bug fixing

backend/app.py

@@ -278,8 +278,17 @@ async def get_schools(
             # Filter by distance using pre-geocoded lat/long from database
             # Use vectorized haversine calculation for better performance
             lat1, lon1 = search_coords
-            lat2 = schools_df["latitude"].values
-            lon2 = schools_df["longitude"].values
+
+            # Handle potential duplicate columns by taking first occurrence
+            lat_col = schools_df.loc[:, "latitude"]
+            lon_col = schools_df.loc[:, "longitude"]
+            if isinstance(lat_col, pd.DataFrame):
+                lat_col = lat_col.iloc[:, 0]
+            if isinstance(lon_col, pd.DataFrame):
+                lon_col = lon_col.iloc[:, 0]
+
+            lat2 = lat_col.values
+            lon2 = lon_col.values
 
             # Vectorized haversine formula
             R = 3959  # Earth's radius in miles
@@ -293,11 +302,8 @@ async def get_schools(
             distances = R * c
 
             # Handle missing coordinates
-            distances = np.where(
-                pd.isna(schools_df["latitude"]) | pd.isna(schools_df["longitude"]),
-                float("inf"),
-                distances
-            )
+            has_coords = ~(pd.isna(lat_col) | pd.isna(lon_col))
+            distances = np.where(has_coords.values, distances, float("inf"))
             schools_df["distance"] = distances
             schools_df = schools_df[schools_df["distance"] <= radius]
             schools_df = schools_df.sort_values("distance")