Refactor projections file handling in app.py for improved clarity and functionality

- Removed the projections file upload section and associated logic to streamline the user interface.
- Updated the handling of ownership and actual data dictionaries to directly utilize session state variables, enhancing data accessibility.
- These changes contribute to ongoing efforts to simplify the application and improve user experience.

app.py

@@ -92,46 +92,12 @@ with tab1:
             if st.session_state['Contest'] is not None:
                 st.success('Contest file loaded successfully!')
                 st.dataframe(st.session_state['Contest'].head(10))
-
-    with col2:
-        st.subheader("Projections File")
-        st.info("upload a projections file that has 'player_names', 'salary', 'median', 'ownership', and 'captain ownership' (Needed for Showdown) columns. Note that the salary for showdown needs to be the FLEX salary, not the captain salary.")
-        
-        # Create two columns for the uploader and template button
-        upload_col, template_col = st.columns([3, 1])
-        
-        with upload_col:
-            projections_file = st.file_uploader("Upload Projections File (CSV or Excel)", type=['csv', 'xlsx', 'xls'])
-            if 'projections_df' in st.session_state:
-                del st.session_state['projections_df']
-        
-        with template_col:
-            # Create empty DataFrame with required columns
-            template_df = pd.DataFrame(columns=['player_names', 'position', 'team', 'salary', 'median', 'ownership', 'captain ownership'])
-            # Add download button for template
-            st.download_button(
-                label="Template",
-                data=template_df.to_csv(index=False),
-                file_name="projections_template.csv",
-                mime="text/csv"
-            )
-            
-        if projections_file and 'Adj_projections_df' not in st.session_state:
-            export_projections, st.session_state['projections_df'] = load_file(projections_file)
-            if st.session_state['projections_df'] is not None:
-                st.success('Projections file loaded successfully!')
-                st.dataframe(st.session_state['projections_df'].head(10))
         
-    if 'Contest_file' in st.session_state and 'projections_df' in st.session_state:
-        st.subheader("Name Matching functions")
-        if 'Adj_Contest' not in st.session_state:
-            try:    
-                st.session_state['Adj_Contest'], st.session_state['Adj_projections_df'], st.session_state['Adj_ownership_df'], st.session_state['Adj_actual_df'] = find_name_mismatches(st.session_state['Contest'], st.session_state['projections_df'], st.session_state['ownership_df'], st.session_state['actual_df'])
-            except:
-                st.warning('Please manage name matching to move forward')
-        st.session_state['Adj_projections_df']['salary'] = (st.session_state['Adj_projections_df']['salary'].astype(str).str.replace(',', '').astype(float).astype(int))
-        st.session_state['ownership_dict'] = dict(zip(st.session_state['Adj_ownership_df']['Player'], st.session_state['Adj_ownership_df']['Own']))
-        st.session_state['actual_dict'] = dict(zip(st.session_state['Adj_actual_df']['Player'], st.session_state['Adj_actual_df']['FPTS']))
+    if 'Contest_file' in st.session_state:
+        st.session_state['ownership_dict'] = dict(zip(st.session_state['ownership_df']['Player'], st.session_state['ownership_df']['Own']))
+        st.session_state['actual_dict'] = dict(zip(st.session_state['actual_df']['Player'], st.session_state['actual_df']['FPTS']))
+        st.write(st.session_state['ownership_dict'])
+        st.write(st.session_state['actual_dict'])
 
 
 with tab2: