Update app.py

app.py

@@ -23,6 +23,9 @@ import inflect
 from matplotlib.pyplot import text
 import rolling_batter_functions as rbf
 
+px_model = joblib.load('joblib_model/linear_reg_model_x.joblib')
+pz_model = joblib.load('joblib_model/linear_reg_model_z.joblib')
+
 def percentile(n):
     def percentile_(x):
         return np.nanpercentile(x, n)
@@ -154,9 +157,24 @@ codes_in = ['In play, out(s)',
 'Intent Ball',
 'Swinging Pitchout']
 
-exit_velo_df['in_zone'] = exit_velo_df['zone'] < 10
 
 
+# exit_velo_df['in_zone'] = exit_velo_df['zone'] < 10
+
+df.loc[df['sz_top']==0,'sz_top'] = np.nan
+df.loc[df['sz_bot']==0,'sz_bot'] = np.nan
+
+if len(df.loc[(~df['x'].isnull())&(df['px'].isnull()),'px']) > 0:
+    df.loc[(~df['x'].isnull())&(df['px'].isnull()),'px'] = px_model.predict(df.loc[(~df['x'].isnull())&(df['px'].isnull())][['x']])
+    df.loc[(~df['y'].isnull())&(df['pz'].isnull()),'pz'] = px_model.predict(df.loc[(~df['y'].isnull())&(df['pz'].isnull())][['y']]) + 3.2
+
+
+df['in_zone'] =  [x < 10 if type(x) == int else np.nan for x in df['zone']]
+
+df['in_zone_2'] = in_zone_model.predict(df[['x','y','sz_bot','sz_top']].fillna(0).values)
+df['in_zone_3'] = df['in_zone_2'] < 10
+df.loc[df['in_zone'].isna(),'in_zone'] = df.loc[df['in_zone'].isna(),'in_zone_3'].fillna(0)
+
 exit_velo_df = exit_velo_df.drop_duplicates(subset=['play_id'])
 
 exit_velo_df_codes = exit_velo_df[exit_velo_df.play_description.isin(codes_in)].dropna(subset=['in_zone'])