Update app.py

app.py

@@ -67,10 +67,18 @@ def player_stat_table():
 def load_dk_player_projections():
     sh = gc.open_by_url('https://docs.google.com/spreadsheets/d/1I_1Ve3F4tftgfLQQoRKOJ351XfEG48s36OxXUKxmgS8/edit#gid=1391856348')
     worksheet = sh.worksheet('DK_ROO')
-    load_display = pd.DataFrame(worksheet.get_all_records())
-    load_display.replace('', np.nan, inplace=True)
-    raw_display = load_display.dropna(subset=['Median'])
-    del load_display
+    
+    # Get all records from the Google Sheet
+    records = worksheet.get_all_records()
+    
+    # Convert to Polars DataFrame
+    load_display = pl.DataFrame(records)
+    
+    # Replace empty strings with np.nan
+    load_display = load_display.apply(lambda df: df.replace("", np.nan))
+    
+    # Drop rows where 'Median' is NaN
+    raw_display = load_display.filter(pl.col("Median").is_not_null())
 
     return raw_display
 
@@ -78,30 +86,39 @@ def load_dk_player_projections():
 def load_fd_player_projections():
     sh = gc.open_by_url('https://docs.google.com/spreadsheets/d/1I_1Ve3F4tftgfLQQoRKOJ351XfEG48s36OxXUKxmgS8/edit#gid=1391856348')
     worksheet = sh.worksheet('FD_ROO')
-    load_display = pd.DataFrame(worksheet.get_all_records())
-    load_display.replace('', np.nan, inplace=True)
-    raw_display = load_display.dropna(subset=['Median'])
-    del load_display
+    
+    # Get all records from the Google Sheet
+    records = worksheet.get_all_records()
+    
+    # Convert to Polars DataFrame
+    load_display = pl.DataFrame(records)
+    
+    # Replace empty strings with np.nan
+    load_display = load_display.apply(lambda df: df.replace("", np.nan))
+    
+    # Drop rows where 'Median' is NaN
+    raw_display = load_display.filter(pl.col("Median").is_not_null())
 
     return raw_display
 
 @st.cache_resource(ttl = 60)
 def set_export_ids():
     sh = gc.open_by_url('https://docs.google.com/spreadsheets/d/1I_1Ve3F4tftgfLQQoRKOJ351XfEG48s36OxXUKxmgS8/edit#gid=1391856348')
-    worksheet = sh.worksheet('DK_ROO')
-    load_display = pd.DataFrame(worksheet.get_all_records())
-    load_display.replace('', np.nan, inplace=True)
-    raw_display = load_display.dropna(subset=['Median'])
-    dk_ids = dict(zip(raw_display['Player'], raw_display['player_id']))
-    
-    worksheet = sh.worksheet('FD_ROO')
-    load_display = pd.DataFrame(worksheet.get_all_records())
-    load_display.replace('', np.nan, inplace=True)
-    raw_display = load_display.dropna(subset=['Median'])
-    fd_ids = dict(zip(raw_display['Player'], raw_display['player_id']))
+    # Fetch DK_ROO worksheet and prepare Polars DataFrame
+    worksheet_dk = sh.worksheet('DK_ROO')
+    records_dk = worksheet_dk.get_all_records()
+    load_display_dk = pl.DataFrame(records_dk)
+    load_display_dk = load_display_dk.apply(lambda df: df.replace("", np.nan))
+    raw_display_dk = load_display_dk.filter(pl.col("Median").is_not_null())
+    dk_ids = dict(zip(raw_display_dk["Player"].to_list(), raw_display_dk["player_id"].to_list()))
     
-    del load_display
-    del raw_display
+    # Fetch FD_ROO worksheet and prepare Polars DataFrame
+    worksheet_fd = sh.worksheet('FD_ROO')
+    records_fd = worksheet_fd.get_all_records()
+    load_display_fd = pl.DataFrame(records_fd)
+    load_display_fd = load_display_fd.apply(lambda df: df.replace("", np.nan))
+    raw_display_fd = load_display_fd.filter(pl.col("Median").is_not_null())
+    fd_ids = dict(zip(raw_display_fd["Player"].to_list(), raw_display_fd["player_id"].to_list()))
 
     return dk_ids, fd_ids