Refactor salary processing in app.py: streamline salary conversion by removing unwanted characters before converting to integers, enhancing clarity and ensuring consistent data handling during projections file loading.

app.py

@@ -141,10 +141,11 @@ with tab1:
             if projections is not None:
                 st.success('Projections file loaded successfully!')
                 try:
-                    projections['salary'] = projections['salary'].str.replace(',', '').str.replace('$', '').str.replace(' ', '').astype(int)
+                    projections['salary'] = projections['salary'].str.replace(',', '').str.replace('$', '').str.replace(' ', '')
                     st.write('replaced salary symbols')
                 except:
                     pass
+                projections['salary'] = projections['salary'].astype(int)
                 projections = projections.apply(lambda x: x.replace(player_wrong_names_mlb, player_right_names_mlb))
                 st.dataframe(projections.head(10))
 
@@ -199,11 +200,6 @@ with tab1:
             except:
                 pass
             
-            try:
-                st.session_state['projections_df']['salary'] = (st.session_state['projections_df']['salary'].astype(str).str.replace([',', '$', ' '], '', regex=True).astype(int))
-            except:
-                pass
-            
             try:
                 name_id_map = dict(zip(
                     st.session_state['csv_file']['Name'],