process.py

import pandas as pd
import gradio as gr


def get_lat_lon(postcodes_df, postcode_mapping):

    try:
    
        postcode_mapping.rename(columns={'postcode': 'Postal code'}, inplace=True)

        # Normalize postcodes to ensure matching and count occurrences
        postcodes_df['Postal code'] = postcodes_df['Postal code'].str.lower().str.replace(' ', '')
        postcode_counts = postcodes_df['Postal code'].value_counts().reset_index()
        postcode_counts.columns = ['Postal code', 'count']
        
        # Normalize the postcodes in the mapping DataFrame
        postcode_mapping['Postal code'] = postcode_mapping['Postal code'].str.lower().str.replace(' ', '')
        
        # Merge the counts with the mapping data
        result_df = pd.merge(postcode_counts, postcode_mapping, on='Postal code', how='left')
        
        # Fill NaN values for latitude and longitude where postcode was not found in the mapping
        result_df['latitude'] = result_df['latitude'].fillna('')
        result_df['longitude'] = result_df['longitude'].fillna('')
        
        # Optionally, convert the DataFrame to a dictionary if needed, or work directly with the DataFrame
        results = result_df.to_dict(orient='records')
    
    except: 
        raise gr.Error('Make sure your file contains the postal codes under a column named "Postal code"')
    
    return results