Create dataframe.py

dataframe.py

@@ -0,0 +1,27 @@
+import pandas as pd
+import streamlit as st
+
+def process_dataframe(ods_file):
+    try:
+        # Read the .ods file into a DataFrame
+        df = pd.read_excel(ods_file, engine='odf')
+
+        # Clean up unnecessary columns and rows
+        df.drop(columns=["Unnamed: 0", "Unnamed: 1"], inplace=True, errors='ignore')
+        df.dropna(how='all', inplace=True)
+        df.reset_index(drop=True, inplace=True)
+
+        # Identify and set the header row
+        for idx, row in df.iterrows():
+            if row['Unnamed: 2'] == 'Application Number' and row['Unnamed: 3'] == 'Decision':
+                df.columns = ['Application Number', 'Decision']
+                df = df.iloc[idx + 1:]
+                break
+
+        # Convert application numbers to strings
+        df.reset_index(drop=True, inplace=True)
+        df['Application Number'] = df['Application Number'].astype(str)
+        return df
+    except Exception as e:
+        st.error(f"Error processing the data: {e}")
+        return pd.DataFrame()  # Return an empty DataFrame on failure