Update loading_file.py

loading_file.py

@@ -45,22 +45,28 @@ def fetch_data():
     # Process the .ods file
     ods_file = BytesIO(ods_response.content)
     df = pd.read_excel(ods_file, engine="odf")
-    df.dropna(how="all", inplace=True)
+    
+    # Print columns to inspect what they look like
+    print("Columns before cleaning:", df.columns.tolist())  # For debugging purposes
+
+    # Drop unnecessary columns
+    df.dropna(how="all", inplace=True)  # Drop rows with all NaN values
     df.reset_index(drop=True, inplace=True)
 
-    # Check columns and rename appropriately
-    print("Columns before renaming:", df.columns.tolist())  # For debugging purposes
+    # Print columns after cleaning
+    print("Columns after cleaning:", df.columns.tolist())  # For debugging purposes
 
-    # Attempt to rename columns only if there are sufficient columns
-    if len(df.columns) >= 2:
+    # If we have extra columns, drop them
+    if len(df.columns) > 2:
+        df = df.iloc[:, :2]  # Keep only the first two columns
+    
+    # Rename columns if they match the expected ones
+    if len(df.columns) == 2:
         df.columns = ["Application Number", "Decision"]
     else:
         st.error("Insufficient data columns detected.")
         return None
 
-    # Only keep relevant columns
-    df = df[["Application Number", "Decision"]]
-
     df["Application Number"] = df["Application Number"].astype(str)
     return df