generalization #6
							
								
								
									
										68
									
								
								0_3_General_modelization_dataset.py
									
									
									
									
									
										Normal file
									
								
							
							
						
						
									
										68
									
								
								0_3_General_modelization_dataset.py
									
									
									
									
									
										Normal file
									
								
							| 
						 | 
					@ -0,0 +1,68 @@
 | 
				
			||||||
 | 
					# Business Data Challenge - Team 1
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					import pandas as pd
 | 
				
			||||||
 | 
					import numpy as np
 | 
				
			||||||
 | 
					import os
 | 
				
			||||||
 | 
					import s3fs
 | 
				
			||||||
 | 
					import re
 | 
				
			||||||
 | 
					import warnings
 | 
				
			||||||
 | 
					from datetime import date, timedelta, datetime
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					# Create filesystem object
 | 
				
			||||||
 | 
					S3_ENDPOINT_URL = "https://" + os.environ["AWS_S3_ENDPOINT"]
 | 
				
			||||||
 | 
					fs = s3fs.S3FileSystem(client_kwargs={'endpoint_url': S3_ENDPOINT_URL})
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					# Import KPI construction functions
 | 
				
			||||||
 | 
					exec(open('0_KPI_functions.py').read())
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					# Ignore warning
 | 
				
			||||||
 | 
					warnings.filterwarnings('ignore')
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					# functions
 | 
				
			||||||
 | 
					def generate_test_set():
 | 
				
			||||||
 | 
					    file_path_list = fs.ls("projet-bdc2324-team1/Generalization/sport/Test_set")
 | 
				
			||||||
 | 
					    test_set = pd.DataFrame()
 | 
				
			||||||
 | 
					    for file in file_path_list:
 | 
				
			||||||
 | 
					        print(file)
 | 
				
			||||||
 | 
					        with fs.open(file, mode="rb") as file_in:
 | 
				
			||||||
 | 
					            df = pd.read_csv(file_in, sep=",")
 | 
				
			||||||
 | 
					        test_set = pd.concat([test_set, df], ignore_index = True)
 | 
				
			||||||
 | 
					    return test_set
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					def generate_train_set():
 | 
				
			||||||
 | 
					    file_path_list = fs.ls("projet-bdc2324-team1/Generalization/sport/Train_set")
 | 
				
			||||||
 | 
					    train_set = pd.DataFrame()
 | 
				
			||||||
 | 
					    for file in file_path_list:
 | 
				
			||||||
 | 
					        print(file)
 | 
				
			||||||
 | 
					        with fs.open(file, mode="rb") as file_in:
 | 
				
			||||||
 | 
					            df = pd.read_csv(file_in, sep=",")
 | 
				
			||||||
 | 
					        train_set = pd.concat([test_set, df], ignore_index = True)
 | 
				
			||||||
 | 
					    return train_set
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					type_of_comp = input('Choisissez le type de compagnie : sport ? musique ? musee ?')
 | 
				
			||||||
 | 
					BUCKET_OUT = f'projet-bdc2324-team1/Generalization/{type_of_comp}/'
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					# create test and train datasets
 | 
				
			||||||
 | 
					test_set = generate_test_set()
 | 
				
			||||||
 | 
					train_set = generate_train_set()
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					# Exportation test set
 | 
				
			||||||
 | 
					FILE_KEY_OUT_S3 = "Test_set.csv"
 | 
				
			||||||
 | 
					FILE_PATH_OUT_S3 = BUCKET_OUT + FILE_KEY_OUT_S3
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					with fs.open(FILE_PATH_OUT_S3, 'w') as file_out:
 | 
				
			||||||
 | 
					    test_set.to_csv(file_out, index = False)
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					print("Exportation dataset test : SUCCESS")
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					# Exportation train set
 | 
				
			||||||
 | 
					FILE_KEY_OUT_S3 = "Train_set.csv"
 | 
				
			||||||
 | 
					FILE_PATH_OUT_S3 = BUCKET_OUT +  FILE_KEY_OUT_S3
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					with fs.open(FILE_PATH_OUT_S3, 'w') as file_out:
 | 
				
			||||||
 | 
					    train_set.to_csv(file_out, index = False)
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					print("Exportation dataset train : SUCCESS")
 | 
				
			||||||
		Loading…
	
		Reference in New Issue
	
	Block a user