23362db91f197708a3fdc410385f8899&o=5565bcc9-8fa6-4aa2-be03-d334c342f2d2', 'https://www.welcometothejungle.com/fr/companies/ministere-de-l-interieur/jobs/data-scientist-sur-l-analyse-territoriale-de-la-delinquance_paris_MDLEDO_e3mWp57?q=23362db91f197708a3fdc410385f8899&o=7b300377-1b33-4b85-add1-572deb8e8ac3', 'https://www.welcometothejungle.com/fr/companies/ministere-de-l-interieur/jobs/data-scientist-sur-l-analyse-territoriale-de-la-delinquance_paris?q=23362db91f197708a3fdc410385f8899&o=bdc68bea-f436-4f4e-af5e-ce3e1efd5c20']\n",
      "['https://www.welcometothejungle.com/fr/companies/flexia/jobs/consultant-confirme-senior-chef-de-projet-data-et-ou-sirh_paris?q=672cff2a1cdc88cf191e8cdd65f584fd&o=52a407b1-ecc4-4e21-846f-0460f475bf72']\n",
      "['https://www.welcometothejungle.com/fr/companies/keyrus/jobs/consultant-dataiku-h-f-nb_levallois-perret?q=f2e3c19745678d700f3fff92340c2d7f&o=d6acc5c5-9fdf-4ce5-a98f-fd165ca3eb24', 'https://www.welcometothejungle.com/fr/companies/orange-1/jobs/expert-dataviz-f-h_lyon-2eme-arrondissement_ORANG_5jJAaAK?q=f2e3c19745678d700f3fff92340c2d7f&o=d03e5d92-b3a5-4387-b08c-b4a85f4751e3']\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=20\n",
      "['https://www.welcometothejungle.com/fr/companies/keyrus/jobs/consultant-senior-dataviz-h-f-nb?q=943777847f39da0c454196d2ce93007f&o=7ed269bb-7f42-4638-a3ce-904945686d35']\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=22\n",
      "['https://www.welcometothejungle.com/fr/companies/cgi/jobs/consultant-dataviz-qliksense-f-h_toulouse?q=78b1c6f24ebb8e98a8ce2bf391487778&o=e6633bac-87dd-4093-85a1-9f025a9ac783', 'https://www.welcometothejungle.com/fr/companies/square-management/jobs/consultant-datascientist-risques-de-credit-climatiques-h-f_neuilly-sur-seine_SM_eYWrZKm?q=78b1c6f24ebb8e98a8ce2bf391487778&o=bde0abcc-cc43-41db-8b7f-0839dde3585e']\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=24\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=25\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=26\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=27\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=28\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=29\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=30\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=31\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=32\n",
      "An error occured on page https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=33\n",
      "J'ai 400 annonces au total\n",
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'https://www.welcometothejungle.com/fr/companies/archery-data-analytics/jobs/data-engineer-f-h_tours?q=509119178de5f26a89f97c7b3935df94&o=cc0b30c5-dc4f-4154-af75-ade5bf63024d', 'https://www.welcometothejungle.com/fr/companies/artefact/jobs/junior-data-consultant_paris?q=509119178de5f26a89f97c7b3935df94&o=77965e4d-ac8e-4a3b-aafb-edb7dbb32cfa', 'https://www.welcometothejungle.com/fr/companies/cgi/jobs/consultant-data-virtualisation-f-h_toulouse?q=23362db91f197708a3fdc410385f8899&o=6d187451-7b67-4000-ba12-adfb58cc8de0', 'https://www.welcometothejungle.com/fr/companies/cgi/jobs/consultant-data-virtualisation-f-h_toulouse_CGI_9mP5kM0?q=23362db91f197708a3fdc410385f8899&o=44e00a67-8727-43e2-9e3b-820c8df0f02a', 'https://www.welcometothejungle.com/fr/companies/mydral/jobs/manager-data-analytics-h-f_paris_MYDRA_dAKkogr?q=23362db91f197708a3fdc410385f8899&o=f7c49c69-4b71-48fa-9dbc-45f2ce9a5aa0', 'https://www.welcometothejungle.com/fr/companies/groupe-micropole/jobs/consultant-data-gouvernance-f-h_villeurbanne?q=23362db91f197708a3fdc410385f8899&o=d1079b30-af3b-47b1-9669-cfd5b3177eb7', 'https://www.welcometothejungle.com/fr/companies/groupe-micropole/jobs/consultant-conseil-data-governance-f-h_levallois-perret?q=23362db91f197708a3fdc410385f8899&o=e9fad836-641e-4fba-9d98-a63bc1347ea9', 'https://www.welcometothejungle.com/fr/companies/quadratic-fr/jobs/data-scientist-analyse-junior-h-f-cdi-paris_paris?q=23362db91f197708a3fdc410385f8899&o=9062bf63-2d1a-434a-a4ed-43744d87e4a9', 'https://www.welcometothejungle.com/fr/companies/quadratic-fr/jobs/consultant-data-scientist-analyst-senior_paris?q=23362db91f197708a3fdc410385f8899&o=fd63795f-3fa6-4492-b6a6-79e1c2f68efd', 'https://www.welcometothejungle.com/fr/companies/kp-consulting/jobs/consultant-data-gouvernance_levallois-perret?q=23362db91f197708a3fdc410385f8899&o=77e28eda-6e57-4f68-ae37-3672327def61', 'https://www.welcometothejungle.com/fr/companies/kp-consulting/jobs/consultant-data-gouvernance_aix-en-provence?q=23362db91f197708a3fdc410385f8899&o=e752eb9c-24b9-48d8-bc5c-040b9d6e440b', 'https://www.welcometothejungle.com/fr/companies/airbus-1/jobs/data-integration-platforms-specialist-h-f_toulouse?q=23362db91f197708a3fdc410385f8899&o=9792a934-8dae-4b71-95fa-2f5a937bd8c0', 'https://www.welcometothejungle.com/fr/companies/ogury/jobs/vp-data-science-analytics_paris?q=23362db91f197708a3fdc410385f8899&o=3da63d80-0cc3-4f9a-9c32-76044a956af5', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/data-science-and-analytics-manager-f-m-d_lille?q=23362db91f197708a3fdc410385f8899&o=bec5c2d7-6a78-4a55-9ca0-a78303d9a8d1', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/data-science-and-analytics-manager-f-m-d_paris?q=23362db91f197708a3fdc410385f8899&o=72c434a6-2637-4a3f-9d4b-9ce9416fb9bc', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/senior-bw-data-engineer-sap-analytics-f-m-d_paris?q=23362db91f197708a3fdc410385f8899&o=811d077a-8b4f-4b0c-8cdf-6764a3b93d64', 'https://www.welcometothejungle.com/fr/companies/decathlon-digital/jobs/senior-bw-data-engineer-sap-analytics-f-m-d_croix?q=23362db91f197708a3fdc410385f8899&o=37802054-8ded-46c1-9078-3aab2a63117b', 'https://www.welcometothejungle.com/fr/companies/ekimetrics/jobs/manager-in-marketing-analytics-data-science-new-york_new-york?q=23362db91f197708a3fdc410385f8899&o=b38153f7-a27a-4afa-b1e7-3090949543b2', 'https://www.welcometothejungle.com/fr/companies/ekimetrics/jobs/manager-en-data-science-marketing-analytics-h-f-n_paris?q=23362db91f197708a3fdc410385f8899&o=5565bcc9-8fa6-4aa2-be03-d334c342f2d2', 'https://www.welcometothejungle.com/fr/companies/ministere-de-l-interieur/jobs/data-scientist-sur-l-analyse-territoriale-de-la-delinquance_paris_MDLEDO_e3mWp57?q=23362db91f197708a3fdc410385f8899&o=7b300377-1b33-4b85-add1-572deb8e8ac3', 'https://www.welcometothejungle.com/fr/companies/ministere-de-l-interieur/jobs/data-scientist-sur-l-analyse-territoriale-de-la-delinquance_paris?q=23362db91f197708a3fdc410385f8899&o=bdc68bea-f436-4f4e-af5e-ce3e1efd5c20', 'https://www.welcometothejungle.com/fr/companies/flexia/jobs/consultant-confirme-senior-chef-de-projet-data-et-ou-sirh_paris?q=672cff2a1cdc88cf191e8cdd65f584fd&o=52a407b1-ecc4-4e21-846f-0460f475bf72', 'https://www.welcometothejungle.com/fr/companies/keyrus/jobs/consultant-dataiku-h-f-nb_levallois-perret?q=f2e3c19745678d700f3fff92340c2d7f&o=d6acc5c5-9fdf-4ce5-a98f-fd165ca3eb24', 'https://www.welcometothejungle.com/fr/companies/orange-1/jobs/expert-dataviz-f-h_lyon-2eme-arrondissement_ORANG_5jJAaAK?q=f2e3c19745678d700f3fff92340c2d7f&o=d03e5d92-b3a5-4387-b08c-b4a85f4751e3', 'https://www.welcometothejungle.com/fr/companies/keyrus/jobs/consultant-senior-dataviz-h-f-nb?q=943777847f39da0c454196d2ce93007f&o=7ed269bb-7f42-4638-a3ce-904945686d35', 'https://www.welcometothejungle.com/fr/companies/cgi/jobs/consultant-dataviz-qliksense-f-h_toulouse?q=78b1c6f24ebb8e98a8ce2bf391487778&o=e6633bac-87dd-4093-85a1-9f025a9ac783', 'https://www.welcometothejungle.com/fr/companies/square-management/jobs/consultant-datascientist-risques-de-credit-climatiques-h-f_neuilly-sur-seine_SM_eYWrZKm?q=78b1c6f24ebb8e98a8ce2bf391487778&o=bde0abcc-cc43-41db-8b7f-0839dde3585e']\n"
     ]
    }
   ],
   "source": [
    "############## SCRIPT PRINCIPAL COMPLET 1 ####################################\n",
    "##############################################################################\n",
    "\n",
    "## 1. je lance selenium pour aller sur la page de résultats ########################################################################\n",
    "service = Service(executable_path = 'chromedriver.exe')                         # je dis où est mon driver                       \n",
    "driver = webdriver.Chrome(service=service)                                      # je définis mon driver\n",
    "driver.get(\"https://www.welcometothejungle.com/fr\")                                                         # et je l'envoie sur la page d'accueil\n",
    "\n",
    "wait = WebDriverWait(driver, 8)                                                 # je laisse le temps à la page de se charger\n",
    "\n",
    "input_element = driver.find_element(By.ID,\"search-query-field\")                 # je sélectionne la barre de recherche\n",
    "input_element.clear()                                                           # je la vide au cas où elle est pré-remplie                                             \n",
    "input_element.send_keys(\"Data analyst\" + Keys.ENTER)                            # j'écris dans la barre de recherche\n",
    "\n",
    "random_delay()                                                                     # je laisse le temps à la page de charger\n",
    "\n",
    "## 2. je vais chercher les url de pagination ######################################################################################\n",
    "page_source = driver.page_source                                   # je vais chercher la page avec mon driver\n",
    "soup = BeautifulSoup(page_source, \"html.parser\")                   #  je passe le code HTML à BeautifulSoup pour l'analyser\n",
    "\n",
    "soup_pages = soup.find('nav', {\"aria-label\" : \"Pagination\"})      # Puis je vais chercher la section nav :\n",
    "\n",
    "if soup_pages is not None:                                        # Je mets un if si la page n'est pas chargée et que nav est vide\n",
    "    pli = soup_pages.find_all('li')                               # Puis je vais chercher tous les li contenus dans cette nav\n",
    "    nb_pages = pli[-2].text                                       # Puis je vais chercher le texte de l'avant dernier li \n",
    "    print(f\"\\nJ'ai {nb_pages} pages\")                               # (car le dernier c'est la flèche) pour avoir le nombre de pages\n",
    "\n",
    "else:                                                             # si la page n'a pas eu le temps de charger, j'affiche un message\n",
    "    print(\"Aucun élément HTML correspondant au sélecteur spécifié n'a été trouvé.\")\n",
    "\n",
    "result_url = driver.current_url                                   # je récupère l'URL sur laquelle je suis\n",
    "base_url = result_url.replace(\"1\",\"\")\n",
    "\n",
    "base_url = \"https://www.welcometothejungle.com/fr/jobs?query=data%20analyst&refinementList%5Boffices.country_code%5D%5B%5D=FR&refinementList%5Bcontract_type%5D%5B%5D=full_time&refinementList%5Bcontract_type%5D%5B%5D=temporary&page=\"\n",
    "page_number = 1\n",
    "urls_to_scrape = []\n",
    "\n",
    "# 3. je fais une boucle qui itère le nom de la page autant de fois que nécessaire\n",
    "for i in range(1,int(nb_pages)):\n",
    "    url = f\"{base_url}{i}\"\n",
    "    urls_to_scrape.append(url)\n",
    "print(urls_to_scrape)\n",
    "\n",
    "random_delay()     \n",
    "\n",
    "jobs_list = []\n",
    "\n",
    "for each_page in urls_to_scrape:\n",
    "    try:\n",
    "    # je charge la page actuelle dans le navigateur Web\n",
    "      driver.get(each_page)\n",
    "      random_delay() \n",
    "\n",
    "     # j'attends que la page soit entièrement chargée\n",
    "      wait = WebDriverWait(driver, 20)\n",
    "      wait.until(EC.visibility_of_element_located((By.PARTIAL_LINK_TEXT, \"Data\")))\n",
    "\n",
    "      links = (driver.find_elements(By.PARTIAL_LINK_TEXT, \"Data\")        # avec Selenium, je cherche les liens avec data dedans quelque soit la casse \n",
    "        or driver.find_elements(By.PARTIAL_LINK_TEXT, \"DATA\")\n",
    "        or  driver.find_elements(By.PARTIAL_LINK_TEXT, \"data\"))\n",
    "\n",
    "      urls = [link.get_attribute(\"href\") for link in links]              # j'extraits le contenu de href pour le mettre dans la liste urls\n",
    "      print(urls)\n",
    "    \n",
    "      jobs_list.extend(urls)\n",
    "    except:\n",
    "        print(f\"An error occured on page {driver.current_url}\")  \n",
    "\n",
    "print(f\"J'ai {len(jobs_list)} annonces au total\")\n",
    "print(jobs_list)\n",
    "\n",
    "driver.quit()                                                     # je ferme le navigateur une fois tout fini\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Récupération des infos de toutes les annonces"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.1 Formatage des URL pour l'API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['/esri/jobs/esri-france-data-scientist-specialise-analyse-spatiale-et-geomarketing-f-h_meudon?q=4143f6f511597ce85a131a249d7dce4f&o=60953789-64cb-4951-a2f6-ba1a20858ed1', '/sport-heroes-group/jobs/senior-data-analyst-head-of-data_paris?q=4143f6f511597ce85a131a249d7dce4f&o=dcb9d6c5-bb31-46aa-8c35-6e9f0168b3e2', '/carrefour/jobs/data-analyst-f-h_evry_CARRE_NPVOZeo?q=4143f6f511597ce85a131a249d7dce4f&o=ee9b39cd-deef-40d5-988b-57748c7c8132', '/hublo/jobs/senior-data-analyst-f-h-n_paris_HUBLO_bR85090?q=4143f6f511597ce85a131a249d7dce4f&o=0b5d40e8-64f9-4643-969b-752d0fd2582c', '/toucan-toco/jobs/data-analyst-engineer-revenue-operations_paris?q=4143f6f511597ce85a131a249d7dce4f&o=acf940dd-2e9c-4ef2-935b-30c2caf6b34f', '/rent-a-car/jobs/data-analyst-rh-joinville-le-pont-h-f_joinville-le-pont?q=4143f6f511597ce85a131a249d7dce4f&o=d6715289-a3b1-41c0-b3cf-48b13b14abaa', '/fbd-group/jobs/data-analyst-f-h_tremblay-en-france?q=4143f6f511597ce85a131a249d7dce4f&o=270b55d3-fa49-4015-a04e-7ee30b35fe7d', '/kramp-france/jobs/data-analyst-stage_poitiers?q=4143f6f511597ce85a131a249d7dce4f&o=34b20d22-1445-477b-bc96-5bd831e5d056', '/decathlon-digital/jobs/senior-data-analyst-customer-growth_paris_DD_r4mRzyZ?q=4143f6f511597ce85a131a249d7dce4f&o=1f659119-eac8-44f3-8ba5-fa7129ca1c83', '/accenture-france/jobs/data-analyst-f-h_nantes?q=4143f6f511597ce85a131a249d7dce4f&o=3c4d527a-0af3-4499-aad8-9f37c29a3ddc', '/coface/jobs/senior-data-analyst_bois-colombes?q=4143f6f511597ce85a131a249d7dce4f&o=1f6959f9-39ed-489e-817e-3aeffd29d785', '/l-oreal/jobs/data-quality-lead-professional-product-division_levallois-perret?q=4143f6f511597ce85a131a249d7dce4f&o=e9a063b1-942b-4fec-be69-305096be41b4', '/medicalib/jobs/data-analyst-confirme-cdi_paris?q=4143f6f511597ce85a131a249d7dce4f&o=2cee260f-59c1-40f1-b961-0a2786ba24db', '/asap/jobs/data-analyst-h-f_paris?q=4143f6f511597ce85a131a249d7dce4f&o=43d4a2c4-12fd-4bd3-942a-216585573f5d', '/beem-energy/jobs/data-bi-analyst-cdi_nantes?q=4143f6f511597ce85a131a249d7dce4f&o=9f32efc9-4a4f-4641-a44b-eee1c92dd172', '/groupe-la-centrale/jobs/digital-data-analyst-f-h_paris?q=4143f6f511597ce85a131a249d7dce4f&o=813b4388-4d3c-4769-ba4b-8d0f1b05f0ee', '/alpagga-1/jobs/data-analyst_paris?q=4143f6f511597ce85a131a249d7dce4f&o=205b35ca-40fb-4879-aac6-f5b859794d2e', '/avanade-france/jobs/business-analyst-data-h-f_issy-les-moulineaux_AF_Z0MgmWr?q=4143f6f511597ce85a131a249d7dce4f&o=f9866298-9d38-49cd-a815-8549f762ea13', '/niji/jobs/consultant-data-analyst-f-h_issy-les-moulineaux_NIJI_x3oy1em?q=4143f6f511597ce85a131a249d7dce4f&o=7b2ada66-75ad-4410-ae04-8d2bdc6bbd94', '/joko/jobs/data-analyst-product_paris?q=4143f6f511597ce85a131a249d7dce4f&o=466a5934-e861-4438-9690-ef0d687fad12', 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'https://api.welcometothejungle.com/api/v1/organizations/ekimetrics/jobs/senior-consultant-data-scientist-f-m-n-paris_paris?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=d21f991f-3273-4b06-a317-c3917dd411b1', 'https://api.welcometothejungle.com/api/v1/organizations/dream-catcher-sales/jobs/ingenieur-d-affaires-international-data-cybersecurite-de-6-ans-d-xp_paris?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=62ec5425-721f-4b06-802c-bb561a265d48', 'https://api.welcometothejungle.com/api/v1/organizations/claravista/jobs/data-scientist-senior_paris?q=c160ad1cff94c5ce3262d8ebb9c8ff7e&o=1bc863b3-1d4b-4c74-9446-4ebe0c0bf295', 'https://api.welcometothejungle.com/api/v1/organizations/monsieur-guiz/jobs/product-owner-h-f_paris_MG_Z9AAqMq?q=318d2a77cb9a9c82bf88486928e43473&o=4036740d-f31f-4e02-8835-936201536441', 'https://api.welcometothejungle.com/api/v1/organizations/monsieur-guiz/jobs/product-manager-data-h-f_paris?q=318d2a77cb9a9c82bf88486928e43473&o=6406c0d0-ff70-44e5-ae2c-425783269f5f', 'https://api.welcometothejungle.com/api/v1/organizations/okteo/jobs/ingenieur-data-bi_lyon?q=318d2a77cb9a9c82bf88486928e43473&o=e03aa5f4-2572-4a66-bd0c-f4eac1897dbe', 'https://api.welcometothejungle.com/api/v1/organizations/natixis/jobs/lead-data-scientist-f-h_paris?q=318d2a77cb9a9c82bf88486928e43473&o=feadc30d-27ad-4197-865c-255536b66719', 'https://api.welcometothejungle.com/api/v1/organizations/wewyse/jobs/product-owner-data_paris_WEWYS_zJLAQ60?q=318d2a77cb9a9c82bf88486928e43473&o=efccb3cc-5c9e-4205-9cc7-b757920d5770', 'https://api.welcometothejungle.com/api/v1/organizations/gojob/jobs/data-analytics-engineer-aix-en-provence_aix-en-provence?q=318d2a77cb9a9c82bf88486928e43473&o=7544e267-f95d-4e2d-bd2b-19c5581532d5', 'https://api.welcometothejungle.com/api/v1/organizations/klb-group-1/jobs/ingenieur-capex-data-analyste-h-f_paris_KLB_pMwkN0J?q=318d2a77cb9a9c82bf88486928e43473&o=988d285d-13e8-4b38-9b6b-2fcc279beec6', 'https://api.welcometothejungle.com/api/v1/organizations/sopra-steria/jobs/ingenieur-data-services-publics-nantes_nantes_SS_pRlXWY8?q=318d2a77cb9a9c82bf88486928e43473&o=eeeae1aa-6292-4b0c-8058-3d8802abf934', 'https://api.welcometothejungle.com/api/v1/organizations/sopra-steria/jobs/ingenieur-data-services-publics-bordeaux_merignac_SS_kLl2Dl3?q=318d2a77cb9a9c82bf88486928e43473&o=5b6b34e1-81ae-4468-9acb-5ba204d8cd61', 'https://api.welcometothejungle.com/api/v1/organizations/sopra-steria/jobs/ingenieur-data-services-publics-bordeaux_merignac_SS_5wPYpQK?q=318d2a77cb9a9c82bf88486928e43473&o=4e9a0336-e5ae-4d17-81f2-cd3b5b667bec', 'https://api.welcometothejungle.com/api/v1/organizations/blank/jobs/data-engineer-f-m_paris?q=318d2a77cb9a9c82bf88486928e43473&o=5e328ce5-b35a-4d44-b516-85307cdc4974', 'https://api.welcometothejungle.com/api/v1/organizations/bartle/jobs/consultant-data-analyste-h-f_paris?q=318d2a77cb9a9c82bf88486928e43473&o=0db619c3-cf75-4fb1-b2d6-7a8e1e6bc34b', 'https://api.welcometothejungle.com/api/v1/organizations/groupe-fnac-darty/jobs/analyste-data-clients-f-h_ivry-sur-seine?q=318d2a77cb9a9c82bf88486928e43473&o=6b20683f-67fb-467f-a563-d78a2a53632a', 'https://api.welcometothejungle.com/api/v1/organizations/safran-aircraft-engines/jobs/data-analyste-mro-moteur-militaires-f-h_chatellerault?q=318d2a77cb9a9c82bf88486928e43473&o=4f58f70b-1677-41d3-acc8-549f1cfbfcef', 'https://api.welcometothejungle.com/api/v1/organizations/sopra-steria/jobs/ingenieur-data-bordeaux_merignac?q=318d2a77cb9a9c82bf88486928e43473&o=fc75b2c2-96e8-4e92-b3c6-9688bb1292ec', 'https://api.welcometothejungle.com/api/v1/organizations/sopra-steria/jobs/ingenieur-data-aeroline-toulon_six-fours-les-plages_SS_xxq3k5M?q=318d2a77cb9a9c82bf88486928e43473&o=593fb0d8-52d1-4e50-bb57-3204e50bac84', 'https://api.welcometothejungle.com/api/v1/organizations/sopra-steria/jobs/ingenieur-data-industries-services-bordeaux_merignac?q=318d2a77cb9a9c82bf88486928e43473&o=5fead609-9650-4cdd-8965-f9527e3ae5de', 'https://api.welcometothejungle.com/api/v1/organizations/securitesociale/jobs/analyste-production-big-data_rouen_LSS_1jlzOw0?q=318d2a77cb9a9c82bf88486928e43473&o=94f1fb96-6b5b-4f26-ad9d-b79fe2ac710d', 'https://api.welcometothejungle.com/api/v1/organizations/pwc/jobs/analyste-audit-it-data-pwc-montpellier-cdi-h-f_montpellier_PF_Q5lM0mj?q=318d2a77cb9a9c82bf88486928e43473&o=a20d5d02-c5bb-4bd3-b7c5-d1ba9877064a', 'https://api.welcometothejungle.com/api/v1/organizations/kp-consulting/jobs/amoa-data_aix-en-provence?q=318d2a77cb9a9c82bf88486928e43473&o=cfbcd547-5d56-487d-94f0-5e5f155a816e', 'https://api.welcometothejungle.com/api/v1/organizations/kelerian-group/jobs/consultants-en-pilotage-de-la-performance-data-et-mise-en-place-de-solutions-anaplan_paris?q=e0ac87b0f03c35ae2c0a82f3e2fbe504&o=3807d66c-2c34-4ed3-b2a3-13b63ea57d79', 'https://api.welcometothejungle.com/api/v1/organizations/viginum/jobs/data-scientist-h-f_paris_VIGIN_ko31rGe?q=e0ac87b0f03c35ae2c0a82f3e2fbe504&o=7880400c-fa6a-45ad-b9ed-1aedb2e13d4d', 'https://api.welcometothejungle.com/api/v1/organizations/edenred/jobs/product-owner-data-h-f_malakoff?q=509119178de5f26a89f97c7b3935df94&o=26e761fb-0462-4952-82d8-e83a48c2e239', 'https://api.welcometothejungle.com/api/v1/organizations/niji/jobs/data-analytics-engineer-f-h_nantes?q=509119178de5f26a89f97c7b3935df94&o=ffadd89e-0f4b-488a-992b-5929247db4ad', 'https://api.welcometothejungle.com/api/v1/organizations/niji/jobs/consultant-data-analytics-engineer-f-h_bordeaux?q=509119178de5f26a89f97c7b3935df94&o=a8f2d753-804f-492b-9ac2-780d17dbf7d8', 'https://api.welcometothejungle.com/api/v1/organizations/elevate/jobs/manager-data-analysis-engineering-science_paris?q=509119178de5f26a89f97c7b3935df94&o=47927b0d-829e-4eb3-93b1-a266bfadcde4', 'https://api.welcometothejungle.com/api/v1/organizations/groupe-adp/jobs/data-analytics-engineer-f-h_paray-vieille-poste?q=509119178de5f26a89f97c7b3935df94&o=84fa3de4-534f-42bd-a906-5dfcface853c', 'https://api.welcometothejungle.com/api/v1/organizations/klint-consulting/jobs/consultant-data-gouvernance-h-f?q=509119178de5f26a89f97c7b3935df94&o=e81d9766-9b81-4e85-a764-fdba5446b77a', 'https://api.welcometothejungle.com/api/v1/organizations/groupe-micropole/jobs/consultant-data-governance-f-h_villeurbanne?q=509119178de5f26a89f97c7b3935df94&o=5e5e5ff4-bd02-4b2b-b176-7d4e790e3f9c', 'https://api.welcometothejungle.com/api/v1/organizations/klint-consulting/jobs/consultant-data-h-f_levallois-perret?q=509119178de5f26a89f97c7b3935df94&o=bae37131-924a-4cbc-b8fe-bf83c7a87843', 'https://api.welcometothejungle.com/api/v1/organizations/corail-analaytics/jobs/analyst-engineer?q=509119178de5f26a89f97c7b3935df94&o=e09a5360-8ce7-490d-aac6-63031263e6dd', 'https://api.welcometothejungle.com/api/v1/organizations/archery-data-analytics/jobs/data-engineer_toulouse?q=509119178de5f26a89f97c7b3935df94&o=4a29b12a-8700-4f4a-aa84-1f1f7a17bd56', 'https://api.welcometothejungle.com/api/v1/organizations/groupe-micropole/jobs/azure-data-integration-api-consultant-f-h_levallois-perret?q=509119178de5f26a89f97c7b3935df94&o=917b72c7-7c51-4db2-9683-f94417cccde2', 'https://api.welcometothejungle.com/api/v1/organizations/meltone-advisory/jobs/consultant-senior-data-analytics-h-f_paris?q=509119178de5f26a89f97c7b3935df94&o=9bf594d6-2dd9-4a83-8164-adace600fa6e', 'https://api.welcometothejungle.com/api/v1/organizations/margo/jobs/data-integration-specialist-python-h-f_paris?q=509119178de5f26a89f97c7b3935df94&o=709c05ce-cf19-49b9-9acb-9918de69bd71', 'https://api.welcometothejungle.com/api/v1/organizations/l-oreal/jobs/data-integration-solutions-architect_clichy?q=509119178de5f26a89f97c7b3935df94&o=df0e98aa-ae56-4de5-b357-48a6f9a9891b', 'https://api.welcometothejungle.com/api/v1/organizations/l-oreal/jobs/it-master-data-analytics-lead_clichy?q=509119178de5f26a89f97c7b3935df94&o=b45c87ca-1ff6-4b3d-b616-791e15bab9e3', 'https://api.welcometothejungle.com/api/v1/organizations/kpmg-france/jobs/architecte-data-analytics-f-h_courbevoie_KF_DP6ygV8?q=509119178de5f26a89f97c7b3935df94&o=14c0e930-f236-4508-aaf2-7cdced9991aa', 'https://api.welcometothejungle.com/api/v1/organizations/opensee/jobs/junior-implementation-engineer-big-data-analytics_paris_OPENS_jJp0mPN?q=509119178de5f26a89f97c7b3935df94&o=65c5ad75-25f5-41a3-9cf7-bb2c4bb85ff8', 'https://api.welcometothejungle.com/api/v1/organizations/opensee/jobs/front-end-developer-big-data-analytics-fintech_paris_OPENS_Po24Wjw?q=509119178de5f26a89f97c7b3935df94&o=a9b472e2-184a-488a-aeac-6553cc951d41', 'https://api.welcometothejungle.com/api/v1/organizations/naos/jobs/digital-data-analytics-web-gtm-ga-server-side-h-f_aix-en-provence_NBIEEP_qdl60OG?q=509119178de5f26a89f97c7b3935df94&o=6a21670a-e8e3-497a-9578-e221872ceea6', 'https://api.welcometothejungle.com/api/v1/organizations/archery-data-analytics/jobs/data-engineer-f-h_tours?q=509119178de5f26a89f97c7b3935df94&o=cc0b30c5-dc4f-4154-af75-ade5bf63024d', 'https://api.welcometothejungle.com/api/v1/organizations/artefact/jobs/junior-data-consultant_paris?q=509119178de5f26a89f97c7b3935df94&o=77965e4d-ac8e-4a3b-aafb-edb7dbb32cfa', 'https://api.welcometothejungle.com/api/v1/organizations/cgi/jobs/consultant-data-virtualisation-f-h_toulouse?q=23362db91f197708a3fdc410385f8899&o=6d187451-7b67-4000-ba12-adfb58cc8de0', 'https://api.welcometothejungle.com/api/v1/organizations/cgi/jobs/consultant-data-virtualisation-f-h_toulouse_CGI_9mP5kM0?q=23362db91f197708a3fdc410385f8899&o=44e00a67-8727-43e2-9e3b-820c8df0f02a', 'https://api.welcometothejungle.com/api/v1/organizations/mydral/jobs/manager-data-analytics-h-f_paris_MYDRA_dAKkogr?q=23362db91f197708a3fdc410385f8899&o=f7c49c69-4b71-48fa-9dbc-45f2ce9a5aa0', 'https://api.welcometothejungle.com/api/v1/organizations/groupe-micropole/jobs/consultant-data-gouvernance-f-h_villeurbanne?q=23362db91f197708a3fdc410385f8899&o=d1079b30-af3b-47b1-9669-cfd5b3177eb7', 'https://api.welcometothejungle.com/api/v1/organizations/groupe-micropole/jobs/consultant-conseil-data-governance-f-h_levallois-perret?q=23362db91f197708a3fdc410385f8899&o=e9fad836-641e-4fba-9d98-a63bc1347ea9', 'https://api.welcometothejungle.com/api/v1/organizations/quadratic-fr/jobs/data-scientist-analyse-junior-h-f-cdi-paris_paris?q=23362db91f197708a3fdc410385f8899&o=9062bf63-2d1a-434a-a4ed-43744d87e4a9', 'https://api.welcometothejungle.com/api/v1/organizations/quadratic-fr/jobs/consultant-data-scientist-analyst-senior_paris?q=23362db91f197708a3fdc410385f8899&o=fd63795f-3fa6-4492-b6a6-79e1c2f68efd', 'https://api.welcometothejungle.com/api/v1/organizations/kp-consulting/jobs/consultant-data-gouvernance_levallois-perret?q=23362db91f197708a3fdc410385f8899&o=77e28eda-6e57-4f68-ae37-3672327def61', 'https://api.welcometothejungle.com/api/v1/organizations/kp-consulting/jobs/consultant-data-gouvernance_aix-en-provence?q=23362db91f197708a3fdc410385f8899&o=e752eb9c-24b9-48d8-bc5c-040b9d6e440b', 'https://api.welcometothejungle.com/api/v1/organizations/airbus-1/jobs/data-integration-platforms-specialist-h-f_toulouse?q=23362db91f197708a3fdc410385f8899&o=9792a934-8dae-4b71-95fa-2f5a937bd8c0', 'https://api.welcometothejungle.com/api/v1/organizations/ogury/jobs/vp-data-science-analytics_paris?q=23362db91f197708a3fdc410385f8899&o=3da63d80-0cc3-4f9a-9c32-76044a956af5', 'https://api.welcometothejungle.com/api/v1/organizations/decathlon-digital/jobs/data-science-and-analytics-manager-f-m-d_lille?q=23362db91f197708a3fdc410385f8899&o=bec5c2d7-6a78-4a55-9ca0-a78303d9a8d1', 'https://api.welcometothejungle.com/api/v1/organizations/decathlon-digital/jobs/data-science-and-analytics-manager-f-m-d_paris?q=23362db91f197708a3fdc410385f8899&o=72c434a6-2637-4a3f-9d4b-9ce9416fb9bc', 'https://api.welcometothejungle.com/api/v1/organizations/decathlon-digital/jobs/senior-bw-data-engineer-sap-analytics-f-m-d_paris?q=23362db91f197708a3fdc410385f8899&o=811d077a-8b4f-4b0c-8cdf-6764a3b93d64', 'https://api.welcometothejungle.com/api/v1/organizations/decathlon-digital/jobs/senior-bw-data-engineer-sap-analytics-f-m-d_croix?q=23362db91f197708a3fdc410385f8899&o=37802054-8ded-46c1-9078-3aab2a63117b', 'https://api.welcometothejungle.com/api/v1/organizations/ekimetrics/jobs/manager-in-marketing-analytics-data-science-new-york_new-york?q=23362db91f197708a3fdc410385f8899&o=b38153f7-a27a-4afa-b1e7-3090949543b2', 'https://api.welcometothejungle.com/api/v1/organizations/ekimetrics/jobs/manager-en-data-science-marketing-analytics-h-f-n_paris?q=23362db91f197708a3fdc410385f8899&o=5565bcc9-8fa6-4aa2-be03-d334c342f2d2', 'https://api.welcometothejungle.com/api/v1/organizations/ministere-de-l-interieur/jobs/data-scientist-sur-l-analyse-territoriale-de-la-delinquance_paris_MDLEDO_e3mWp57?q=23362db91f197708a3fdc410385f8899&o=7b300377-1b33-4b85-add1-572deb8e8ac3', 'https://api.welcometothejungle.com/api/v1/organizations/ministere-de-l-interieur/jobs/data-scientist-sur-l-analyse-territoriale-de-la-delinquance_paris?q=23362db91f197708a3fdc410385f8899&o=bdc68bea-f436-4f4e-af5e-ce3e1efd5c20', 'https://api.welcometothejungle.com/api/v1/organizations/flexia/jobs/consultant-confirme-senior-chef-de-projet-data-et-ou-sirh_paris?q=672cff2a1cdc88cf191e8cdd65f584fd&o=52a407b1-ecc4-4e21-846f-0460f475bf72', 'https://api.welcometothejungle.com/api/v1/organizations/keyrus/jobs/consultant-dataiku-h-f-nb_levallois-perret?q=f2e3c19745678d700f3fff92340c2d7f&o=d6acc5c5-9fdf-4ce5-a98f-fd165ca3eb24', 'https://api.welcometothejungle.com/api/v1/organizations/orange-1/jobs/expert-dataviz-f-h_lyon-2eme-arrondissement_ORANG_5jJAaAK?q=f2e3c19745678d700f3fff92340c2d7f&o=d03e5d92-b3a5-4387-b08c-b4a85f4751e3', 'https://api.welcometothejungle.com/api/v1/organizations/keyrus/jobs/consultant-senior-dataviz-h-f-nb?q=943777847f39da0c454196d2ce93007f&o=7ed269bb-7f42-4638-a3ce-904945686d35', 'https://api.welcometothejungle.com/api/v1/organizations/cgi/jobs/consultant-dataviz-qliksense-f-h_toulouse?q=78b1c6f24ebb8e98a8ce2bf391487778&o=e6633bac-87dd-4093-85a1-9f025a9ac783', 'https://api.welcometothejungle.com/api/v1/organizations/square-management/jobs/consultant-datascientist-risques-de-credit-climatiques-h-f_neuilly-sur-seine_SM_eYWrZKm?q=78b1c6f24ebb8e98a8ce2bf391487778&o=bde0abcc-cc43-41db-8b7f-0839dde3585e']\n",
      "400\n"
     ]
    }
   ],
   "source": [
    "## 1. formatage des urls en relative pour le requêtage ##\n",
    "\n",
    "relative_urls = [sub.replace(\"https://www.welcometothejungle.com/fr/companies\", \"\") for sub in jobs_list]\n",
    "print(relative_urls)\n",
    "print(len(relative_urls))                               # je vérifie que je n'ai rien perdu\n",
    "\n",
    "## 2. formatage des urls relatives en url de requêtage ##\n",
    "api_urls = []\n",
    "for url in relative_urls:\n",
    "    api_url = f\"https://api.welcometothejungle.com/api/v1/organizations{url}\"\n",
    "    api_urls.append(api_url)\n",
    "print(api_urls)\n",
    "print(len(api_urls))                       # je vérifie que je n'ai rien perdu"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.2. Requêtage et fabrication du Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>job.salary_period</th>\n",
       "      <th>job.contract_type</th>\n",
       "      <th>job.application_fields</th>\n",
       "      <th>job.remote</th>\n",
       "      <th>job.is_default</th>\n",
       "      <th>job.apply_url</th>\n",
       "      <th>job.urls</th>\n",
       "      <th>job.updated_at</th>\n",
       "      <th>job.organization.nb_employees</th>\n",
       "      <th>job.organization.equality_indexes.equality_among_highest_earners</th>\n",
       "      <th>...</th>\n",
       "      <th>job.profession.sub_category_name.es</th>\n",
       "      <th>job.profession.sub_category_name.fr</th>\n",
       "      <th>job.profession.sub_category_name.sk</th>\n",
       "      <th>job.profession.sub_category_reference</th>\n",
       "      <th>job.contract_duration_max</th>\n",
       "      <th>job.organization.website_organization.i18n_descriptions.en</th>\n",
       "      <th>job.organization.equality_indexes</th>\n",
       "      <th>job.featured_page</th>\n",
       "      <th>job.organization.gdpr_setting</th>\n",
       "      <th>job.organization.website_organization.i18n_descriptions.es</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>None</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': '3605cdfd-d0ce-4063-8041-f0e09eb9cb10'...</td>\n",
       "      <td>partial</td>\n",
       "      <td>False</td>\n",
       "      <td>None</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-26T12:26:07Z</td>\n",
       "      <td>242.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Datos/Inteligencia empresarial</td>\n",
       "      <td>Données/Business Intelligence</td>\n",
       "      <td>Údaje/obchodné spravodajstvo</td>\n",
       "      <td>data-business-intelligence-yZjY1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>None</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': '0a5dbdd8-47a2-479a-a9dc-5988af8929b3'...</td>\n",
       "      <td>partial</td>\n",
       "      <td>False</td>\n",
       "      <td>None</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-26T10:16:29Z</td>\n",
       "      <td>70.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Datos/Inteligencia empresarial</td>\n",
       "      <td>Données/Business Intelligence</td>\n",
       "      <td>Údaje/obchodné spravodajstvo</td>\n",
       "      <td>data-business-intelligence-yZjY1</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>monthly</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': '6eaef475-fea7-4aa5-9a1d-8918d6df0684'...</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "      <td>https://www.aplitrak.com/?adid=Q2F0aGVyaW5lLk1...</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-26T09:20:49Z</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Datos/Inteligencia empresarial</td>\n",
       "      <td>Données/Business Intelligence</td>\n",
       "      <td>Údaje/obchodné spravodajstvo</td>\n",
       "      <td>data-business-intelligence-yZjY1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>yearly</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': '72b937f4-0688-4f71-ac41-b62c42ea862b'...</td>\n",
       "      <td>punctual</td>\n",
       "      <td>False</td>\n",
       "      <td>https://careers.hublo.com/jobs/3616361-senior-...</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-26T06:28:48Z</td>\n",
       "      <td>200.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Datos/Inteligencia empresarial</td>\n",
       "      <td>Données/Business Intelligence</td>\n",
       "      <td>Údaje/obchodné spravodajstvo</td>\n",
       "      <td>data-business-intelligence-yZjY1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;p&gt;At Hublo, &lt;strong&gt;we believe in the power o...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>None</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': 'af6b4e82-b14a-4e5c-9edd-67497867cc20'...</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>False</td>\n",
       "      <td>None</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-26T07:00:08Z</td>\n",
       "      <td>85.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Datos/Inteligencia empresarial</td>\n",
       "      <td>Données/Business Intelligence</td>\n",
       "      <td>Údaje/obchodné spravodajstvo</td>\n",
       "      <td>data-business-intelligence-yZjY1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;p&gt;Toucan is a customer-facing analytics platf...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>395</th>\n",
       "      <td>None</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': '5c36f22d-bfcb-44cd-b988-f95554e5b82f'...</td>\n",
       "      <td>punctual</td>\n",
       "      <td>False</td>\n",
       "      <td>https://jobs.keyrus.fr/jobs/1075663-consultant...</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-14T07:53:57Z</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Datos/Inteligencia empresarial</td>\n",
       "      <td>Données/Business Intelligence</td>\n",
       "      <td>Údaje/obchodné spravodajstvo</td>\n",
       "      <td>data-business-intelligence-yZjY1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>yearly</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': '5113e7ed-4bf5-40e9-9a20-d361706ab0d3'...</td>\n",
       "      <td>partial</td>\n",
       "      <td>False</td>\n",
       "      <td>http://app.mytalentplug.com/redirection.aspx?o...</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-07T18:44:01Z</td>\n",
       "      <td>137000.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Datos/Inteligencia empresarial</td>\n",
       "      <td>Données/Business Intelligence</td>\n",
       "      <td>Údaje/obchodné spravodajstvo</td>\n",
       "      <td>data-business-intelligence-yZjY1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397</th>\n",
       "      <td>None</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': '5413359b-a100-4405-b0a7-714fb6fc8bf5'...</td>\n",
       "      <td>punctual</td>\n",
       "      <td>False</td>\n",
       "      <td>https://jobs.keyrus.fr/jobs/1094548-consultant...</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-14T07:47:43Z</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Datos/Inteligencia empresarial</td>\n",
       "      <td>Données/Business Intelligence</td>\n",
       "      <td>Údaje/obchodné spravodajstvo</td>\n",
       "      <td>data-business-intelligence-yZjY1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>398</th>\n",
       "      <td>None</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': 'e7e8bb66-2650-4679-ac20-ee1781cd0bcf'...</td>\n",
       "      <td>partial</td>\n",
       "      <td>False</td>\n",
       "      <td>https://cgi.njoyn.com/corp/xweb/xweb.asp?clid=...</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-26T00:22:28Z</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Datos/Inteligencia empresarial</td>\n",
       "      <td>Données/Business Intelligence</td>\n",
       "      <td>Údaje/obchodné spravodajstvo</td>\n",
       "      <td>data-business-intelligence-yZjY1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>None</td>\n",
       "      <td>full_time</td>\n",
       "      <td>[{'id': '15242def-7b41-4ded-a6bd-5a3bb8ef4b1a'...</td>\n",
       "      <td>punctual</td>\n",
       "      <td>False</td>\n",
       "      <td>https://careers.flatchr.io/vacancy/exy5jpx6k6b...</td>\n",
       "      <td>[{'kind': 'canonical', 'href': 'https://www.we...</td>\n",
       "      <td>2024-06-07T20:45:55Z</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Banca y préstamos</td>\n",
       "      <td>Services bancaires et prêts</td>\n",
       "      <td>Bankovníctvo a úverové služby</td>\n",
       "      <td>banking-and-lending-hZmQ3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>400 rows × 136 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    job.salary_period job.contract_type  \\\n",
       "0                None         full_time   \n",
       "1                None         full_time   \n",
       "2             monthly         full_time   \n",
       "3              yearly         full_time   \n",
       "4                None         full_time   \n",
       "..                ...               ...   \n",
       "395              None         full_time   \n",
       "396            yearly         full_time   \n",
       "397              None         full_time   \n",
       "398              None         full_time   \n",
       "399              None         full_time   \n",
       "\n",
       "                                job.application_fields job.remote  \\\n",
       "0    [{'id': '3605cdfd-d0ce-4063-8041-f0e09eb9cb10'...    partial   \n",
       "1    [{'id': '0a5dbdd8-47a2-479a-a9dc-5988af8929b3'...    partial   \n",
       "2    [{'id': '6eaef475-fea7-4aa5-9a1d-8918d6df0684'...         no   \n",
       "3    [{'id': '72b937f4-0688-4f71-ac41-b62c42ea862b'...   punctual   \n",
       "4    [{'id': 'af6b4e82-b14a-4e5c-9edd-67497867cc20'...   fulltime   \n",
       "..                                                 ...        ...   \n",
       "395  [{'id': '5c36f22d-bfcb-44cd-b988-f95554e5b82f'...   punctual   \n",
       "396  [{'id': '5113e7ed-4bf5-40e9-9a20-d361706ab0d3'...    partial   \n",
       "397  [{'id': '5413359b-a100-4405-b0a7-714fb6fc8bf5'...   punctual   \n",
       "398  [{'id': 'e7e8bb66-2650-4679-ac20-ee1781cd0bcf'...    partial   \n",
       "399  [{'id': '15242def-7b41-4ded-a6bd-5a3bb8ef4b1a'...   punctual   \n",
       "\n",
       "     job.is_default                                      job.apply_url  \\\n",
       "0             False                                               None   \n",
       "1             False                                               None   \n",
       "2             False  https://www.aplitrak.com/?adid=Q2F0aGVyaW5lLk1...   \n",
       "3             False  https://careers.hublo.com/jobs/3616361-senior-...   \n",
       "4             False                                               None   \n",
       "..              ...                                                ...   \n",
       "395           False  https://jobs.keyrus.fr/jobs/1075663-consultant...   \n",
       "396           False  http://app.mytalentplug.com/redirection.aspx?o...   \n",
       "397           False  https://jobs.keyrus.fr/jobs/1094548-consultant...   \n",
       "398           False  https://cgi.njoyn.com/corp/xweb/xweb.asp?clid=...   \n",
       "399           False  https://careers.flatchr.io/vacancy/exy5jpx6k6b...   \n",
       "\n",
       "                                              job.urls        job.updated_at  \\\n",
       "0    [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-26T12:26:07Z   \n",
       "1    [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-26T10:16:29Z   \n",
       "2    [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-26T09:20:49Z   \n",
       "3    [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-26T06:28:48Z   \n",
       "4    [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-26T07:00:08Z   \n",
       "..                                                 ...                   ...   \n",
       "395  [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-14T07:53:57Z   \n",
       "396  [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-07T18:44:01Z   \n",
       "397  [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-14T07:47:43Z   \n",
       "398  [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-26T00:22:28Z   \n",
       "399  [{'kind': 'canonical', 'href': 'https://www.we...  2024-06-07T20:45:55Z   \n",
       "\n",
       "     job.organization.nb_employees  \\\n",
       "0                            242.0   \n",
       "1                             70.0   \n",
       "2                         100000.0   \n",
       "3                            200.0   \n",
       "4                             85.0   \n",
       "..                             ...   \n",
       "395                         3500.0   \n",
       "396                       137000.0   \n",
       "397                         3500.0   \n",
       "398                        14000.0   \n",
       "399                          900.0   \n",
       "\n",
       "     job.organization.equality_indexes.equality_among_highest_earners  ...  \\\n",
       "0                                                  0.0                 ...   \n",
       "1                                                 10.0                 ...   \n",
       "2                                                  NaN                 ...   \n",
       "3                                                  0.0                 ...   \n",
       "4                                                  NaN                 ...   \n",
       "..                                                 ...                 ...   \n",
       "395                                                0.0                 ...   \n",
       "396                                                5.0                 ...   \n",
       "397                                                0.0                 ...   \n",
       "398                                                0.0                 ...   \n",
       "399                                                0.0                 ...   \n",
       "\n",
       "     job.profession.sub_category_name.es  job.profession.sub_category_name.fr  \\\n",
       "0         Datos/Inteligencia empresarial        Données/Business Intelligence   \n",
       "1         Datos/Inteligencia empresarial        Données/Business Intelligence   \n",
       "2         Datos/Inteligencia empresarial        Données/Business Intelligence   \n",
       "3         Datos/Inteligencia empresarial        Données/Business Intelligence   \n",
       "4         Datos/Inteligencia empresarial        Données/Business Intelligence   \n",
       "..                                   ...                                  ...   \n",
       "395       Datos/Inteligencia empresarial        Données/Business Intelligence   \n",
       "396       Datos/Inteligencia empresarial        Données/Business Intelligence   \n",
       "397       Datos/Inteligencia empresarial        Données/Business Intelligence   \n",
       "398       Datos/Inteligencia empresarial        Données/Business Intelligence   \n",
       "399                    Banca y préstamos          Services bancaires et prêts   \n",
       "\n",
       "     job.profession.sub_category_name.sk  \\\n",
       "0           Údaje/obchodné spravodajstvo   \n",
       "1           Údaje/obchodné spravodajstvo   \n",
       "2           Údaje/obchodné spravodajstvo   \n",
       "3           Údaje/obchodné spravodajstvo   \n",
       "4           Údaje/obchodné spravodajstvo   \n",
       "..                                   ...   \n",
       "395         Údaje/obchodné spravodajstvo   \n",
       "396         Údaje/obchodné spravodajstvo   \n",
       "397         Údaje/obchodné spravodajstvo   \n",
       "398         Údaje/obchodné spravodajstvo   \n",
       "399        Bankovníctvo a úverové služby   \n",
       "\n",
       "     job.profession.sub_category_reference  job.contract_duration_max  \\\n",
       "0         data-business-intelligence-yZjY1                        NaN   \n",
       "1         data-business-intelligence-yZjY1                        NaN   \n",
       "2         data-business-intelligence-yZjY1                        NaN   \n",
       "3         data-business-intelligence-yZjY1                        NaN   \n",
       "4         data-business-intelligence-yZjY1                        NaN   \n",
       "..                                     ...                        ...   \n",
       "395       data-business-intelligence-yZjY1                        NaN   \n",
       "396       data-business-intelligence-yZjY1                        NaN   \n",
       "397       data-business-intelligence-yZjY1                        NaN   \n",
       "398       data-business-intelligence-yZjY1                        NaN   \n",
       "399              banking-and-lending-hZmQ3                        NaN   \n",
       "\n",
       "     job.organization.website_organization.i18n_descriptions.en  \\\n",
       "0                                                  NaN            \n",
       "1                                                                 \n",
       "2                                                  NaN            \n",
       "3    <p>At Hublo, <strong>we believe in the power o...            \n",
       "4    <p>Toucan is a customer-facing analytics platf...            \n",
       "..                                                 ...            \n",
       "395                                                NaN            \n",
       "396                                                NaN            \n",
       "397                                                NaN            \n",
       "398                                                NaN            \n",
       "399                                                NaN            \n",
       "\n",
       "    job.organization.equality_indexes job.featured_page  \\\n",
       "0                                 NaN               NaN   \n",
       "1                                 NaN               NaN   \n",
       "2                                 NaN               NaN   \n",
       "3                                 NaN               NaN   \n",
       "4                                 NaN               NaN   \n",
       "..                                ...               ...   \n",
       "395                               NaN               NaN   \n",
       "396                               NaN               NaN   \n",
       "397                               NaN               NaN   \n",
       "398                               NaN               NaN   \n",
       "399                               NaN               NaN   \n",
       "\n",
       "     job.organization.gdpr_setting  \\\n",
       "0                              NaN   \n",
       "1                              NaN   \n",
       "2                              NaN   \n",
       "3                              NaN   \n",
       "4                              NaN   \n",
       "..                             ...   \n",
       "395                            NaN   \n",
       "396                            NaN   \n",
       "397                            NaN   \n",
       "398                            NaN   \n",
       "399                            NaN   \n",
       "\n",
       "     job.organization.website_organization.i18n_descriptions.es  \n",
       "0                                                  NaN           \n",
       "1                                                  NaN           \n",
       "2                                                  NaN           \n",
       "3                                                  NaN           \n",
       "4                                                  NaN           \n",
       "..                                                 ...           \n",
       "395                                                NaN           \n",
       "396                                                NaN           \n",
       "397                                                NaN           \n",
       "398                                                NaN           \n",
       "399                                                NaN           \n",
       "\n",
       "[400 rows x 136 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 3.  je requête chaque URL et je stocke dans un dataframe ##\n",
    "\n",
    "# création d'une liste vide pour stocker les données JSON\n",
    "data_json = []\n",
    "\n",
    "for job_url in api_urls:\n",
    "    link = job_url\n",
    "    r = requests.get(link)\n",
    "    data_json.append(json.loads(r.text))                # comme j'itère sur chaque url je dois stocker ce résultat dans une liste\n",
    "    # print(json.dumps(data_json, indent=2))\n",
    "\n",
    "# j'en fais un dataframe\n",
    "df_jraw = pd.json_normalize(data_json)\n",
    "df_jraw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['job.salary_period', 'job.contract_type', 'job.application_fields',\n",
       "       'job.remote', 'job.is_default', 'job.apply_url', 'job.urls',\n",
       "       'job.updated_at', 'job.organization.nb_employees',\n",
       "       'job.organization.equality_indexes.equality_among_highest_earners',\n",
       "       ...\n",
       "       'job.profession.sub_category_name.es',\n",
       "       'job.profession.sub_category_name.fr',\n",
       "       'job.profession.sub_category_name.sk',\n",
       "       'job.profession.sub_category_reference', 'job.contract_duration_max',\n",
       "       'job.organization.website_organization.i18n_descriptions.en',\n",
       "       'job.organization.equality_indexes', 'job.featured_page',\n",
       "       'job.organization.gdpr_setting',\n",
       "       'job.organization.website_organization.i18n_descriptions.es'],\n",
       "      dtype='object', length=136)"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_jraw.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 4. je nettoie et je formate ## \n",
    "\n",
    "# 4.1 je drop toutes les colonnes dont je n'ai pas besoin\n",
    "df_jobs_temp = df_jraw.drop(columns=[\"job.slug\", \n",
    "                                   \"job.videos\", \n",
    "                                   \"job.updated_at\",\n",
    "                                   \"job.offices\",\n",
    "                                   \"job.apply_url\", \n",
    "                                   \"job.is_default\",\n",
    "                                   'job.organization.has_external_ats',\n",
    "                                   'job.organization.labels',\n",
    "                                   'job.organization.logo.url', \n",
    "                                   'job.organization.logo.thumb.url',\n",
    "                                   'job.organization.sectors',\n",
    "                                   'job.organization.cover_image.small.url',\n",
    "                                   'job.organization.cover_image.url',\n",
    "                                   'job.organization.cover_image.medium.url',\n",
    "                                   'job.organization.cover_image.large.url',\n",
    "                                   'job.organization.cover_image.social.url',\n",
    "                                   'job.organization.website_organization.slug',\n",
    "                                   'job.organization.website_organization.i18n_descriptions.fr',\n",
    "                                   'job.organization.gdpr_setting.application_message',\n",
    "                                   'job.organization.gdpr_setting.consent_duration',\n",
    "                                   'job.organization.gdpr_setting.privacy_policy_url',\n",
    "                                   'job.organization.media_website_url',\n",
    "                                   'job.organization.headquarter.address',\n",
    "                                   'job.organization.headquarter.local_address',\n",
    "                                   'job.organization.headquarter.city',\n",
    "                                   'job.organization.headquarter.latitude',\n",
    "                                   'job.organization.headquarter.longitude',\n",
    "                                   'job.organization.headquarter.district',\n",
    "                                   'job.organization.headquarter.country_code',\n",
    "                                   'job.organization.headquarter.zip_code',\n",
    "                                   'job.organization.headquarter.local_city',\n",
    "                                   'job.organization.headquarter.local_district',\n",
    "                                   'job.organization.media_facebook',\n",
    "                                   'job.organization.media_instagram',\n",
    "                                   'job.organization.media_linkedin',\n",
    "                                   'job.organization.media_pinterest',\n",
    "                                   'job.organization.media_twitter',\n",
    "                                   'job.organization.media_youtube',\n",
    "                                   'job.organization.playlist_id',\n",
    "                                   'job.organization.video_playlist_provider',\n",
    "                                   'job.organization.automatic_email',\n",
    "                                   'job.archived_at',\n",
    "                                   'job.profession.name.cs', 'job.profession.name.en',\n",
    "                                   'job.profession.name.es', 'job.profession.name.sk',\n",
    "                                   'job.profession.category.cs',\n",
    "                                   'job.profession.category.en', 'job.profession.category.es',\n",
    "                                   'job.profession.category.fr', 'job.profession.category.sk',\n",
    "                                   'job.profession.category_name.cs',\n",
    "                                   'job.profession.category_name.en',\n",
    "                                   'job.profession.category_name.es',\n",
    "                                   'job.profession.category_name.sk',\n",
    "                                   'job.profession.sub_category_name.cs',\n",
    "                                   'job.profession.sub_category_name.en',\n",
    "                                   'job.profession.sub_category_name.es',\n",
    "                                   'job.profession.sub_category_name.sk',\n",
    "                                   'job.profession.sub_category_reference',\n",
    "                                   'job.questions',\n",
    "                                   \"job.featured_page.type\",\n",
    "                                   'job.featured_page.slug',\n",
    "                                   'job.cta_content.links',\n",
    "                                   'job.cta_content.contents',\n",
    "                                   'job.organization.website_organization.i18n_descriptions.en',\n",
    "                                   'job.organization.website_organization.i18n_descriptions.es',\n",
    "                                   'job.status',\n",
    "                                   'job.profession.name.fr',\n",
    "                                   'job.organization.reference',\n",
    "                                   'job.organization.default_language',\n",
    "                                   'job.organization.parity_men',\n",
    "                                   'job.organization.revenue',\n",
    "                                   'job.organization.average_age',\n",
    "                                   'job.salary_currency',\n",
    "                                   'job.salary_period',\n",
    "                                   'job.profession.category_reference',\n",
    "                                   'job.office.address',\n",
    "                                   'job.office.local_address',\n",
    "                                   'job.office.district',\n",
    "                                   'job.office.country_code',\n",
    "                                   'job.office.local_city',\n",
    "                                   'job.office.local_district',\n",
    "                                   'job.language',\n",
    "                                   'job.start_date',\n",
    "                                   'job.recruitment_process',\n",
    "                                   'job.featured_page',\n",
    "                                   'job.organization.gdpr_setting',\n",
    "                                   'job.organization.gdpr_setting',\n",
    "                                   'job.organization.equality_indexes',\n",
    "                                   'job.organization.equality_indexes.equality_among_highest_earners',\n",
    "                                   'job.organization.equality_indexes.gap_in_annual_raises',\n",
    "                                   'job.organization.equality_indexes.gap_in_annual_raises_excluding_promotions',\n",
    "                                   'job.organization.equality_indexes.gap_in_promotions',\n",
    "                                   'job.organization.equality_indexes.gender_pay_gap',\n",
    "                                   'job.organization.equality_indexes.maternity_leave_return_raise',\n",
    "                                   'job.organization.equality_indexes.published',\n",
    "                                   'job.organization.equality_indexes.workforce_range',\n",
    "                                   'job.organization.equality_indexes.year',\n",
    "                                   'job.organization.turnover',\n",
    "                                   'job.organization.jobs_count',\n",
    "                                   'job.organization.website_organization.i18n_descriptions.en',\n",
    "                                   'job.benefits.FR.categories',\n",
    "                                   'job.benefits.FR.count',\n",
    "                                   'job.benefits.FR.preview',\n",
    "                                   'job.organization.website_organization.i18n_descriptions.es',\n",
    "                                   'job.apply_url',\n",
    "                                   \"job.organization.profile_type\",\n",
    "                                    'job.contract_duration_max',\n",
    "                                    'job.contract_duration_min',\n",
    "                                    'job.profession.category_name.fr',\n",
    "                                    'job.profession.sub_category_name.fr',\n",
    "                                    'job.wttj_reference',\n",
    "                                    'job.company_description',\n",
    "                                   ]\n",
    "                                   )\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Les fonctions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 4.2 je passe toutes mes fonctions\n",
    "\n",
    "# html cleaner\n",
    "### faire un if none pass sinon\n",
    "df_jobs_temp[[\"job.organization.description_clean\",\"job.profile_clean\", \"job.description_clean\"]] = df_jobs_temp[[\"job.organization.description\",\"job.profile\", \"job.description\"]].map(remove_html_tags).copy()\n",
    "\n",
    "# level bins cleaner\n",
    "df_jobs_temp[\"job.experience_level_clean\"] = df_jobs_temp[\"job.experience_level\"].astype(str).apply(lambda x: experience_replace(x))\n",
    "df_jobs_temp[\"job.education_level_clean\"] = df_jobs_temp[\"job.education_level\"].astype(str).apply(lambda x: experience_replace(x))\n",
    "\n",
    "# date convertor\n",
    "df_jobs_temp['job.organization.creation_year_date'] = df_jobs_temp['job.organization.creation_year'].apply(convert_year_to_date)\n",
    "\n",
    "# # tools extractor\n",
    "# df_jobs_temp[\"competences\"] = df_jobs_temp[\"job.tools\"].apply(jtools_extractor)\n",
    "\n",
    "# # skills extractor\n",
    "# df_jobs_temp[\"job.skills_clean\"] = df_jobs_temp[\"job.skills\"].apply(jskills_extractor)\n",
    "\n",
    "df_jobs_temp['competences'] = df_jobs_temp.apply(extract_competences, axis=1)\n",
    "\n",
    "# job urls extractor\n",
    "df_jobs_temp[\"job.urls_clean\"] = df_jobs_temp[\"job.urls\"].apply(jurls_extractor)\n",
    "\n",
    "# # application mandatories\n",
    "# df_jobs_temp[\"job.application_mandatory\"] = df_jobs_temp[\"job.application_fields\"].apply(appli_mandatory_extractor)\n",
    "\n",
    "# type de contrats\n",
    "df_jobs_temp['job.contract_type'] = df_jobs_temp['job.contract_type'].apply(contract_corrector)\n",
    "\n",
    "# départements\n",
    "df_jobs_temp[\"departement\"] = df_jobs_temp['job.office.zip_code'].astype(str).apply(dpt_extractor)\n",
    "\n",
    "# date de publication\n",
    "df_jobs_temp['date_publication'] = df_jobs_temp['job.published_at'].apply(convert_publication_date)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Je calcule le salaire moyen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_jobs_temp['salaire_avg'] = ((df_jobs_temp['job.salary_max'] + df_jobs_temp['job.salary_min']) / 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Je concatane dans description_job mes colonne job description et job profile\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_jobs_temp[\"description_job\"] = df_jobs_temp[\"job.description_clean\"].astype(str) + \" --- \" + df_jobs_temp[\"job.profile_clean\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "# display(df_jobs_temp[\"job.urls\"][0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Je continue de nettoyer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 4.3 puis je drop les colonnes que j'ai nettoyées\n",
    "df_jobs = df_jobs_temp.drop(columns=[\"job.skills\", \"job.tools\", \"job.application_fields\", \"job.profile\", \"job.organization.description\", \n",
    "                                     \"job.organization.creation_year\", \"job.urls\",'job.profile_clean', 'job.description_clean', \n",
    "                                   'job.description',\"job.organization.description\",'job.published_at','job.experience_level','job.education_level', 'job.office.zip_code',])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(400, 24)"
      ]
     },
     "execution_count": 353,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_jobs.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "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>job.contract_type</th>\n",
       "      <th>job.remote</th>\n",
       "      <th>job.organization.nb_employees</th>\n",
       "      <th>job.organization.equality_indexes.equality_index</th>\n",
       "      <th>job.organization.industry</th>\n",
       "      <th>job.organization.parity_women</th>\n",
       "      <th>job.organization.name</th>\n",
       "      <th>job.reference</th>\n",
       "      <th>job.salary_min</th>\n",
       "      <th>job.name</th>\n",
       "      <th>...</th>\n",
       "      <th>job.organization.description_clean</th>\n",
       "      <th>job.experience_level_clean</th>\n",
       "      <th>job.education_level_clean</th>\n",
       "      <th>job.organization.creation_year_date</th>\n",
       "      <th>competences</th>\n",
       "      <th>job.urls_clean</th>\n",
       "      <th>departement</th>\n",
       "      <th>date_publication</th>\n",
       "      <th>salaire_avg</th>\n",
       "      <th>description_job</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>CDI</td>\n",
       "      <td>partial</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT / Digital, Big Data</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Corail Analytics</td>\n",
       "      <td>CA_5AaNPzX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Data Analytics Engineer</td>\n",
       "      <td>...</td>\n",
       "      <td>Corail Analytics conseille les entreprises dan...</td>\n",
       "      <td>2 to 3 years</td>\n",
       "      <td>bac 5</td>\n",
       "      <td>2021</td>\n",
       "      <td>[Aircall, Github, Looker, Tableau, Dbt, Airbyt...</td>\n",
       "      <td>https://www.welcometothejungle.com/fr/companie...</td>\n",
       "      <td>75</td>\n",
       "      <td>2024-06-18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Corail Analytics, founded in February 2021, is...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343</th>\n",
       "      <td>CDI</td>\n",
       "      <td>no</td>\n",
       "      <td>270.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Organization / Management, Strategy, Change Ma...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>Bartle</td>\n",
       "      <td>BARTL_DbRowzm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Consultant Senior Data Scientist H/F</td>\n",
       "      <td>...</td>\n",
       "      <td>Cabinet de conseil en management interdiscipli...</td>\n",
       "      <td>3 to 4 years</td>\n",
       "      <td>bac 5</td>\n",
       "      <td>2005</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.welcometothejungle.com/fr/companie...</td>\n",
       "      <td>75</td>\n",
       "      <td>2024-06-03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Au sein de l’équipe Bartle Analytics, vous int...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>CDI</td>\n",
       "      <td>no</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT / Digital</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Micropole</td>\n",
       "      <td>MICRO_AKLWM6Q</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Consultant Data Gouvernance - F/H</td>\n",
       "      <td>...</td>\n",
       "      <td>Micropole est accélérateur de la transformatio...</td>\n",
       "      <td>2 to 3 years</td>\n",
       "      <td>bac 5</td>\n",
       "      <td>1987</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.welcometothejungle.com/fr/companie...</td>\n",
       "      <td>69</td>\n",
       "      <td>2024-06-22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>En résumé :Poste : Consultant Data Gouvernance...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    job.contract_type job.remote  job.organization.nb_employees  \\\n",
       "362               CDI    partial                            4.0   \n",
       "343               CDI         no                          270.0   \n",
       "360               CDI         no                         1200.0   \n",
       "\n",
       "     job.organization.equality_indexes.equality_index  \\\n",
       "362                                               NaN   \n",
       "343                                              88.0   \n",
       "360                                               NaN   \n",
       "\n",
       "                             job.organization.industry  \\\n",
       "362                             IT / Digital, Big Data   \n",
       "343  Organization / Management, Strategy, Change Ma...   \n",
       "360                                       IT / Digital   \n",
       "\n",
       "     job.organization.parity_women job.organization.name  job.reference  \\\n",
       "362                            NaN      Corail Analytics     CA_5AaNPzX   \n",
       "343                           55.0                Bartle  BARTL_DbRowzm   \n",
       "360                            NaN             Micropole  MICRO_AKLWM6Q   \n",
       "\n",
       "     job.salary_min                              job.name  ...  \\\n",
       "362             NaN               Data Analytics Engineer  ...   \n",
       "343             NaN  Consultant Senior Data Scientist H/F  ...   \n",
       "360             NaN     Consultant Data Gouvernance - F/H  ...   \n",
       "\n",
       "                    job.organization.description_clean  \\\n",
       "362  Corail Analytics conseille les entreprises dan...   \n",
       "343  Cabinet de conseil en management interdiscipli...   \n",
       "360  Micropole est accélérateur de la transformatio...   \n",
       "\n",
       "    job.experience_level_clean  job.education_level_clean  \\\n",
       "362               2 to 3 years                      bac 5   \n",
       "343               3 to 4 years                      bac 5   \n",
       "360               2 to 3 years                      bac 5   \n",
       "\n",
       "     job.organization.creation_year_date  \\\n",
       "362                                 2021   \n",
       "343                                 2005   \n",
       "360                                 1987   \n",
       "\n",
       "                                           competences  \\\n",
       "362  [Aircall, Github, Looker, Tableau, Dbt, Airbyt...   \n",
       "343                                               None   \n",
       "360                                               None   \n",
       "\n",
       "                                        job.urls_clean departement  \\\n",
       "362  https://www.welcometothejungle.com/fr/companie...          75   \n",
       "343  https://www.welcometothejungle.com/fr/companie...          75   \n",
       "360  https://www.welcometothejungle.com/fr/companie...          69   \n",
       "\n",
       "    date_publication salaire_avg  \\\n",
       "362       2024-06-18         NaN   \n",
       "343       2024-06-03         NaN   \n",
       "360       2024-06-22         NaN   \n",
       "\n",
       "                                       description_job  \n",
       "362  Corail Analytics, founded in February 2021, is...  \n",
       "343  Au sein de l’équipe Bartle Analytics, vous int...  \n",
       "360  En résumé :Poste : Consultant Data Gouvernance...  \n",
       "\n",
       "[3 rows x 24 columns]"
      ]
     },
     "execution_count": 354,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_jobs.sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 400 entries, 0 to 399\n",
      "Data columns (total 24 columns):\n",
      " #   Column                                            Non-Null Count  Dtype  \n",
      "---  ------                                            --------------  -----  \n",
      " 0   job.contract_type                                 400 non-null    object \n",
      " 1   job.remote                                        400 non-null    object \n",
      " 2   job.organization.nb_employees                     394 non-null    float64\n",
      " 3   job.organization.equality_indexes.equality_index  256 non-null    float64\n",
      " 4   job.organization.industry                         400 non-null    object \n",
      " 5   job.organization.parity_women                     262 non-null    float64\n",
      " 6   job.organization.name                             400 non-null    object \n",
      " 7   job.reference                                     400 non-null    object \n",
      " 8   job.salary_min                                    49 non-null     float64\n",
      " 9   job.name                                          400 non-null    object \n",
      " 10  job.salary_max                                    48 non-null     float64\n",
      " 11  job.office.city                                   400 non-null    object \n",
      " 12  job.office.latitude                               382 non-null    float64\n",
      " 13  job.office.longitude                              382 non-null    float64\n",
      " 14  job.organization.description_clean                400 non-null    object \n",
      " 15  job.experience_level_clean                        400 non-null    object \n",
      " 16  job.education_level_clean                         400 non-null    object \n",
      " 17  job.organization.creation_year_date               378 non-null    object \n",
      " 18  competences                                       275 non-null    object \n",
      " 19  job.urls_clean                                    400 non-null    object \n",
      " 20  departement                                       397 non-null    object \n",
      " 21  date_publication                                  400 non-null    object \n",
      " 22  salaire_avg                                       48 non-null     float64\n",
      " 23  description_job                                   279 non-null    object \n",
      "dtypes: float64(8), object(16)\n",
      "memory usage: 75.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df_jobs.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Je renomme mes colonnes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_jobs2 = df_jobs.rename(columns={\"job.contract_type\": \"contrat\", \n",
    "                                   \"job.remote\": \"teletravail\", \n",
    "                                   \"job.organization.nb_employees\": \"nb_employes\", \n",
    "                                   \"job.organization.equality_indexes.equality_index\": \"index_egalite\",\n",
    "                                   'job.organization.industry': \"secteur\", \n",
    "                                   'job.organization.parity_women': \"repartition_genre\",\n",
    "                                   'job.organization.name': \"nom_entreprise\",\n",
    "                                   'job.reference': \"reference\",\n",
    "                                   'job.salary_min': \"salaire_min\", \n",
    "                                   'job.name': \"nom_emploi\", \n",
    "                                   'job.organization.description_clean': \"description_cie\",\n",
    "                                   'job.salary_max': \"salaire_max\", \n",
    "                                   'job.office.city': \"ville\", \n",
    "                                   'job.office.latitude': \"office_latitude\",\n",
    "                                   'job.office.longitude': \"office_longitude\", \n",
    "                                   'job.experience_level_clean': \"niveau_experience\",\n",
    "                                   'job.education_level_clean': \"niveau_etudes\", \n",
    "                                   'job.organization.creation_year_date': \"company_creation\",\n",
    "                                   'job.urls_clean': \"url\",\n",
    "                                   })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_jobs2[\"impact\"] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 400 entries, 0 to 399\n",
      "Data columns (total 25 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   contrat            400 non-null    object \n",
      " 1   teletravail        400 non-null    object \n",
      " 2   nb_employes        394 non-null    float64\n",
      " 3   index_egalite      256 non-null    float64\n",
      " 4   secteur            400 non-null    object \n",
      " 5   repartition_genre  262 non-null    float64\n",
      " 6   nom_entreprise     400 non-null    object \n",
      " 7   reference          400 non-null    object \n",
      " 8   salaire_min        49 non-null     float64\n",
      " 9   nom_emploi         400 non-null    object \n",
      " 10  salaire_max        48 non-null     float64\n",
      " 11  ville              400 non-null    object \n",
      " 12  office_latitude    382 non-null    float64\n",
      " 13  office_longitude   382 non-null    float64\n",
      " 14  description_cie    400 non-null    object \n",
      " 15  niveau_experience  400 non-null    object \n",
      " 16  niveau_etudes      400 non-null    object \n",
      " 17  company_creation   378 non-null    object \n",
      " 18  competences        275 non-null    object \n",
      " 19  url                400 non-null    object \n",
      " 20  departement        397 non-null    object \n",
      " 21  date_publication   400 non-null    object \n",
      " 22  salaire_avg        48 non-null     float64\n",
      " 23  description_job    279 non-null    object \n",
      " 24  impact             0 non-null      float64\n",
      "dtypes: float64(9), object(16)\n",
      "memory usage: 78.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df_jobs2.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Je réordonne les colonnes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_wtjj = df_jobs2[['nom_entreprise',\n",
    "                   'nom_emploi',\n",
    "                    'description_cie',\n",
    "                    'description_job',\n",
    "                    'salaire_min',\n",
    "                    'salaire_max',\n",
    "                    'salaire_avg',\n",
    "                    'ville',\n",
    "                    'departement',\n",
    "                    'contrat',\n",
    "                    'niveau_experience',\n",
    "                    'niveau_etudes',\n",
    "                    'teletravail',\n",
    "                    'competences',\n",
    "                    'date_publication',\n",
    "                    'secteur',\n",
    "                    'nb_employes',\n",
    "                    'url',\n",
    "                    'impact',\n",
    "                    'index_egalite',\n",
    "                    'repartition_genre',\n",
    "                    'company_creation',\n",
    "                    'reference',\n",
    "                    'office_latitude',\n",
    "                    'office_longitude']]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 400 entries, 0 to 399\n",
      "Data columns (total 25 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   nom_entreprise     400 non-null    object \n",
      " 1   nom_emploi         400 non-null    object \n",
      " 2   description_cie    400 non-null    object \n",
      " 3   description_job    279 non-null    object \n",
      " 4   salaire_min        49 non-null     float64\n",
      " 5   salaire_max        48 non-null     float64\n",
      " 6   salaire_avg        48 non-null     float64\n",
      " 7   ville              400 non-null    object \n",
      " 8   departement        397 non-null    object \n",
      " 9   contrat            400 non-null    object \n",
      " 10  niveau_experience  400 non-null    object \n",
      " 11  niveau_etudes      400 non-null    object \n",
      " 12  teletravail        400 non-null    object \n",
      " 13  competences        275 non-null    object \n",
      " 14  date_publication   400 non-null    object \n",
      " 15  secteur            400 non-null    object \n",
      " 16  nb_employes        394 non-null    float64\n",
      " 17  url                400 non-null    object \n",
      " 18  impact             0 non-null      float64\n",
      " 19  index_egalite      256 non-null    float64\n",
      " 20  repartition_genre  262 non-null    float64\n",
      " 21  company_creation   378 non-null    object \n",
      " 22  reference          400 non-null    object \n",
      " 23  office_latitude    382 non-null    float64\n",
      " 24  office_longitude   382 non-null    float64\n",
      "dtypes: float64(9), object(16)\n",
      "memory usage: 78.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df_wtjj.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Je fais les exports csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 5. j'exporte en csv avec date et heure du moment\n",
    "\n",
    "# today = date.today()\n",
    "now = datetime.now()\n",
    "\n",
    "# Étape 2: je formate la date dd-mm-hh-mn\n",
    "formatted_date = now.strftime(\"%d-%m_%H-%M\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 5.1. j'exporte le df complet pour la viz\n",
    "\n",
    "# Étape 3: j'ajoute la date au nom de fichier\n",
    "full_file = f\"fullwttj_{formatted_date}.csv\"\n",
    "\n",
    "df_wtjj.to_csv(full_file, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 5.2 j'exporte le df strict pour le site\n",
    "# pour cela je drop qq colonnes\n",
    "\n",
    "df_strict_wtjj = df_wtjj.drop(columns=['nom_entreprise',\n",
    "                   'nom_emploi',\n",
    "                    'description_cie',\n",
    "                    'description_job',\n",
    "                    'salaire_min',\n",
    "                    'salaire_max',\n",
    "                    'salaire_avg',\n",
    "                    'ville',\n",
    "                    'departement',\n",
    "                    'contrat',\n",
    "                    'niveau_experience',\n",
    "                    'niveau_etudes',\n",
    "                    'teletravail',\n",
    "                    'competences',\n",
    "                    'date_publication',\n",
    "                    'secteur',\n",
    "                    'nb_employes',\n",
    "                    'url',\n",
    "                    'impact',\n",
    "                    'index_egalite',\n",
    "                    'repartition_genre'])\n",
    "\n",
    "# Étape 3: j'ajoute la date au nom de fichier\n",
    "strict_file = f\"strictwttj_{formatted_date}.csv\"\n",
    "\n",
    "df_wtjj.to_csv(strict_file, index=False)"
   ]
  }
 ],
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