Merge branch 'main' of https://huggingface.co/spaces/Multichem-PD/DFS_Portfolio_Manager

app.py

@@ -162,7 +162,20 @@ with tab1:
                     st.write('replaced salary symbols')
                 except:
                     pass
+                try:
+                    projections['ownership'] = projections['ownership'].str.replace('%', '').str.replace(' ', '')
+                    st.write('replaced ownership symbols')
+                except:
+                    pass
                 projections['salary'] = projections['salary'].dropna().astype(int)
+                projections['ownership'] = projections['ownership'].astype(float)
+                if type_var == 'Showdown':
+                    if projections['captain ownership'].isna().all():
+                        projections['CPT_Own_raw'] = (projections['ownership'] / 2) * ((100 - (100-projections['ownership']))/100)
+                        cpt_own_var = 100 / projections['CPT_Own_raw'].sum()
+                        projections['captain ownership'] = projections['CPT_Own_raw'] * cpt_own_var
+                        projections = projections.drop(columns='CPT_Own_raw', axis=1)
+                            
                 projections = projections.apply(lambda x: x.replace(player_wrong_names_mlb, player_right_names_mlb))
                 st.dataframe(projections.head(10))
 
@@ -250,7 +263,7 @@ with tab1:
             projections['player_names'] = projections['player_names'].map(lambda x: projections_match_dict.get(x, x))
             st.session_state['projections_df'] = projections
 
-            if 'Stack' not in st.session_state['portfolio'].columns and sport_var in stacking_sports:
+            if sport_var in stacking_sports:
                 team_dict = dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['team']))
                 st.session_state['portfolio']['Stack'] = st.session_state['portfolio'].apply(
                     lambda row: Counter(
@@ -825,17 +838,30 @@ with tab2:
                             'cpt_own_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['captain ownership']))
                         }
                 elif type_var == 'Showdown':
-                    st.session_state['map_dict'] = {
-                        'pos_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['position'])),
-                        'team_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['team'])),
-                        'salary_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['salary'])),
-                        'proj_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['median'])),
-                        'own_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['ownership'])),
-                        'own_percent_rank':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['ownership'].rank(pct=True))),
-                        'cpt_salary_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['salary'] * 1.5)),
-                        'cpt_proj_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['median'] * 1.5)),
-                        'cpt_own_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['captain ownership']))
-                    }
+                    if sport_var == 'GOLF':
+                        st.session_state['map_dict'] = {
+                            'pos_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['position'])),
+                            'team_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['team'])),
+                            'salary_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['salary'])),
+                            'proj_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['median'])),
+                            'own_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['ownership'])),
+                            'own_percent_rank':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['ownership'].rank(pct=True))),
+                            'cpt_salary_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['salary'])),
+                            'cpt_proj_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['median'])),
+                            'cpt_own_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['ownership']))
+                        }
+                    if sport_var != 'GOLF':
+                        st.session_state['map_dict'] = {
+                            'pos_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['position'])),
+                            'team_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['team'])),
+                            'salary_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['salary'])),
+                            'proj_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['median'])),
+                            'own_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['ownership'])),
+                            'own_percent_rank':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['ownership'].rank(pct=True))),
+                            'cpt_salary_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['salary'] * 1.5)),
+                            'cpt_proj_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['median'] * 1.5)),
+                            'cpt_own_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['captain ownership']))
+                        }
             elif site_var == 'Fanduel':
                 st.session_state['map_dict'] = {
                     'pos_map':dict(zip(st.session_state['projections_df']['player_names'], st.session_state['projections_df']['position'])),