added exFPTS as variable

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', 'version']]
     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', 'version']]
     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
@@ -1149,7 +1149,7 @@ 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')