Remove filtering of 'K' position players in data loading for DraftKings and FanDuel, ensuring all players are included in the analysis.

src/streamlit_app.py

@@ -123,8 +123,8 @@ def init_baselines():
     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%',
                                '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']
-    dk_sd_roo_raw = load_display.dropna(subset=['Median'])
+    # load_display = raw_display[raw_display['Position'] != 'K']
+    dk_sd_roo_raw = raw_display.dropna(subset=['Median'])
 
     dk_sd_id_map = dict(zip(dk_sd_roo_raw['Player'], dk_sd_roo_raw['player_id']))
 
@@ -135,8 +135,8 @@ def init_baselines():
     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%',
                                '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']
-    fd_sd_roo_raw = load_display.dropna(subset=['Median'])
+    # load_display = raw_display[raw_display['Position'] != 'K']
+    fd_sd_roo_raw = raw_display.dropna(subset=['Median'])
 
     fd_sd_id_map = dict(zip(fd_sd_roo_raw['Player'], fd_sd_roo_raw['player_id']))