Ajout régression logistique
This commit is contained in:
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@ -2457,24 +2457,24 @@
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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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"execution_count": 37,
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"id": "a89fad43-ee68-4081-9384-3e9f08ec6a59",
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"metadata": {},
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"outputs": [],
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"source": [
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"df1_customer_product = pd.merge(df1_customer, nb_tickets, on = 'customer_id', how = 'left')\n",
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"print(\"shape : \", df1_customer_product.shape)\n",
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"df1_customer_product.head()"
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"# df1_customer_product = pd.merge(df1_customer, nb_tickets, on = 'customer_id', how = 'left')\n",
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"# print(\"shape : \", df1_customer_product.shape)\n",
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"# df1_customer_product.head()"
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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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"execution_count": 38,
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"id": "a19fec00-4ece-400c-937c-ce5cd8daccfd",
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"metadata": {},
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"outputs": [],
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"source": [
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"df1_customer_product.to_csv(\"customer_product.csv\", index = False)"
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"# df1_customer_product.to_csv(\"customer_product.csv\", index = False)"
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]
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},
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{
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@ -2487,7 +2487,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 38,
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"execution_count": 39,
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"id": "46de1912-4a66-46e5-8b9e-7768b2d2723b",
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"metadata": {},
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"outputs": [],
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@ -2501,7 +2501,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 39,
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"execution_count": 40,
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"id": "d53825e4-6453-45bc-94f2-7b2504ec4afb",
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"metadata": {},
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"outputs": [
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@ -2707,7 +2707,7 @@
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"[5 rows x 28 columns]"
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]
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},
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"execution_count": 39,
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"execution_count": 40,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -2718,7 +2718,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 40,
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"execution_count": 41,
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"id": "1e42a790-b215-4107-a969-85005da06ebd",
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"metadata": {},
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"outputs": [],
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@ -2732,405 +2732,68 @@
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},
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{
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"cell_type": "code",
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"execution_count": 41,
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"execution_count": 42,
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"id": "d950f24d-a5d1-4f1e-aeaa-ca826470365f",
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"text/plain": [
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" customer_id event_type_id nb_tickets nb_purchases total_amount \\\n",
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"1 1 4.0 453242.0 228945.0 3248965.5 \n",
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"3 1 6.0 217356.0 111786.0 1435871.5 \n",
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"... ... ... ... ... ... \n",
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"\n",
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" nb_suppliers vente_internet_max purchase_date_min \\\n",
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"0 7.0 1.0 3262.190868 \n",
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"1 6.0 1.0 3698.198229 \n",
|
||||
"2 6.0 1.0 3803.369792 \n",
|
||||
"3 5.0 1.0 2502.715509 \n",
|
||||
"4 1.0 0.0 2041.274549 \n",
|
||||
"... ... ... ... \n",
|
||||
"156291 1.0 1.0 0.110521 \n",
|
||||
"156292 1.0 1.0 0.092095 \n",
|
||||
"156293 1.0 1.0 0.087894 \n",
|
||||
"156294 1.0 1.0 0.040394 \n",
|
||||
"156295 1.0 1.0 0.000000 \n",
|
||||
"\n",
|
||||
" purchase_date_max time_between_purchase ... average_ticket_basket \\\n",
|
||||
"0 4.179306 3258.011562 ... 1.956087 \n",
|
||||
"1 5.221840 3692.976389 ... 1.956087 \n",
|
||||
"2 0.146331 3803.223461 ... 1.956087 \n",
|
||||
"3 1408.715532 1093.999977 ... 1.956087 \n",
|
||||
"4 1340.308160 700.966389 ... 1.000000 \n",
|
||||
"... ... ... ... ... \n",
|
||||
"156291 0.110521 0.000000 ... NaN \n",
|
||||
"156292 0.092095 0.000000 ... NaN \n",
|
||||
"156293 0.087894 0.000000 ... NaN \n",
|
||||
"156294 0.040394 0.000000 ... NaN \n",
|
||||
"156295 0.000000 0.000000 ... NaN \n",
|
||||
"\n",
|
||||
" total_price purchase_count first_buying_date country age \\\n",
|
||||
"0 8821221.5 641472.0 2013-06-10 10:37:58+00:00 fr NaN \n",
|
||||
"1 8821221.5 641472.0 2013-06-10 10:37:58+00:00 fr NaN \n",
|
||||
"2 8821221.5 641472.0 2013-06-10 10:37:58+00:00 fr NaN \n",
|
||||
"3 8821221.5 641472.0 2013-06-10 10:37:58+00:00 fr NaN \n",
|
||||
"4 0.0 307.0 2018-04-07 12:55:07+00:00 fr NaN \n",
|
||||
"... ... ... ... ... .. \n",
|
||||
"156291 NaN NaN NaT NaN NaN \n",
|
||||
"156292 NaN NaN NaT NaN NaN \n",
|
||||
"156293 NaN NaN NaT NaN NaN \n",
|
||||
"156294 NaN NaN NaT NaN NaN \n",
|
||||
"156295 NaN NaN NaT NaN NaN \n",
|
||||
"\n",
|
||||
" tenant_id nb_campaigns nb_campaigns_opened time_to_open \n",
|
||||
"0 1311.0 0.0 0.0 NaT \n",
|
||||
"1 1311.0 0.0 0.0 NaT \n",
|
||||
"2 1311.0 0.0 0.0 NaT \n",
|
||||
"3 1311.0 0.0 0.0 NaT \n",
|
||||
"4 1311.0 4.0 0.0 NaT \n",
|
||||
"... ... ... ... ... \n",
|
||||
"156291 NaN NaN NaN NaT \n",
|
||||
"156292 NaN NaN NaN NaT \n",
|
||||
"156293 NaN NaN NaN NaT \n",
|
||||
"156294 NaN NaN NaN NaT \n",
|
||||
"156295 NaN NaN NaN NaT \n",
|
||||
"\n",
|
||||
"[156296 rows x 40 columns]"
|
||||
"customer_id 0\n",
|
||||
"event_type_id 78355\n",
|
||||
"nb_tickets 0\n",
|
||||
"nb_purchases 0\n",
|
||||
"total_amount 0\n",
|
||||
"nb_suppliers 0\n",
|
||||
"vente_internet_max 0\n",
|
||||
"purchase_date_min 78355\n",
|
||||
"purchase_date_max 78355\n",
|
||||
"time_between_purchase 78355\n",
|
||||
"nb_tickets_internet 0\n",
|
||||
"name_event_types 78355\n",
|
||||
"avg_amount 78355\n",
|
||||
"birthdate 149382\n",
|
||||
"street_id 7\n",
|
||||
"is_partner 7\n",
|
||||
"gender 7\n",
|
||||
"is_email_true 7\n",
|
||||
"opt_in 7\n",
|
||||
"structure_id 136874\n",
|
||||
"profession 150011\n",
|
||||
"language 155191\n",
|
||||
"mcp_contact_id 53526\n",
|
||||
"last_buying_date 78452\n",
|
||||
"max_price 78452\n",
|
||||
"ticket_sum 7\n",
|
||||
"average_price 13127\n",
|
||||
"fidelity 7\n",
|
||||
"average_purchase_delay 78452\n",
|
||||
"average_price_basket 78452\n",
|
||||
"average_ticket_basket 78452\n",
|
||||
"total_price 65332\n",
|
||||
"purchase_count 7\n",
|
||||
"first_buying_date 78452\n",
|
||||
"country 8311\n",
|
||||
"age 149382\n",
|
||||
"tenant_id 7\n",
|
||||
"nb_campaigns 7\n",
|
||||
"nb_campaigns_opened 7\n",
|
||||
"time_to_open 69024\n",
|
||||
"dtype: int64"
|
||||
]
|
||||
},
|
||||
"execution_count": 41,
|
||||
"execution_count": 42,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"df1_customer_product"
|
||||
"df1_customer_product.isna().sum()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 42,
|
||||
"execution_count": 43,
|
||||
"id": "ebf6d843-dcc0-4e83-b063-94806c0bac17",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
|
|
|
|||
|
|
@ -80,3 +80,5 @@ def tickets_kpi_function(tickets_information = None):
|
|||
|
||||
return tickets_kpi
|
||||
|
||||
|
||||
|
||||
File diff suppressed because one or more lines are too long
Loading…
Reference in New Issue
Block a user