Update pages/market_rent_estimation.py

pages/market_rent_estimation.py

@@ -22,12 +22,12 @@ def main():
     max_size = (100 + st.session_state['max_property_size_perc']) / 100 * st.session_state['building_sf']
 
     # # user's filter for lease size is a range in percentage around picked lease 
-    # lease_min_size = (100 + st.session_state['min_property_lease_size_perc']) / 100 * st.session_state['rented_sf']
-    # lease_max_size = (100 + st.session_state['max_property_lease_size_perc']) / 100 * st.session_state['rented_sf']
+    lease_min_size = (100 + st.session_state['min_property_lease_size_perc']) / 100 * st.session_state['rented_sf']
+    lease_max_size = (100 + st.session_state['max_property_lease_size_perc']) / 100 * st.session_state['rented_sf']
 
     #apply all filters 
-    # (df_properties['rented_sf'] >= lease_min_size) & (df_properties['rented_sf'] <= lease_max_size) &
-    mask =  (df_properties['building_sf'] >= min_size) & (df_properties['building_sf'] <= max_size) & (df_properties['months_since'] <= st.session_state['months_back'])
+    # 
+    mask = (df_properties['rented_sf'] >= lease_min_size) & (df_properties['rented_sf'] <= lease_max_size) & (df_properties['building_sf'] >= min_size) & (df_properties['building_sf'] <= max_size) & (df_properties['months_since'] <= st.session_state['months_back'])
     df_properties_filtered = df_properties[mask]
     
     # create distances matrix for remaining rows