Ajout de statistiques sur les tags
This commit is contained in:
parent
1667f99a83
commit
da1f16d8ec
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@ -91,6 +91,18 @@
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" return df"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 56,
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"id": "09daec01-9927-45c7-a6d4-9b9d0340ee02",
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"metadata": {},
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"outputs": [],
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"source": [
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"companies = {'musee' : ['1', '2', '3', '4', '101'],\n",
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" 'sport': ['5', '6', '7', '8', '9'],\n",
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" 'musique' : ['10', '11', '12', '13', '14']}"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ae3c0c33-55a7-4a28-9a62-3ce13496917a",
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@ -3767,13 +3779,223 @@
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d679204b-f3e8-4502-8de9-3bf4180da3bd",
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"metadata": {},
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"source": [
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"# 2 - Autres informations sur client "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dc071992-cf4d-4b9f-9c3b-3f0e98e20eff",
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"execution_count": 57,
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"id": "1df2a145-f47f-4511-aa76-0df7531dd2ec",
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"metadata": {},
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"outputs": [],
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"source": []
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"source": [
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"def tags_information(tenant_id, first_tags = 20):\n",
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"\n",
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" customersplus = load_dataset_2(tenant_id, \"customersplus\")[['id', 'structure_id']]\n",
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" customersplus.rename(columns = {'id' : 'customer_id'}, inplace = True)\n",
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" tags = load_dataset_2(tenant_id, \"tags\")[['id', 'name']]\n",
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" tags.rename(columns = {'id' : 'tag_id', 'name' : 'tag_name'}, inplace = True)\n",
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" structure_tag_mappings = load_dataset_2(tenant_id, \"structure_tag_mappings\")[['structure_id', 'tag_id']]\n",
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" \n",
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" customer_tags = pd.merge(customersplus, structure_tag_mappings, on = 'structure_id', how = 'left')\n",
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" customer_tags = pd.merge(customer_tags, tags, on = 'tag_id', how = 'inner')\n",
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" \n",
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" nb_customers_with_tag = customer_tags['customer_id'].nunique()\n",
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" \n",
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" # print('Nombre de client avec tag : ', nb_customers_with_tag)\n",
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" # print('Proportion de clients avec tags : ', nb_customers_with_tag/len(customersplus))\n",
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" # print('Moyenne de tags par client : ', len(customer_tags)/nb_customers_with_tag)\n",
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" \n",
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" # info = customer_tags.groupby(['tag_id', 'tag_name'])['customer_id'].count().reset_index().sort_values('customer_id', ascending = False).head(first_tags)\n",
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"\n",
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" tags_informations = pd.DataFrame({'company_number' : tenant_id,\n",
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" 'nb_customers_with_tags' : [nb_customers_with_tag],\n",
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" 'prop_customers_with_tags' : [nb_customers_with_tag/len(customersplus)],\n",
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" 'mean_tags_per_customers' : [len(customer_tags)/nb_customers_with_tag]})\n",
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" \n",
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" return tags_informations"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 58,
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"id": "c4ecbb15-0f55-46dc-a3df-6e8c4ae44ebd",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Nombre de client avec tag : 13320\n",
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"Proportion de clients avec tags : 0.0877089012682233\n",
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"Moyenne de tags par client : 2.1725975975975977\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/tmp/ipykernel_467/1769900082.py:8: DtypeWarning: Columns (20) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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" df = pd.read_csv(file_in, sep=\",\")\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Nombre de client avec tag : 5953\n",
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"Proportion de clients avec tags : 0.021598421025897787\n",
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"Moyenne de tags par client : 1.0\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/tmp/ipykernel_467/1769900082.py:8: DtypeWarning: Columns (19,20) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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" df = pd.read_csv(file_in, sep=\",\")\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Nombre de client avec tag : 23659\n",
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"Proportion de clients avec tags : 0.09207484608139978\n",
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"Moyenne de tags par client : 3.0620482691576143\n",
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"Nombre de client avec tag : 10495\n",
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"Proportion de clients avec tags : 0.03271416949025744\n",
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"Moyenne de tags par client : 5.298427822772749\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/tmp/ipykernel_467/1769900082.py:8: DtypeWarning: Columns (20) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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" df = pd.read_csv(file_in, sep=\",\")\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Nombre de client avec tag : 532342\n",
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"Proportion de clients avec tags : 0.18660686931118298\n",
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"Moyenne de tags par client : 24.114082676174338\n"
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]
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}
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],
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"source": [
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"tags_comparaison = pd.DataFrame()\n",
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"\n",
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"for tenant_id in companies['musee'] : \n",
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" \n",
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" tags_comparaison = pd.concat([tags_comparaison, tags_information(tenant_id)])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 59,
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"id": "bd2dd513-3375-4073-a12a-fa0e9f20571e",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>company_number</th>\n",
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" <th>nb_customers_with_tags</th>\n",
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" <th>prop_customers_with_tags</th>\n",
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" <th>mean_tags_per_customers</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>1</td>\n",
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" <td>13320</td>\n",
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" <td>0.087709</td>\n",
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" <td>2.172598</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>2</td>\n",
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" <td>5953</td>\n",
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" <td>0.021598</td>\n",
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" <td>1.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>3</td>\n",
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" <td>23659</td>\n",
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" <td>0.092075</td>\n",
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" <td>3.062048</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>4</td>\n",
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" <td>10495</td>\n",
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" <td>0.032714</td>\n",
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" <td>5.298428</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>101</td>\n",
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" <td>532342</td>\n",
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" <td>0.186607</td>\n",
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" <td>24.114083</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" company_number nb_customers_with_tags prop_customers_with_tags \\\n",
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"0 1 13320 0.087709 \n",
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"0 2 5953 0.021598 \n",
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"0 3 23659 0.092075 \n",
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"0 4 10495 0.032714 \n",
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"0 101 532342 0.186607 \n",
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"\n",
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" mean_tags_per_customers \n",
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"0 2.172598 \n",
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"0 1.000000 \n",
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"0 3.062048 \n",
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"0 5.298428 \n",
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"0 24.114083 "
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]
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},
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"execution_count": 59,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"tags_comparaison"
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]
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}
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],
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"metadata": {
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@ -473,9 +473,7 @@
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{
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"cell_type": "markdown",
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"id": "605cced5-052f-4a99-ac26-020c5d2ab633",
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"metadata": {
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"jp-MarkdownHeadingCollapsed": true
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},
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"metadata": {},
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"source": [
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"## KPI sur tags"
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]
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