Update functions to support NBA data by replacing NFL references with NBA equivalents in regular and showdown functions.

src/sim_func_hold/regular_functions.py

@@ -9,23 +9,23 @@ def init_DK_seed_frames(slate_var, sharp_split):
 
     
     if slate_var == 'Main Slate':
-        collection = db['DK_NFL_name_map']
+        collection = db['DK_NBA_name_map']
         cursor = collection.find()
         raw_data = pd.DataFrame(list(cursor))
         names_dict = dict(zip(raw_data['key'], raw_data['value']))
-        collection = db[f"DK_NFL_seed_frame_Main Slate"] 
+        collection = db[f"DK_NBA_seed_frame_Main Slate"] 
     elif slate_var == 'Secondary Slate':
-        collection = db['DK_NFL_Secondary_name_map']
+        collection = db['DK_NBA_Secondary_name_map']
         cursor = collection.find()
         raw_data = pd.DataFrame(list(cursor))
         names_dict = dict(zip(raw_data['key'], raw_data['value']))
-        collection = db[f"DK_NFL_seed_frame_Secondary Slate"] 
+        collection = db[f"DK_NBA_seed_frame_Secondary Slate"] 
     elif slate_var == 'Late Slate':
-        collection = db['DK_NFL_Late_name_map']
+        collection = db['DK_NBA_Late_name_map']
         cursor = collection.find()
         raw_data = pd.DataFrame(list(cursor))
         names_dict = dict(zip(raw_data['key'], raw_data['value']))
-        collection = db[f"DK_NFL_seed_frame_Late Slate"] 
+        collection = db[f"DK_NBA_seed_frame_Late Slate"] 
 
     cursor = collection.find().limit(sharp_split)
 

src/sim_func_hold/showdown_functions.py

@@ -35,7 +35,7 @@ def init_SD_baselines(slate_var):
 
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display[raw_display['version'] == 'overall']
-    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', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
                                 'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX', 'version', 'slate', 'timestamp', 'player_id', 'site']]
     raw_display = raw_display.rename(columns={'player_id': 'player_ID'})                            
     raw_display['Small_Field_Own'] = raw_display['Large_Field_Own']