Update app.py

app.py

@@ -766,12 +766,13 @@ def server(input, output, session):
 
 
     
-        brushed_df_final = (((brushed_df.group_by(['pitcher_id', 'pitch_description']).agg([
+        brushed_df_final = (((brushed_df.group_by(['pitcher_id', 'pitch_type']).agg([
                         pl.col('is_pitch').drop_nans().count().alias('pitches'),
                         pl.col('start_speed').drop_nans().mean().round(1).alias('start_speed'),
                         pl.col('vb').drop_nans().mean().round(1).alias('vb'),
                         pl.col('ivb').drop_nans().mean().round(1).alias('ivb'),
                         pl.col('hb').drop_nans().mean().round(1).alias('hb'),
+                        pl.col('vaa').drop_nans().mean().round(1).alias('vaa'),
                         pl.col('spin_rate').drop_nans().mean().alias('spin_rate'),
                         pl.col('release_pos_x').drop_nans().mean().round(1).alias('x0'),
                         pl.col('release_pos_z').drop_nans().mean().round(1).alias('z0'),
@@ -785,21 +786,22 @@ def server(input, output, session):
                     .alias('proportion')
                 )
                 )).sort('proportion', descending=True).
-                select(["pitch_description", "pitches", "proportion", "start_speed", "ivb", "hb",
+                select(["pitch_type", "pitches", "proportion", "start_speed", "ivb", "hb",
                                                                 "spin_rate", "x0", "z0",'tj_stuff_plus','pitch_grade'])
                 .with_columns(
-            pl.when(pl.col("pitch_description") == "Four-Seam Fastball")
+            pl.when(pl.col("pitch_type") == "Four-Seam Fastball")
             .then(pl.lit("4-Seam"))
-            .otherwise(pl.col("pitch_description"))
-            .alias("pitch_description")
+            .otherwise(pl.col("pitch_type"))
+            .alias("pitch_type")
         )
                 .rename({
-                    'pitch_description': 'Pitch Type',
+                    'pitch_type': 'Pitch Type',
                     'pitches': 'Pitches',
                     'proportion': 'Prop',
                     'start_speed': 'Velo',
                     'ivb': 'iVB',
                     'hb': 'HB',
+                    'vaa': 'VAA',
                     'spin_rate': 'Spin',
                     'x0': 'hRel',
                     'z0': 'vRel',
@@ -849,7 +851,7 @@ def server(input, output, session):
                 .set_properties(subset=brushed_df_final.columns, **{'height': '30px'})
                 .set_table_styles([{'selector': 'thead th', 'props': [('height', '30px')]}], overwrite=False)
                 # .set_table_styles([{'selector': 'table', 'props': [('width', '100px')]}], overwrite=False)
-                .set_table_styles([{'selector': 'thead th:nth-child(1)', 'props': [('min-width', '155px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(1)', 'props': [('min-width', '115px')]}], overwrite=False)
                 .set_table_styles([{'selector': 'thead th:nth-child(2)', 'props': [('min-width', '40px')]}], overwrite=False)
                 .set_table_styles([{'selector': 'thead th:nth-child(3)', 'props': [('min-width', '40px')]}], overwrite=False)
                 .set_table_styles([{'selector': 'thead th:nth-child(4)', 'props': [('min-width', '40px')]}], overwrite=False)
@@ -858,6 +860,7 @@ def server(input, output, session):
                 .set_table_styles([{'selector': 'thead th:nth-child(7)', 'props': [('min-width', '40px')]}], overwrite=False)
                 .set_table_styles([{'selector': 'thead th:nth-child(8)', 'props': [('min-width', '40px')]}], overwrite=False)
                 .set_table_styles([{'selector': 'thead th:nth-child(9)', 'props': [('min-width', '40px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(10)', 'props': [('min-width', '40px')]}], overwrite=False)
                 .background_gradient(cmap=cmap_sum,subset = (brushed_df_final.columns[-2]),vmin=80,vmax=120)
                 .background_gradient(cmap=cmap_sum,subset = (brushed_df_final.columns[-1]),vmin=20,vmax=80)
                 .applymap(lambda x: f'background-color: {dict_pitch_name.get(x, "")}80', subset=['Pitch Type'])