update

app.py

@@ -83,7 +83,6 @@ model_dir = model.download()
 model = joblib.load(model_dir + "/incident_model.pkl")
 
 batch_data = results_df_preprocessed.copy()
-batch_data = batch_data[:100]
 batch_data.drop(columns=['incident_datetime','incident_category'], inplace=True)
 y_pred = model.predict(batch_data)
 
@@ -93,11 +92,12 @@ results_df_preprocessed["report_type_code"]=results_df_preprocessed.apply(lambda
 results_df_preprocessed.drop(columns=["report_type_code_II","report_type_code_IS","report_type_code_VI","report_type_code_VS"],inplace=True)
 results_df_preprocessed["police_district"]=results_df_preprocessed.apply(lambda x:unencode_police_district(x.police_district_Bayview,x.police_district_Central,x.police_district_Ingleside,x.police_district_Mission,x.police_district_Northern,x.police_district_OutOfSF,x.police_district_Park,x.police_district_Richmond,x.police_district_Southern,x.police_district_Taraval,x.police_district_Tenderloin),axis=1)
 results_df_preprocessed.drop(columns=["police_district_Bayview","police_district_Central","police_district_Ingleside","police_district_Mission","police_district_Northern","police_district_OutOfSF","police_district_Park","police_district_Richmond","police_district_Southern","police_district_Taraval","police_district_Tenderloin"],inplace=True)
+results_df_preprocessed.reset_index(inplace=True)
 results_df_preprocessed["idx_temp"]=results_df_preprocessed.index
 results_df_preprocessed["incident_category_pred"]=y_pred[results_df_preprocessed.idx_temp]
 results_df_preprocessed.drop(columns=["idx_temp"],inplace=True)
 
-df = results_df_preprocessed
+df = results_df_preprocessed[['incident_datetime', 'latitude', 'longitude', 'incident_day_of_week', 'report_type_code', 'police_district', 'incident_category', 'incident_category_pred']]
 
 st.write(df)
 st.button("Re-run")