66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
import pandas as pd
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import numpy as np
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import os
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import s3fs
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import re
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import warnings
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# Ignore warning
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warnings.filterwarnings('ignore')
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exec(open('../0_KPI_functions.py').read())
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exec(open('plot.py').read())
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# Create filesystem object
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S3_ENDPOINT_URL = "https://" + os.environ["AWS_S3_ENDPOINT"]
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fs = s3fs.S3FileSystem(client_kwargs={'endpoint_url': S3_ENDPOINT_URL})
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companies = {'musee' : ['1', '2', '3', '4'], # , '101'
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'sport': ['5', '6'],
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'musique' : ['10', '11', '12', '13', '14']}
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type_of_activity = input('Choisissez le type de compagnie : sport ? musique ? musee ?')
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list_of_comp = companies[type_of_activity]
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# Load files
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customer, campaigns_kpi, campaigns_brut, tickets, products = load_files(list_of_comp)
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# Identify anonymous customer for each company and remove them from our datasets
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outlier_list = outlier_detection(tickets, list_of_comp)
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# Identify valid customer (customer who bought tickets after starting date or received mails after starting date)
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customer_valid_list = valid_customer_detection(products, campaigns_brut)
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# Identify customer who bought during the period of y
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consumer_target_period = identify_purchase_during_target_periode(products)
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databases = [customer, campaigns_kpi, campaigns_brut, tickets, products]
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for dataset in databases:
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dataset['customer_id'] = dataset['customer_id'].apply(lambda x: remove_elements(x, outlier_list))# remove outlier
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dataset['customer_id'] = dataset['customer_id'].isin(customer_valid_list) # keep only valid customer
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dataset['has_purchased_target_period'] = np.where(dataset['customer_id'].isin(customer_valid_list), 1, 0)
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#print(f'shape of {dataset} : ', dataset.shape)
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# Generate graph and automatically saved them in the bucket
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compute_nb_clients(customer, type_of_activity)
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maximum_price_paid(customer, type_of_activity)
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mailing_consent(customer, type_of_activity)
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#gender_bar(customer, type_of_activity)
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#country_bar(customer, type_of_activity)
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#lazy_customer_plot(campaigns_kpi, type_of_activity)
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#campaigns_effectiveness(customer, type_of_activity)
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#sale_dynamics(products, campaigns_brut, type_of_activity)
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#tickets_internet(tickets, type_of_activity)
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#box_plot_price_tickets(tickets, type_of_activity)
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