diff --git a/Exploration_billet_AJ.ipynb b/Exploration_billet_AJ.ipynb index 3280f31..886aaae 100644 --- a/Exploration_billet_AJ.ipynb +++ b/Exploration_billet_AJ.ipynb @@ -397,6 +397,170 @@ "targets_KPI(display_input_databases('5', file_name = \"target_information\"))" ] }, + { + "cell_type": "code", + "execution_count": 35, + "id": "7bbca184-1ec1-43b5-ba50-c5e8343d52e7", + "metadata": {}, + "outputs": [], + "source": [ + "def targets_name_category(df_target=None):\n", + " if df_target is None:\n", + " return None\n", + " \n", + " df_target['target_name'] = df_target['target_name'].fillna('').str.lower()\n", + "\n", + " # Target name category for museums\n", + " df_target['target_jeune'] = df_target['target_name'].str.contains('|'.join(['jeune', 'pass_culture', 'etudiant', '12-25 ans', 'student', 'jeunesse']), case=False).astype(int)\n", + " df_target['target_optin'] = df_target['target_name'].str.contains('|'.join(['optin', 'opt-in']), case=False).astype(int)\n", + " df_target['target_optout'] = df_target['target_name'].str.contains('|'.join(['optout', 'unsubscribed']), case=False).astype(int)\n", + " df_target['target_scolaire'] = df_target['target_name'].str.contains('|'.join(['scolaire', 'enseignant', 'chercheur', 'schulen', 'école']), case=False).astype(int)\n", + " df_target['target_entreprise'] = df_target['target_name'].str.contains('|'.join(['b2b', 'btob', 'cse']), case=False).astype(int)\n", + " df_target['target_famille'] = df_target['target_name'].str.contains('|'.join(['famille', 'enfants', 'family']), case=False).astype(int)\n", + " df_target['target_newsletter'] = df_target['target_name'].str.contains('|'.join(['nl', 'newsletter']), case=False).astype(int)\n", + " \n", + " # Target name category for sport companies\n", + " df_target['target_abonne'] = ((df_target['target_name']\n", + " .str.contains('|'.join(['abo', 'adh']), case=False)\n", + " & ~df_target['target_name'].str.contains('|'.join(['hors abo', 'anciens abo']), case=False))\n", + " .astype(int))\n", + "\n", + " list_target_jeune = df_target[df_target['target_jeune'] == 1]['target_name'].unique()\n", + " list_target_optin = df_target[df_target['target_optin'] == 1]['target_name'].unique()\n", + " list_target_optout = df_target[df_target['target_optout'] == 1]['target_name'].unique()\n", + " list_target_scolaire = df_target[df_target['target_scolaire'] == 1]['target_name'].unique()\n", + " list_target_entreprise = df_target[df_target['target_entreprise'] == 1]['target_name'].unique()\n", + " list_target_famille = df_target[df_target['target_famille'] == 1]['target_name'].unique()\n", + " list_target_newsletter = df_target[df_target['target_newsletter'] == 1]['target_name'].unique()\n", + " list_target_abonne = df_target[df_target['target_abonne'] == 1]['target_name'].unique()\n", + "\n", + " list_all = [list_target_jeune, list_target_optin, list_target_optout, list_target_scolaire,\n", + " list_target_entreprise, list_target_famille, list_target_newsletter, list_target_abonne]\n", + "\n", + " category_name = ['target_jeune', 'target_optin', 'target_optout', 'target_scolaire',\n", + " 'target_entreprise', 'target_famille', 'target_newsletter', 'target_abonne']\n", + " \n", + " liste_category = pd.DataFrame({'category_name': category_name,\n", + " 'list_target_name': list_all})\n", + " \n", + " return liste_category\n" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "fbabcf4d-3ee6-4441-b231-d7ef24b7f160", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "File path : projet-bdc2324-team1/0_Input/Company_7/target_information.csv\n" + ] + }, + { + "data": { + "text/html": [ + "
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category_namelist_target_name
0target_jeune[jeunesses vaudoises, etudiant hors ssc 22-23, student supporter club, etudiants hors epfl, student supporter club ehl, etudiants]
1target_optin[]
2target_optout[]
3target_scolaire[]
4target_entreprise[prospects b2b, prospects survey b2b, b2b à enlever, prospect b2b fc 06.10, prospect b2b rk 06.10]
5target_famille[family corner - 20.11.22, family corner - saison 19-20]
6target_newsletter[consentements nl lhc, newsletter 2022, b2b à enlever, abonnés newsletter - saison 21-22]
7target_abonne[abonnés 23/24, non renouvellement abo 23-24 debout (23.06), résas abos debout - 29.06, abonnés - assis, sondage reconduction abos, sondage nouveaux abos, abonnés b2c - relance 1, abonnés b2c - relance 2, relance abos assis, non renouvellement abo 23-24 assis (23.06), résas abos assis - 29.06, abonnés - playoffs, abonnés - debout, abonnés non vip - saison 22-23, avantage abonné - ticket, paiements abos, campagneabosconcours - abonnés 21-22 en attente, campagneabosconcours - abonnés 22-23, nouveaux abonnés - saison 22-23, abonnements - relance 15.04, abonnements - relance 13.04, abonnements - relance 11.04, abonnements - relance 07.04, abonnés newsletter - saison 21-22, abonnés 1-3 ans, abonnés 1-3 ans - relance, abonnés - non-renouvellement 22-23, abonnés - renoncement playoffs 22, abonnés 5 ans - relance, abonnés - version finale]
\n", + "
" + ], + "text/plain": [ + " category_name \\\n", + "0 target_jeune \n", + "1 target_optin \n", + "2 target_optout \n", + "3 target_scolaire \n", + "4 target_entreprise \n", + "5 target_famille \n", + "6 target_newsletter \n", + "7 target_abonne \n", + "\n", + " list_target_name \n", + "0 [jeunesses vaudoises, etudiant hors ssc 22-23, student supporter club, etudiants hors epfl, student supporter club ehl, etudiants] \n", + "1 [] \n", + "2 [] \n", + "3 [] \n", + "4 [prospects b2b, prospects survey b2b, b2b à enlever, prospect b2b fc 06.10, prospect b2b rk 06.10] \n", + "5 [family corner - 20.11.22, family corner - saison 19-20] \n", + "6 [consentements nl lhc, newsletter 2022, b2b à enlever, abonnés newsletter - saison 21-22] \n", + "7 [abonnés 23/24, non renouvellement abo 23-24 debout (23.06), résas abos debout - 29.06, abonnés - assis, sondage reconduction abos, sondage nouveaux abos, abonnés b2c - relance 1, abonnés b2c - relance 2, relance abos assis, non renouvellement abo 23-24 assis (23.06), résas abos assis - 29.06, abonnés - playoffs, abonnés - debout, abonnés non vip - saison 22-23, avantage abonné - ticket, paiements abos, campagneabosconcours - abonnés 21-22 en attente, campagneabosconcours - abonnés 22-23, nouveaux abonnés - saison 22-23, abonnements - relance 15.04, abonnements - relance 13.04, abonnements - relance 11.04, abonnements - relance 07.04, abonnés newsletter - saison 21-22, abonnés 1-3 ans, abonnés 1-3 ans - relance, abonnés - non-renouvellement 22-23, abonnés - renoncement playoffs 22, abonnés 5 ans - relance, abonnés - version finale] " + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pd.set_option('display.max_colwidth', None)\n", + "targets_name_category(display_input_databases('7', file_name = \"target_information\"))" + ] + }, { "cell_type": "code", "execution_count": null, @@ -409,12 +573,33 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 6, "id": "9d224485-3472-4cc7-9825-1a643bc94fef", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "File path : projet-bdc2324-team1/0_Input/Company_5/customerplus_cleaned.csv\n", + "File path : projet-bdc2324-team1/0_Input/Company_5/target_information.csv\n", + "File path : projet-bdc2324-team1/0_Input/Company_6/customerplus_cleaned.csv\n", + "File path : projet-bdc2324-team1/0_Input/Company_6/target_information.csv\n", + "File path : projet-bdc2324-team1/0_Input/Company_7/customerplus_cleaned.csv\n", + "File path : projet-bdc2324-team1/0_Input/Company_7/target_information.csv\n", + "File path : projet-bdc2324-team1/0_Input/Company_8/customerplus_cleaned.csv\n", + "File path : projet-bdc2324-team1/0_Input/Company_8/target_information.csv\n", + "File path : projet-bdc2324-team1/0_Input/Company_9/customerplus_cleaned.csv\n", + "File path : projet-bdc2324-team1/0_Input/Company_9/target_information.csv\n" + ] + } + ], "source": [ - "nb_compagnie = ['1', '2']\n", + "companies = {'musee' : ['1', '2', '3', '4'], # , '101'\n", + " 'sport': ['5', '6', '7', '8', '9'],\n", + " 'musique' : ['10', '11', '12', '13', '14']}\n", + "\n", + "nb_compagnie = companies['sport']\n", "\n", "def load_files(nb_compagnie):\n", " targets = pd.DataFrame()\n", @@ -440,55 +625,68 @@ " # Concaténation\n", " targets = pd.concat([targets, df_target_KPI], ignore_index=True)\n", " \n", - " return targets" + " return targets\n", + "\n", + "targets = load_files(nb_compagnie)" ] }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 21, "id": "3c911274-0ebd-49af-9487-26524ba20e74", "metadata": {}, "outputs": [], "source": [ - "companies = {'musee' : ['1', '2', '3', '4'], # , '101'\n", - " 'sport': ['5', '6', '7', '8', '9'],\n", - " 'musique' : ['10', '11', '12', '13', '14']}\n", "\n", "def target_description(targets):\n", "\n", " describe_target = targets.groupby('number_company').agg(\n", " prop_target_jeune=('target_jeune', lambda x: (x.sum() / x.count())*100),\n", - " prop_target_optin=('target_optin', lambda x: (x.sum() / x.count())*100),\n", - " prop_target_optout=('target_optout', lambda x: (x.sum() / x.count())*100),\n", " prop_target_scolaire=('target_scolaire', lambda x: (x.sum() / x.count())*100),\n", " prop_target_entreprise=('target_entreprise', lambda x: (x.sum() / x.count())*100),\n", " prop_target_famille=('target_famille', lambda x: (x.sum() / x.count())*100),\n", - " prop_target_newsletter=('target_newsletter', lambda x: (x.sum() / x.count())*100))\n", + " prop_target_optin=('target_optin', lambda x: (x.sum() / x.count())*100),\n", + " prop_target_optout=('target_optout', lambda x: (x.sum() / x.count())*100),\n", + " prop_target_newsletter=('target_newsletter', lambda x: (x.sum() / x.count())*100),\n", + " prop_target_abonne=('target_abonne', lambda x: (x.sum() / x.count())*100))\n", "\n", - " plot = describe_target[['prop_target_jeune', 'prop_target_scolaire', 'prop_target_entreprise', 'prop_target_famille']].plot.bar()\n", + " plot = describe_target.plot.bar()\n", " \n", + " # Adding a title\n", + " plot.set_title(\"Distribution of Targets by Category\")\n", + " \n", + " # Adding labels for x and y axes\n", + " plot.set_xlabel(\"Company Number\")\n", + " plot.set_ylabel(\"Target Proportion\")\n", + "\n", + " plot.set_xticklabels(plot.get_xticklabels(), rotation=0, horizontalalignment='center')\n", + "\n", + " \n", + " # Adding a legend\n", + " plot.legend([\"Youth\", \"School\", \"Enterprise\", \"Family\", \"Optin\", \"Optout\", \"Newsletter\", \"Subscriber\"], title=\"Target Category\")\n", + "\n", " return plot" ] }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 22, "id": "af62ecef-9120-4107-af3e-512588a96800", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 51, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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