Update player data processing in Streamlit app to include 'exFPTS' in dataframes and adjust column selections for improved accuracy and consistency in lineup generation.

src/streamlit_app.py

@@ -122,7 +122,7 @@ def init_handbuilder_data(site_var):
         cursor = collection.find()
         raw_display = pd.DataFrame(list(cursor))
         raw_display = raw_display.rename(columns={'player_ID': 'player_id'})
-        raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
+        raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
                                    'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX', 'version', 'slate', 'timestamp', 'player_id', 'site']]
         load_display = raw_display[raw_display['Position'] != 'K']
         load_display['Player'] = load_display['Player'].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(load_display['Player'])
@@ -132,7 +132,7 @@ def init_handbuilder_data(site_var):
         cursor = collection.find()
         raw_display = pd.DataFrame(list(cursor))
         raw_display = raw_display.rename(columns={'player_ID': 'player_id'})
-        raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
+        raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
                                    'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX', 'version', 'slate', 'timestamp', 'player_id', 'site']]
         load_display = raw_display[raw_display['Position'] != 'K']
         load_display['Player'] = load_display['Player'].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(load_display['Player'])
@@ -155,7 +155,7 @@ def init_baselines():
 
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display.rename(columns={'player_ID': 'player_id'})
-    raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
+    raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
                                'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX', 'version', 'slate', 'timestamp', 'player_id', 'site']]
     raw_display['Player'] = raw_display['Player'].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(raw_display['Player'])
     load_display = raw_display[raw_display['Position'] != 'K']
@@ -168,7 +168,7 @@ def init_baselines():
 
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display.rename(columns={'player_ID': 'player_id'})
-    raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
+    raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
                                'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX', 'version', 'slate', 'timestamp', 'player_id', 'site']]
     raw_display['Player'] = raw_display['Player'].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(raw_display['Player'])
     load_display = raw_display[raw_display['Position'] != 'K']
@@ -181,7 +181,7 @@ def init_baselines():
 
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display.rename(columns={'player_ID': 'player_id'})
-    raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
+    raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
                                'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX', 'version', 'slate', 'timestamp', 'player_id', 'site']]
     raw_display['Player'] = raw_display['Player'].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(raw_display['Player'])
     # load_display = raw_display[raw_display['Position'] != 'K']
@@ -194,7 +194,7 @@ def init_baselines():
 
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display.rename(columns={'player_ID': 'player_id'})
-    raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
+    raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
                                'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX', 'version', 'slate', 'timestamp', 'player_id', 'site']]
     raw_display['Player'] = raw_display['Player'].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(raw_display['Player'])
     # load_display = raw_display[raw_display['Position'] != 'K']
@@ -206,14 +206,14 @@ def init_baselines():
     cursor = collection.find()
 
     raw_display = pd.DataFrame(list(cursor))
-    raw_display = raw_display[['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Total', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '60+%', '2x%', '3x%', '4x%', 'Own', 'LevX', 'slate', 'version']]
+    raw_display = raw_display[['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Total', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '60+%', '2x%', '3x%', '4x%', 'Own', 'LevX', 'slate']]
     dk_stacks_raw = raw_display.copy()
 
     collection = db["FD_DFS_Stacks"] 
     cursor = collection.find()
 
     raw_display = pd.DataFrame(list(cursor))
-    raw_display = raw_display[['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Total', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '60+%', '2x%', '3x%', '4x%', 'Own', 'LevX', 'slate', 'version']]
+    raw_display = raw_display[['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Total', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '60+%', '2x%', '3x%', '4x%', 'Own', 'LevX', 'slate']]
     fd_stacks_raw = raw_display.copy()
 
     return player_stats, dk_stacks_raw, fd_stacks_raw, dk_roo_raw, fd_roo_raw, dk_sd_roo_raw, fd_sd_roo_raw, dk_id_map, fd_id_map, dk_sd_id_map, fd_sd_id_map
@@ -571,8 +571,8 @@ with app_load_reset_column:
         slate_names_dk, slate_name_lookup_dk = define_dk_showdown_slates()
         slate_names_fd, slate_name_lookup_fd = define_fd_showdown_slates()
         player_stats, dk_stacks_raw, fd_stacks_raw, dk_roo_raw, fd_roo_raw, dk_sd_roo_raw, fd_sd_roo_raw, dk_id_map, fd_id_map, dk_sd_id_map, fd_sd_id_map = init_baselines()
-        dk_lineups = init_DK_lineups('Regular', slate_names_dk[0], 'proj', 50, dk_showdown_db_translation, 25000, [])
-        fd_lineups = init_FD_lineups('Regular', slate_names_fd[0], 'proj', 50, fd_showdown_db_translation, 25000, [])
+        dk_lineups = init_DK_lineups('Regular', 'Main Slate', 'proj', 50, dk_showdown_db_translation, 25000, [])
+        fd_lineups = init_FD_lineups('Regular', 'Main Slate', 'proj', 50, fd_showdown_db_translation, 25000, [])
         for key in st.session_state.keys():
             del st.session_state[key]
 with app_view_site_column:
@@ -1029,12 +1029,10 @@ if selected_tab == 'Stacks ROO':
             split_var1 = st.radio("Would you like to view the whole slate or just specific games?", ('Full Slate Run', 'Specific Games'), key='split_var1_radio')
             if site_var == 'Draftkings':
                 raw_baselines = dk_stacks_raw[dk_stacks_raw['slate'] == str(slate_var1)]
-                raw_baselines = raw_baselines[raw_baselines['version'] == 'overall']
-                raw_baselines = raw_baselines.iloc[:,:-2]
+                raw_baselines = raw_baselines.iloc[:,:-1]
             elif site_var == 'Fanduel':
                 raw_baselines = fd_stacks_raw[fd_stacks_raw['slate'] == str(slate_var1)]
-                raw_baselines = raw_baselines[raw_baselines['version'] == 'overall']
-                raw_baselines = raw_baselines.iloc[:,:-2]
+                raw_baselines = raw_baselines.iloc[:,:-1]
             if split_var1 == 'Specific Games':
                 team_var1 = st.multiselect('Which teams would you like to include in the ROO?', options = raw_baselines['Team'].unique(), key='team_var1_multiselect')
             elif split_var1 == 'Full Slate Run':
@@ -1044,7 +1042,7 @@ if selected_tab == 'Stacks ROO':
     if view_var == 'Simple':
         st.session_state['final_stacks'] = st.session_state['final_stacks'][['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Salary', 'Median', '60+%', '4x%']]
     elif view_var == 'Advanced':
-        st.session_state['final_stacks'] = st.session_state['final_stacks'][['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Total', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish',
+        st.session_state['final_stacks'] = st.session_state['final_stacks'][['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Total', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish',
                                                         'Top_10_finish', '60+%', '2x%', '3x%', '4x%', 'Own', 'LevX']]
     with st.container():
         st.dataframe(st.session_state['final_stacks'].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(player_roo_format, precision=2), height=750, use_container_width = True, key='stacks_dataframe')
@@ -1149,7 +1147,7 @@ if selected_tab == 'Player ROO':
         final_Proj = final_Proj[['Player', 'Position', 'Team', 'Salary', 'Median', 'Top_5_finish', '4x%']]
         st.session_state['disp_proj'] = final_Proj.set_index('Player')
     elif view_var == 'Advanced':
-        final_Proj = final_Proj[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%', 'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX']]
+        final_Proj = final_Proj[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'exFPTS', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%', 'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX']]
         st.session_state['disp_proj'] = final_Proj.set_index('Player')
     with st.container():
         st.dataframe(st.session_state['disp_proj'].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(player_roo_format, precision=2), height=750, use_container_width = True, key='player_dataframe')