using the portfolio management projections instead of the projections_df

app.py

@@ -1748,7 +1748,7 @@ if selected_tab == 'Data Load':
             st.session_state['origin_portfolio'] = buffer.getvalue()
 
             portfolio_inc_proj = pd.DataFrame()
-            portfolio_inc_proj['player_names'] = get_portfolio_names(st.session_state['portfolio']) + st.session_state['projections_df']['player_names'].tolist()
+            portfolio_inc_proj['player_names'] = set(get_portfolio_names(st.session_state['portfolio']) + st.session_state['projections_df']['player_names'].tolist())
             portfolio_inc_proj['position'] = portfolio_inc_proj['player_names'].map(lambda x: st.session_state['map_dict']['pos_map'].get(x, 'FLEX'))
             portfolio_inc_proj['team'] = portfolio_inc_proj['player_names'].map(lambda x: st.session_state['map_dict']['team_map'].get(x, 'Unknown'))
             portfolio_inc_proj['salary'] = portfolio_inc_proj['player_names'].map(lambda x: st.session_state['map_dict']['salary_map'].get(x, 0))
@@ -1880,16 +1880,16 @@ if selected_tab == 'Projections Management':
                     player_name = row['player_names']
                     
                     # Find and update the original projections_df
-                    orig_idx = st.session_state['projections_df'][st.session_state['projections_df']['player_names'] == player_name].index
+                    orig_idx = st.session_state['portfolio_inc_proj'][st.session_state['portfolio_inc_proj']['player_names'] == player_name].index
                     if len(orig_idx) > 0:
-                        # Player exists in projections_df - update existing row
-                        st.session_state['projections_df'].loc[orig_idx[0], 'player_names'] = row['player_names']
-                        st.session_state['projections_df'].loc[orig_idx[0], 'position'] = row['position']
-                        st.session_state['projections_df'].loc[orig_idx[0], 'team'] = row['team']
-                        st.session_state['projections_df'].loc[orig_idx[0], 'salary'] = row['salary']
-                        st.session_state['projections_df'].loc[orig_idx[0], 'median'] = row['median']
-                        st.session_state['projections_df'].loc[orig_idx[0], 'ownership'] = row['ownership']
-                        st.session_state['projections_df'].loc[orig_idx[0], 'captain ownership'] = row['captain ownership']
+                        # Player exists in portfolio_inc_proj - update existing row
+                        st.session_state['portfolio_inc_proj'].loc[orig_idx[0], 'player_names'] = row['player_names']
+                        st.session_state['portfolio_inc_proj'].loc[orig_idx[0], 'position'] = row['position']
+                        st.session_state['portfolio_inc_proj'].loc[orig_idx[0], 'team'] = row['team']
+                        st.session_state['portfolio_inc_proj'].loc[orig_idx[0], 'salary'] = row['salary']
+                        st.session_state['portfolio_inc_proj'].loc[orig_idx[0], 'median'] = row['median']
+                        st.session_state['portfolio_inc_proj'].loc[orig_idx[0], 'ownership'] = row['ownership']
+                        st.session_state['portfolio_inc_proj'].loc[orig_idx[0], 'captain ownership'] = row['captain ownership']
                     else:
                         # Player is new (from portfolio but not in projections) - add new row
                         new_row = pd.DataFrame([{
@@ -1901,7 +1901,7 @@ if selected_tab == 'Projections Management':
                             'ownership': row['ownership'],
                             'captain ownership': row['captain ownership']
                         }])
-                        st.session_state['projections_df'] = pd.concat([st.session_state['projections_df'], new_row], ignore_index=True)
+                        st.session_state['portfolio_inc_proj'] = pd.concat([st.session_state['portfolio_inc_proj'], new_row], ignore_index=True)
                     
                     # Update map_dict entries
                     if 'map_dict' in st.session_state:
@@ -1945,7 +1945,7 @@ if selected_tab == 'Projections Management':
 if selected_tab == 'Manage Portfolio':
     if 'base_frame_names' not in st.session_state:
             st.session_state['base_frame_names'] = {}
-    if 'origin_portfolio' in st.session_state and 'projections_df' in st.session_state:
+    if 'origin_portfolio' in st.session_state and 'portfolio_inc_proj' in st.session_state:
         with st.container():
             reset_port_col, recalc_stacks_col, recalc_div_col, set_base_col, blank_reset_col, contest_size_col = st.columns([.15, .10, .10, .10, .30, .25])
             with reset_port_col:
@@ -2009,7 +2009,7 @@ if selected_tab == 'Manage Portfolio':
                 st.session_state['map_dict'], 
                 type_var, 
                 sport_var, 
-                st.session_state['projections_df'] if 'stack_dict' in st.session_state else None
+                st.session_state['portfolio_inc_proj'] if 'stack_dict' in st.session_state else None
             )
             processed_frame = processed_frame[processed_frame['salary'] <= salary_max]
             
@@ -2151,8 +2151,8 @@ if selected_tab == 'Manage Portfolio':
                         cpt_flex_focus = st.selectbox("Focus on Overall, CPT, or FLEX?", options=['Overall', 'CPT', 'FLEX'], index=0)
                     player_lock = st.multiselect("Lock players?", options=sorted(list(player_names)), default=[])
                     player_remove = st.multiselect("Remove players?", options=sorted(list(player_names)), default=[])
-                    team_include = st.multiselect("Include teams?", options=sorted(list(set(st.session_state['projections_df']['team'].unique()))), default=[])
-                    team_remove = st.multiselect("Remove teams?", options=sorted(list(set(st.session_state['projections_df']['team'].unique()))), default=[])
+                    team_include = st.multiselect("Include teams?", options=sorted(list(set(st.session_state['portfolio_inc_proj']['team'].unique()))), default=[])
+                    team_remove = st.multiselect("Remove teams?", options=sorted(list(set(st.session_state['portfolio_inc_proj']['team'].unique()))), default=[])
                     if sport_var in stacking_sports:
                         size_include = st.multiselect("Include sizes?", options=sorted(list(set(st.session_state['working_frame']['Size'].unique()))), default=[])
                     else:
@@ -2918,17 +2918,17 @@ if selected_tab == 'Manage Portfolio':
 
             with st.expander('Exposure Management'):
                 with st.form(key='Exposures'):
-                    exposure_player = st.selectbox("Player", options=sorted(list(set(get_portfolio_names(st.session_state['working_frame']) + st.session_state['projections_df']['player_names'].tolist()))), key='exposure_player')
+                    exposure_player = st.selectbox("Player", options=sorted(list(set(get_portfolio_names(st.session_state['working_frame']) + st.session_state['portfolio_inc_proj']['player_names'].tolist()))), key='exposure_player')
                     exposure_target = st.number_input("Target Exposure", value=.50, min_value=0.0, max_value=1.0, step=0.01)
                     comp_salary_below = st.number_input("Comp Salary Below", value=-5000, min_value=-5000, max_value=0, step=100)
                     comp_salary_above = st.number_input("Comp Salary Above", value=5000, min_value=0, max_value=5000, step=100)
                     if 'Stack' in st.session_state['working_frame'].columns:
-                        ignore_stacks = st.multiselect("Ignore Specific Stacks?", options=sorted(list(set(st.session_state['projections_df']['team'].unique()))), default=[])
+                        ignore_stacks = st.multiselect("Ignore Specific Stacks?", options=sorted(list(set(st.session_state['portfolio_inc_proj']['team'].unique()))), default=[])
                     else:
                         ignore_stacks = []
-                    remove_teams_exposure = st.multiselect("Removed/Locked teams?", options=sorted(list(set(st.session_state['projections_df']['team'].unique()))), default=[])
-                    specific_replacements = st.multiselect("Specific Replacements?", options=sorted(list(set(get_portfolio_names(st.session_state['working_frame']) + st.session_state['projections_df']['player_names'].tolist()))), default=[])
-                    specific_exclusions = st.multiselect("Specific exclusions?", options=sorted(list(set(get_portfolio_names(st.session_state['working_frame']) + st.session_state['projections_df']['player_names'].tolist()))), default=[])
+                    remove_teams_exposure = st.multiselect("Removed/Locked teams?", options=sorted(list(set(st.session_state['portfolio_inc_proj']['team'].unique()))), default=[])
+                    specific_replacements = st.multiselect("Specific Replacements?", options=sorted(list(set(get_portfolio_names(st.session_state['working_frame']) + st.session_state['portfolio_inc_proj']['player_names'].tolist()))), default=[])
+                    specific_exclusions = st.multiselect("Specific exclusions?", options=sorted(list(set(get_portfolio_names(st.session_state['working_frame']) + st.session_state['portfolio_inc_proj']['player_names'].tolist()))), default=[])
                     specific_columns = st.multiselect("Specific Positions?", options=sorted(list(st.session_state['player_columns'])), default=[])
                     submitted_col, export_col = st.columns(2)
                     st.info("Portfolio Button applies to your overall Portfolio, Export button applies to your Custom Export")