diff --git a/0_6_segmentation_V2TP.py b/0_6_segmentation_V2TP.py
index 38d3dc6..77eed3d 100644
--- a/0_6_segmentation_V2TP.py
+++ b/0_6_segmentation_V2TP.py
@@ -21,7 +21,7 @@ import matplotlib.pyplot as plt
 ###################################
 
 # choose the type of companies for which you want to run the pipeline
-activity = "sport"
+type_of_activity = "sport"
 
 # choose the model we use for the segmentation
 model_name = "LogisticRegression_Benchmark"
@@ -76,7 +76,7 @@ X_test_business_fig = df_business_fig(X_test_segment, "segment", business_var)
 # save histogram to Minio
 hist_segment_business_KPIs(X_test_business_fig, "segment", "size", "nb_tickets", 
                            "nb_purchases", "total_amount", "nb_campaigns")
-save_file_s3_mp(File_name = "segments_business_KPIs_", type_of_activity = activity)
+save_file_s3_mp(File_name = "segments_business_KPIs_", type_of_activity)
 
 
 ### 2. description of marketing personae (spider chart)
@@ -95,5 +95,5 @@ X_test_segment_caract = pd.concat([X_test_segment_pb, X_test_segment_mp[['share_
 # visualization and save the graphic to the MinIo
 categories = list(X_test_segment_caract.drop("segment", axis=1).columns)
 radar_mp_plot_all(df=X_test_segment_caract, categories=categories)
-save_file_s3_mp(File_name = "spider_chart_all_", type_of_activity = activity)
+save_file_s3_mp(File_name = "spider_chart_all_", type_of_activity)