diff --git a/0_1_Input_cleaning.py b/0_1_Input_cleaning.py
index ec7eeeb..a7fc903 100644
--- a/0_1_Input_cleaning.py
+++ b/0_1_Input_cleaning.py
@@ -30,29 +30,29 @@ def export_dataset(df, output_name):
         df.to_csv(file_out, index = False)
 
 ## 1 - Cleaning of the datasets
-for tenant_id in ("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "101"): 
+for tenant_id in ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "101"]:
     
     # Timer
     start = time.time()
     
-    # # Cleaning customerplus
-    # df1_customerplus_clean = preprocessing_customerplus(directory_path = tenant_id)
-    
-    # ## Exportation 
-    # export_dataset(df = df1_customerplus_clean, output_name = "0_Input/Company_"+ tenant_id +"/customerplus_cleaned.csv")
-    
-    # # Cleaning target area
-    # df1_target_information = preprocessing_target_area(directory_path = tenant_id)
-    # ## Exportation 
-    # export_dataset(df = df1_target_information, output_name = "0_Input/Company_"+ tenant_id +"/target_information.csv")
-    
-    # # Cleaning campaign area
-    # df1_campaigns_information = preprocessing_campaigns_area(directory_path = tenant_id)
-    # ## Exportation 
-    # export_dataset(df = df1_campaigns_information, output_name = "0_Input/Company_"+ tenant_id +"/campaigns_information.csv")
+    # Cleaning customerplus
+    df1_customerplus_clean = preprocessing_customerplus(directory_path = tenant_id)
     
     ## Exportation 
-    # export_dataset(df = df1_campaigns_information, output_name = "1_Temp/Company 1 - Campaigns dataset clean.csv")
+    export_dataset(df = df1_customerplus_clean, output_name = "0_Input/Company_"+ tenant_id +"/customerplus_cleaned.csv")
+    
+    # Cleaning target area
+    df1_target_information = preprocessing_target_area(directory_path = tenant_id)
+    ## Exportation 
+    export_dataset(df = df1_target_information, output_name = "0_Input/Company_"+ tenant_id +"/target_information.csv")
+    
+    # Cleaning campaign area
+    df1_campaigns_information = preprocessing_campaigns_area(directory_path = tenant_id)
+    ## Exportation 
+    export_dataset(df = df1_campaigns_information, output_name = "0_Input/Company_"+ tenant_id +"/campaigns_information.csv")
+    
+    # Exportation 
+    export_dataset(df = df1_campaigns_information, output_name = "1_Temp/Company 1 - Campaigns dataset clean.csv")
 
     if tenant_id == "101":
         # Cleaning product area
diff --git a/0_Cleaning_and_merge_functions.py b/0_Cleaning_and_merge_functions.py
index c8144f5..64ec7d4 100644
--- a/0_Cleaning_and_merge_functions.py
+++ b/0_Cleaning_and_merge_functions.py
@@ -145,7 +145,7 @@ def preprocessing_tickets_area(directory_path):
     tickets.rename(columns = {'id' : 'ticket_id'}, inplace = True)
     
     if directory_path == '101':
-        tickets_1 = tickets[['id', 'purchase_id', 'product_id', 'is_from_subscription', 'type_of', 'supplier_id']]
+        tickets_1 = tickets_1[['id', 'purchase_id', 'product_id', 'is_from_subscription', 'type_of', 'supplier_id']]
         tickets_1.rename(columns = {'id' : 'ticket_id'}, inplace = True)
 
     # Base des fournisseurs
@@ -294,6 +294,5 @@ def uniform_product_df(directory_path):
         products_purchased_reduced_1 = products_purchased_1[['ticket_id', 'customer_id', 'purchase_id' ,'event_type_id', 'supplier_name', 'purchase_date',  'amount', 'is_full_price', 'name_event_types', 'name_facilities', 'name_categories', 'name_events', 'name_seasons', 'start_date_time', 'end_date_time', 'open']] # 'type_of_ticket_name', 'children',
         
         return products_purchased_reduced, products_purchased_reduced_1
-        
     else : 
         return products_purchased_reduced
\ No newline at end of file