Update appStore/target.py

appStore/target.py

@@ -8,6 +8,7 @@ import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 import streamlit as st
+from st_aggrid import AgGrid
 from utils.target_classifier import load_targetClassifier, target_classification 
 import logging
 logger = logging.getLogger(__name__)
@@ -27,7 +28,7 @@ _lab_dict = {
             }
 
 @st.cache_data
-def to_excel(df):
+def to_excel(df,hits):
     # df['Target Validation'] = 'No'
     # df['Netzero Validation'] = 'No'
     # df['GHG Validation'] = 'No'
@@ -37,9 +38,6 @@ def to_excel(df):
     output = BytesIO()
     writer = pd.ExcelWriter(output, engine='xlsxwriter')
     df.to_excel(writer, index=False, sheet_name='rawdata')
-    hits  = df[df['Target Label'] == 'TARGET']
-    hits = hits.reset_index(drop=True)
-    hits = hits.sort_values(by=['Target Score'], ascending=False)
     hits = hits.drop(columns = ['Target Score','Netzero Score','GHG Score'])
     hits.to_excel(writer,index=False,sheet_name = 'Target')
     workbook = writer.book
@@ -106,6 +104,8 @@ def target_display():
                 st.write('**Economy-wide Related Paragraphs**: `{}`'.format(count_economy))
             # st.write('-------------------')    
             hits = hits.sort_values(by=['Target Score'], ascending=False)
+            hits = hits.reset_index(drop=True)
+
             # netzerohit = hits[hits['Netzero Label'] == 'NETZERO']
             # if not netzerohit.empty:
             #     netzerohit = netzerohit.sort_values(by = ['Netzero Score'], ascending = False)
@@ -133,8 +133,8 @@ def target_display():
         #     hits = hits.reset_index(drop =True)
             st.write('----------------')
             st.write('Explore the data')
-            st.write(hits)
-            df_xlsx = to_excel(df)
+            AgGrid(hits)
+            df_xlsx = to_excel(df,hits)
             
             with st.sidebar:
                 st.write('-------------')