Update app

data.py

@@ -8,7 +8,11 @@ from tqdm.auto import tqdm
 import os
 import re
 
-from translate import translate_pa_outcome, translate_pitch_outcome, jp_pitch_to_en_pitch, jp_pitch_to_pitch_code, translate_pitch_outcome, max_pitch_types
+from translate import (
+    translate_pa_outcome, translate_pitch_outcome, 
+    jp_pitch_to_en_pitch, jp_pitch_to_pitch_code,
+    max_pitch_types
+)
 
 # load game data
 # game_df = pd.read_csv('game.csv').drop_duplicates()
@@ -177,15 +181,31 @@ df = (
 # pitch_stats = pd.concat([whiff_rate, csw_rate, velo], axis=1)
 # league_pitch_stats = pd.DataFrame(df.groupby('pitch_name')['release_speed'].apply(lambda x: round(x.mean(), 1)).rename('Velocity'))
 
-pitch_stats= (
-    df
-    .group_by(['name', 'pitch_name'])
-    .agg(
-        ((pl.col('whiff').sum() / pl.col('swing').sum()) * 100).round(1).alias('Whiff%'),
-        ((pl.col('csw').sum() / pl.col('normal_pitch').sum()) * 100).round(1).alias('CSW%'),
-        pl.col('release_speed').mean().round(1).alias('Velocity'),
-        pl.len().alias('Count')
+pitch_stats, rhb_pitch_stats, lhb_pitch_stats = [
+    (
+        _df
+        .group_by(['name', 'pitch_name'])
+        .agg(
+            ((pl.col('whiff').sum() / pl.col('swing').sum()) * 100).round(1).alias('Whiff%'),
+            ((pl.col('csw').sum() / pl.col('normal_pitch').sum()) * 100).round(1).alias('CSW%'),
+            pl.col('release_speed').mean().round(1).alias('Velocity'),
+            pl.len().alias('Count')
+        )
+        .sort(['name', 'Count'], descending=[False, True])
     )
-    .sort(['name', 'Count'], descending=[False, True])
-)
-league_pitch_stats = df.group_by('pitch_name').agg(pl.col('release_speed').mean().round(1).alias('Velocity'))
+    for _df
+    in (
+        df,
+        df.filter(pl.col('stand') == 'R'),
+        df.filter(pl.col('stand') == 'L'),
+    )
+]
+league_pitch_stats, rhb_league_pitch_stats, lhb_league_pitch_stats = [
+    _df.group_by('pitch_name').agg(pl.col('release_speed').mean().round(1).alias('Velocity'))
+    for _df
+    in (
+        df,
+        df.filter(pl.col('stand') == 'R'),
+        df.filter(pl.col('stand') == 'L'),
+    )
+]

demo.py

@@ -46,7 +46,6 @@ with gr.Blocks(css=css) as demo:
       pitch_velo_summary = gr.Plot(label='Velocity Summary')#, elem_classes='pitch-velo-summary')
       pitch_loc_summary = gr.Plot(label='Overall Location')
 
-
   max_pitch_maps = len(jp_pitch_to_en_pitch)
   pitch_maps_per_row = 4
   max_rows = ceil(max_pitch_maps/pitch_maps_per_row)

gradio_function.py

@@ -9,7 +9,11 @@ import polars as pl
 import gradio as gr
 
 from translate import max_pitch_types
-from data import df, pitch_stats, league_pitch_stats
+from data import (
+    df,
+    pitch_stats, rhb_pitch_stats,lhb_pitch_stats,
+    league_pitch_stats, rhb_league_pitch_stats, lhb_league_pitch_stats
+)
 
 # GRADIO FUNCTIONS
 
@@ -261,12 +265,18 @@ def get_data(player, handedness):
   # _df_by_pitch_name = _df.set_index('pitch_name').sort_index()
   _df = df.filter(pl.col('name') == player)
   league_df = df
+  _pitch_stats = pitch_stats
+  _league_pitch_stats = league_pitch_stats
   if handedness == 'Right':
     _df = _df.filter(pl.col('stand') == 'R')
     league_df = league_df.filter(pl.col('stand') == 'R')
+    _pitch_stats = rhb_pitch_stats
+    _league_pitch_stats = rhb_league_pitch_stats
   elif handedness == 'Left':
     _df = _df.filter(pl.col('stand') == 'L')
     league_df = league_df.filter(pl.col('stand') == 'L')
+    _pitch_stats = lhb_pitch_stats
+    _league_pitch_stats = lhb_league_pitch_stats
 
   handedness = gr.update(value=handedness, interactive=True)
 
@@ -296,7 +306,7 @@ def get_data(player, handedness):
         #     'Whiff%': pitch_stats.loc[(player, pitch_name), 'Whiff%'].item(),
         #     'CSW%': pitch_stats.loc[(player, pitch_name), 'CSW%'].item()
         # }]),
-        value=pitch_stats.filter((pl.col('name') == player) & (pl.col('pitch_name') == pitch_name)).select(['Whiff%', 'CSW%']),
+        value=_pitch_stats.filter((pl.col('name') == player) & (pl.col('pitch_name') == pitch_name)).select(['Whiff%', 'CSW%']),
         visible=True
     ))
 
@@ -321,11 +331,11 @@ def get_data(player, handedness):
 
   # velo_stats = pd.concat([pitch_stats.loc[player, 'Velocity'].rename('Avg. Velo'), league_pitch_stats['Velocity'].rename('League Avg. Velo')], join='inner', axis=1).rename_axis(['Pitch']).reset_index()
   velo_stats = (
-      pitch_stats
+      _pitch_stats
       .filter(pl.col('name') == player)
       .select(pl.col('pitch_name').alias('Pitch'), pl.col('Velocity').alias('Avg. Velo'), pl.col('Count'))
       .join(
-          league_pitch_stats.select(pl.col('pitch_name').alias('Pitch'), pl.col('Velocity').alias('League Avg. Velo')),
+          _league_pitch_stats.select(pl.col('pitch_name').alias('Pitch'), pl.col('Velocity').alias('League Avg. Velo')),
           on='Pitch',
           how='inner'
       )