Implement error handling for column dropping in data retrieval for Streamlit app

- Added try-except blocks to handle potential errors when dropping the '_id' column from various data tables.
- Ensured that if an error occurs, the original DataFrame is returned, maintaining data integrity across different tables.

src/streamlit_app.py

@@ -102,31 +102,70 @@ def init_baselines():
         df = pd.DataFrame(cursor)
 
         if table == 'Bullpen_Data':
-            bp_data = df.drop(columns = ['_id'])
+            try:
+                bp_data = df.drop(columns = ['_id'])
+            except:
+                bp_data = df
         elif table == 'Hitter_Agg_Merge':
-            hitter_agg = df.drop(columns = ['_id'])
+            try:
+                hitter_agg = df.drop(columns = ['_id'])
+            except:
+                hitter_agg = df
         elif table == 'Hitter_Long_Merge':
-            hitter_long = df.drop(columns = ['_id'])
+            try:
+                hitter_long = df.drop(columns = ['_id'])
+            except:
+                hitter_long = df
         elif table == 'Hitter_Short_Merge':
-            hitter_short = df.drop(columns = ['_id'])
+            try:
+                hitter_short = df.drop(columns = ['_id'])
+            except:
+                hitter_short = df
         elif table == 'Pitcher_Agg_Merge':
-            pitcher_agg = df.drop(columns = ['_id'])
+            try:
+                pitcher_agg = df.drop(columns = ['_id'])
+            except:
+                pitcher_agg = df
         elif table == 'Pitcher_Long_Merge':
-            pitcher_long = df.drop(columns = ['_id'])
+            try:
+                pitcher_long = df.drop(columns = ['_id'])
+            except:
+                pitcher_long = df
         elif table == 'Pitcher_Short_Merge':
-            pitcher_short = df.drop(columns = ['_id'])
+            try:
+                pitcher_short = df.drop(columns = ['_id'])
+            except:
+                pitcher_short = df
         elif table == 'Slate_Hitters_Merge':
-            slate_hitters = df.drop(columns = ['_id'])
+            try:
+                slate_hitters = df.drop(columns = ['_id'])
+            except:
+                slate_hitters = df
         elif table == 'Slate_Teams_Merge':
-            slate_team = df.drop(columns = ['_id'])
+            try:
+                slate_team = df.drop(columns = ['_id'])
+            except:
+                slate_team = df
         elif table == 'Starting_Pitchers':  
-            starting_pitchers = df.drop(columns = ['_id'])
+            try:
+                starting_pitchers = df.drop(columns = ['_id'])
+            except:
+                starting_pitchers = df
         elif table == 'True_AVG_Split':
-            true_avg_split = df.drop(columns = ['_id'])
+            try:
+                true_avg_split = df.drop(columns = ['_id'])
+            except:
+                true_avg_split = df
         elif table == 'Pitcher_Info':
-            pitcher_info = df.drop(columns = ['_id'])
+            try:
+                pitcher_info = df.drop(columns = ['_id'])
+            except:
+                pitcher_info = df
         elif table == 'Hitter_Info':    
-            hitter_info = df.drop(columns = ['_id'])
+            try:
+                hitter_info = df.drop(columns = ['_id'])
+            except:
+                hitter_info = df
 
     return bp_data, hitter_agg, hitter_long, hitter_short, pitcher_agg, pitcher_long, pitcher_short, slate_hitters, slate_team, starting_pitchers, true_avg_split, pitcher_info, hitter_info