update app.py

app.py

@@ -182,51 +182,47 @@ if file_upload:
         else:
             st.error("Unsupported file type. Please upload a GeoJSON or KML file for polygons.")
 
+    # Display a preview of the dataframe
     if locations_df is not None:
-        # Display a preview of the points data
         st.write("Preview of the uploaded points data:")
         st.dataframe(locations_df.head())
 
-        # Create a LeafMap object to display the points
-        m = leafmap.Map(center=[locations_df['latitude'].mean(), locations_df['longitude'].mean()], zoom=10)
-
-        # Add points to the map
-        for _, row in locations_df.iterrows():
-            m.add_marker(location=[row['latitude'], row['longitude']], popup=row.get('name', 'No Name'))
-
-        # Display map
-        st.write("Map of Uploaded Points:")
-        m.to_streamlit()
-
-        # Store the map in session_state
-        st.session_state.map_data = m
-
-    if polygons_df is not None:
-        # Display a preview of the polygons data
-        st.write("Preview of the uploaded polygons data:")
-        st.dataframe(polygons_df.head())
-
-        # Create a LeafMap object to display the polygons
-        m = leafmap.Map(center=[polygons_df.geometry.centroid.y.mean(), polygons_df.geometry.centroid.x.mean()], zoom=4)
+        # Check column names in the uploaded data
+        st.write("Column names in the uploaded data:", locations_df.columns)
+
+        # Check for latitude and longitude columns in different cases
+        latitude_column = None
+        longitude_column = None
+        
+        for col in locations_df.columns:
+            if 'lat' in col.lower():
+                latitude_column = col
+            if 'lon' in col.lower() or 'long' in col.lower():
+                longitude_column = col
+
+        if latitude_column is None or longitude_column is None:
+            st.error("Latitude and/or Longitude columns not found in the uploaded file. Please make sure the data includes these columns.")
+        else:
+            # Create a LeafMap object to display the points
+            m = leafmap.Map(center=[locations_df[latitude_column].mean(), locations_df[longitude_column].mean()], zoom=10)
 
-        # Plot polygons on the map
-        for _, row in polygons_df.iterrows():
-            m.add_geojson(geojson=row['geometry'].__geo_interface__)
+            # Add points to the map
+            for _, row in locations_df.iterrows():
+                m.add_marker(location=[row[latitude_column], row[longitude_column]], popup=row.get('name', 'No Name'))
 
-        # Display map
-        st.write("Map of Uploaded Polygons:")
-        m.to_streamlit()
+            # Display map
+            st.write("Map of Uploaded Points:")
+            m.to_streamlit()
 
-        # Store the map in session_state
-        st.session_state.map_data = m
+            # Store the map in session_state
+            st.session_state.map_data = m
 
     # Process each point
-    if locations_df is not None:
+    if locations_df is not None and latitude_column and longitude_column:
         for idx, row in locations_df.iterrows():
-            latitude = row['latitude']
-            longitude = row['longitude']
+            latitude = row[latitude_column]
+            longitude = row[longitude_column]
             location_name = row.get('name', f"Location_{idx}")
-            # st.write(f"Processing {location_name} (Lat: {latitude}, Lon: {longitude})")
 
             # Define the region of interest (ROI)
             roi = ee.Geometry.Point([longitude, latitude])
@@ -261,17 +257,15 @@ if file_upload:
                 if result:
                     # Extract just the numeric value, not the dictionary with 'NDVI' label
                     calculated_value = result.getInfo()
-                    # Display the result as a numeric value, not as a dictionary
-                    # st.write(f"Result for {location_name}: {calculated_value['NDVI'] if 'NDVI' in calculated_value else calculated_value}")
-
                     # Store the result in session state
                     st.session_state.results.append({
                         'Location Name': location_name,
                         'Latitude': latitude,
                         'Longitude': longitude,
-                        'Calculated Value': calculated_value['NDVI'] if 'NDVI' in calculated_value else calculated_value  # Only store the numeric value
+                        'Calculated Value': calculated_value
                     })
 
+
     # Generate the dynamic filename
     filename = f"{main_selection}_{sub_selection}_{start_date.strftime('%Y/%m/%d')}_{end_date.strftime('%Y/%m/%d')}_{shape_type}.csv"