Update app.py

app.py

@@ -725,6 +725,21 @@ def server(input, output, session):
             pl.col("start_speed").count().alias("pitcher_total")
         )
 
+        df_pitcher_totals_hands = (
+            df_spring_stuff
+            .group_by(["pitcher_id", "batter_hand"])
+            .agg(pl.col("start_speed").count().alias("pitcher_total"))
+            .pivot(
+                values="pitcher_total",
+                index="pitcher_id",
+                columns="batter_hand",
+                aggregate_function="first"
+            )
+            .rename({"L": "pitcher_total_left", "R": "pitcher_total_right"})
+            .fill_null(0)  # Fill missing values with 0 if some pitchers don't face both hands
+        )
+                
+        
         df_spring_group = df_spring_stuff.group_by(['pitcher_id', 'pitcher_name', 'pitch_type']).agg([
             pl.col('start_speed').count().alias('count'),
             pl.col('start_speed').mean().alias('start_speed'),
@@ -741,6 +756,7 @@ def server(input, output, session):
 
         # Join total pitches per pitcher to the grouped DataFrame on pitcher_id
         df_spring_group = df_spring_group.join(df_pitcher_totals, on=["pitcher_id"], how="left")
+        df_spring_group = df_spring_group.join(df_pitcher_totals_hands, on=["pitcher_id"], how="left")
 
         # Now calculate the pitch percent for each pitcher/pitch_type combination
         df_spring_group = df_spring_group.with_columns(
@@ -749,8 +765,8 @@ def server(input, output, session):
 
         # Optionally, if you want the percentage of left/right-handed batters within the group:
         df_spring_group = df_spring_group.with_columns([
-            (pl.col("rhh_count") / pl.col("pitcher_total")).alias("rhh_percent"),
-            (pl.col("lhh_count") / pl.col("pitcher_total")).alias("lhh_percent")
+            (pl.col("rhh_count") / pl.col("pitcher_total_right")).alias("rhh_percent"),
+            (pl.col("lhh_count") / pl.col("pitcher_total_left")).alias("lhh_percent")
         ])
 
         df_merge = df_spring_group.join(df_year_old_group,on=['pitcher_id','pitch_type'],how='left',suffix='_old')