Update map.py

map.py

@@ -426,7 +426,41 @@ def find_lat_lon_columns(df):
     else:
         return None, None
 
+
+# Load dataset
+data_path = 'parsed_files_distance_embeds.h5'
+
+parsed = load_data(data_path).drop(columns=['embeddings'])
+parsed_responses = filter_dataframe(parsed)
+st.session_state['parsed_responses'] = parsed_responses
+st.dataframe(parsed_responses)
+
 my_dataset = st.file_uploader("Upload Parsed DataFrame", type=["csv", "xlsx"])
+
+if my_dataset is not None:    
+    if parsed: # save space by cleaning default dataset
+        parsed = None
+    try:
+        if my_dataset.type == "text/csv":
+            data = pd.read_csv(my_dataset)
+        elif my_dataset.type == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet":
+            data = pd.read_excel(my_dataset)
+        else:
+            st.error("Unsupported file type. Please upload a CSV, Excel or HD5 file.")
+            st.stop()
+        parser = filter_dataframe(data)
+        st.session_state['parsed_responses'] = parser
+        st.dataframe(parser)
+        st.success(f"Successfully loaded and displayed data from {my_dataset.name}")
+    except Exception as e:
+        st.error(f"An error occurred while reading the file: {e}")
+else:
+    parsed = load_data(data_path).drop(columns=['embeddings'])
+    parsed_responses = filter_dataframe(parsed)
+    st.session_state['parsed_responses'] = parsed_responses
+    st.dataframe(parsed_responses)
+
+
 map_1 = KeplerGl(height=800)
 powerplant = pd.read_csv('global_power_plant_database.csv')
 secret_bases = pd.read_csv('secret_bases.csv')