Update pages/market_rent_estimation.py

pages/market_rent_estimation.py

@@ -41,15 +41,15 @@ def main():
     sorted_distances = distances[sorted_indices]
     sorted_indexes = df_properties_filtered.index[sorted_indices]
     reordered_df_properties_filtered = df_properties_filtered.loc[sorted_indexes]
- 
-       
+
+
     #comps page
     with tab1:
         filtered_data = reordered_df_properties_filtered[["google_ola", "market_costar", "submarket_costar", "execution_date", "rented_sf", "building_sf", "year_built", "office_rate", "min_clear_height", "max_clear_height", "docks", "drive_ins", "rent_combined"]]#pd.concat([filtered_data2])
         comps_scores = sorted_distances
-        
+
         filtered_data.insert(loc=1, column='Similarity score', value=comps_scores)
-        
+
         # Formatting the DataFrame
         filtered_data['Similarity score'] = ((1 - filtered_data['Similarity score']) * 100).apply(lambda x: f"{x:.2f}")
         filtered_data['execution_date'] = pd.to_datetime(filtered_data['execution_date']).dt.strftime('%m-%d-%Y')
@@ -57,17 +57,17 @@ def main():
         filtered_data['RSF (sf)'] = filtered_data['building_sf'].round(0).astype(int)
         filtered_data['Year built'] = filtered_data['year_built'].astype(int)
         filtered_data.loc[filtered_data['office_rate'].notna(), 'office_rate'] = (filtered_data.loc[filtered_data['office_rate'].notna(), 'office_rate'] * 100).apply(lambda x: f"{x:.2f} %")
-        
+
         filtered_data.loc[filtered_data['min_clear_height'].notna(), 'min_clear_height'] = (filtered_data.loc[filtered_data['min_clear_height'].notna(), 'min_clear_height']).apply(lambda x: f"{int(x)}")
         # filtered_data['Clear Height (feet)'] = filtered_data['min_clear_height'].round(0).astype(int)
-        
+
         filtered_data.loc[filtered_data['docks'].notna(), 'docks'] = (filtered_data.loc[filtered_data['docks'].notna(), 'docks']).apply(lambda x: f"{int(x)}")
         filtered_data.loc[filtered_data['drive_ins'].notna(), 'drive_ins'] = (filtered_data.loc[filtered_data['drive_ins'].notna(), 'drive_ins']).apply(lambda x: f"{int(x)}")
-        
+
         # filtered_data['Docks (/10ksf)'] = filtered_data['docks'].astype(int)
         # filtered_data['Doors (/10ksf)'] = filtered_data['drive_ins'].astype(int)
         filtered_data['Rent (NNN)'] = filtered_data['rent_combined'].apply(lambda x: f"${x:.2f}")
-        
+
         # Dropping old columns and renaming headers
         filtered_data = filtered_data.drop(columns=['rented_sf', 'building_sf', 'year_built', 'max_clear_height', 'rent_combined'])
         filtered_data = filtered_data.rename(columns={
@@ -80,8 +80,8 @@ def main():
             'submarket_costar': 'Submarket'
         })
         filtered_data = filtered_data.sort_values(by="Similarity score", ascending=False)
-       
-       
+
+        
         # Display the filtered data
         col_1_1, col_1_2 = st.columns([2, 1])
         with col_1_1:
@@ -95,16 +95,16 @@ def main():
             # if sort_column:
             #     filtered_data_sorted = filtered_data.sort_values(by=sort_column, ascending=False)         
             st.dataframe(filtered_data_sorted)
- 
+
         with col_1_2:
         # Create a map object
             m = folium.Map(width=500, height=440, location=(reordered_df_properties_filtered['lat'].mean(), reordered_df_properties_filtered['long'].mean()), zoom_start=9)
-           
+
             # Add markers to the map
             all_markers = folium.FeatureGroup(name='All Markers')
             active_markers = folium.FeatureGroup(name='Active Markers', show=False)
             inactive_markers = folium.FeatureGroup(name='Inactive Markers', show=False)
-               
+
             for index, row in reordered_df_properties_filtered.iterrows():
                 status_color = 'green' if index==0 else 'red'
                 html_content = f"""
@@ -121,12 +121,12 @@ def main():
                     color: {status_color};
                 ">{index}</div>
                 """
-                   
+
                 # Create a DivIcon with custom HTML content
                 icon = folium.DivIcon(html=html_content)
                 marker = folium.Marker([row['lat'], row['long']], popup=row['google_ola'], icon=icon).add_to(m)
- 
- 
+
+            
             #add poligons on map
             gdf = gpd.read_file('costar_sm_polygons.geojson')
             gdf_Atlanta = gdf[gdf.full_submarket.str.contains("Atlanta")]
@@ -142,20 +142,20 @@ def main():
                                         )
                 # Add a popup with the name
                 popup = folium.Popup(row['full_submarket'], parse_html=True)
-               
+
                 # Add the GeoJson and Popup to the map
                 geojson.add_child(popup).add_to(m)
-                   
+    
             # Add layer control to toggle marker visibility
             folium.LayerControl().add_to(m)
-           
+
             # Render the map
             folium_static(m)
- 
+
         back_to_serach_tab2 = st.button("Search page ")
         if back_to_serach_tab2:
             st.switch_page("app.py")
-           
+
     with tab2:
         st.title('Combined estimation')
         if 'user_select_value' not in st.session_state:
@@ -166,17 +166,17 @@ def main():
             st.session_state['submarket_val'] = ""
         if 'market_val' not in st.session_state:
             st.session_state['market_val'] = ""
- 
+
         box_contents = [
             {"header": "Address", "content": st.session_state['user_select_value']},
             {"header": "LSF", "content": str(st.session_state['rented_sf'])},
             {"header": "Sub-Market", "content": st.session_state['submarket_val']},
             {"header": "Market", "content": st.session_state['market_val']}
         ]
- 
+
         # Divide the layout into four columns
         col1, col2, col3, col4 = st.columns(4)
-       
+
         for i, col in enumerate([col1, col2, col3, col4]):
             col.markdown(f"""
                     <div style="padding: 20px; margin: 10px; text-align: center;">
@@ -184,7 +184,7 @@ def main():
                     <p style="font-size: small;">{box_contents[i]['content']}</p>
                     </div>
             """, unsafe_allow_html=True)
-           
+
         # Add padding between the boxes and the slider
         st.markdown('<style>div[data-testid="stBlock"]{margin-top: 20px;}</style>', unsafe_allow_html=True)
        
@@ -193,25 +193,24 @@ def main():
         #         return ast.literal_eval(val)
         #     except (ValueError, SyntaxError):
         #         return val
-                
+     
         average_rent = reordered_df_properties_filtered['rent_combined'].mean()
-       
+
         x1 ="Comps " + str(average_rent)
         x3="Rent " + str(st.session_state['prediction'])
-       
+
         # x2 = (st.session_state['prediction']+average_rent)/2
-       
+
         pick = st.select_slider(
         "Combined estimation ",
         options=[x1, x3],
         value=x1)
-       
+
         back_to_serach_tab1 = st.button("Search page")
         if back_to_serach_tab1:
             st.switch_page("app.py")
- 
-           
- 
+
+
 if __name__ == "__main__":
     main()