Update clients.py

clients.py

@@ -143,12 +143,12 @@ def UserSpecificClient(email_receiver):
                     df.rename(columns={selected_column: col}, inplace=True)
                     
                 if opt_out_scraping:
-                    if 'User description' not in df.columns:
+                    if 'User Description' not in df.columns:
                         all_columns = df.columns.tolist()
                         description_column = st.selectbox("Select the column for Description:", all_columns,key="userdescription")
                         df.rename(columns={description_column: 'Scrapped Profile'}, inplace=True)
                     else:
-                        df.rename(columns={'User description': 'Scrapped Profile'}, inplace=True)                    
+                        df.rename(columns={'User Description': 'Scrapped Profile'}, inplace=True)                    
                     # Check if "Person Linkedin Url" is in the DataFrame
                     if 'Person Linkedin Url' not in df.columns:
                         # Use the DataFrame index to generate a unique value for each row
@@ -234,12 +234,12 @@ def bothFeaturesFunction(email_receiver):
                         df.rename(columns={description_column: 'scraped_content'}, inplace=True)
                     else:
                         df.rename(columns={'Company Description': 'scraped_content'}, inplace=True)    
-                    if 'User description' not in df.columns:
+                    if 'User Description' not in df.columns:
                         all_columns = df.columns.tolist()
                         description_column = st.selectbox("Select the column for User Description:", all_columns,key="bothuserdescription")
                         df.rename(columns={description_column: 'Scrapped Profile'}, inplace=True)
                     else:
-                        df.rename(columns={'User description': 'Scrapped Profile'}, inplace=True)                    
+                        df.rename(columns={'User Description': 'Scrapped Profile'}, inplace=True)                    
                     # Check if "Person Linkedin Url" is in the DataFrame
                     if 'Person Linkedin Url' not in df.columns:
                         # Use the DataFrame index to generate a unique value for each row
@@ -319,12 +319,12 @@ def BH_Ngo(email_receiver,calendly_link,sender_name):
                     df.rename(columns={selected_column: col}, inplace=True)
                     
                 if opt_out_scraping: 
-                    if 'User description' not in df.columns:
+                    if 'User Description' not in df.columns:
                         all_columns = df.columns.tolist()
                         User_description_column = st.selectbox("Select the column for User Description:", all_columns,key="bothuserdescription")
                         df.rename(columns={User_description_column: 'Scrapped Profile'}, inplace=True)
                     else:
-                        df.rename(columns={'User description': 'Scrapped Profile'}, inplace=True)                    
+                        df.rename(columns={'User Description': 'Scrapped Profile'}, inplace=True)                    
                     # Check if "Person Linkedin Url" is in the DataFrame
                     if 'Person Linkedin Url' not in df.columns:
                         # Use the DataFrame index to generate a unique value for each row