diff --git a/Exploration_billet_AJ.ipynb b/Exploration_billet_AJ.ipynb index 64402cd..3280f31 100644 --- a/Exploration_billet_AJ.ipynb +++ b/Exploration_billet_AJ.ipynb @@ -100,9 +100,7 @@ { "cell_type": "markdown", "id": "ccf597b0-b459-4ea5-baf0-5ba8c90915e4", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "# Cleaning target area and tags" ] @@ -406,7 +404,101 @@ "metadata": {}, "outputs": [], "source": [ - "#export_in_temporary(target_agg, 'Target_kpi_concatenate')" + "#export_inv_temporary(target_agg, 'Target_kpi_concatenate')" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "9d224485-3472-4cc7-9825-1a643bc94fef", + "metadata": {}, + "outputs": [], + "source": [ + "nb_compagnie = ['1', '2']\n", + "\n", + "def load_files(nb_compagnie):\n", + " targets = pd.DataFrame()\n", + " \n", + " # début de la boucle permettant de générer des datasets agrégés pour les 5 compagnies de spectacle\n", + " for directory_path in nb_compagnie:\n", + " df_customerplus_clean_0 = display_input_databases(directory_path, file_name = \"customerplus_cleaned\")\n", + " df_target_information = display_input_databases(directory_path, file_name = \"target_information\")\n", + " \n", + " df_target_KPI = targets_KPI(df_target = df_target_information)\n", + " df_target_KPI = pd.merge(df_customerplus_clean_0[['customer_id']], df_target_KPI, how = 'left', on = 'customer_id')\n", + "\n", + " targets_columns = list(df_target_KPI.columns)\n", + " targets_columns.remove('customer_id')\n", + " df_target_KPI[targets_columns] = df_target_KPI[targets_columns].fillna(0)\n", + " \n", + " # creation de la colonne Number compagnie, qui permettra d'agréger les résultats\n", + " df_target_KPI[\"number_company\"]=int(directory_path)\n", + " \n", + " # Traitement des index\n", + " df_target_KPI[\"customer_id\"]= directory_path + '_' + df_target_KPI['customer_id'].astype('str')\n", + " \n", + " # Concaténation\n", + " targets = pd.concat([targets, df_target_KPI], ignore_index=True)\n", + " \n", + " return targets" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "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", + "\n", + " plot = describe_target[['prop_target_jeune', 'prop_target_scolaire', 'prop_target_entreprise', 'prop_target_famille']].plot.bar()\n", + " \n", + " return plot" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "af62ecef-9120-4107-af3e-512588a96800", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "target_description(targets)" ] }, { @@ -546,9 +638,7 @@ { "cell_type": "markdown", "id": "ca2c8b6a-4965-422e-ba7c-66423a464fc1", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## Base communes au types Musée" ] @@ -781,9 +871,7 @@ { "cell_type": "markdown", "id": "76bffba1-5f7e-4308-9224-437ca66148f8", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## KPI sur target_type" ]