Post processing.py

    # Remove Non Existing Features In Test Data 
    feature_remove_list = [
            'balance_due',
            'collection_status',
            'compliance_detail',
            'payment_amount',
            'payment_date',
            'payment_status'
        ]
    
    train_data.drop(feature_remove_list, axis=1, inplace=True)

    
    
    # Remove String Data
    string_remove_list = ['violator_name', 'zip_code', 'country', 'city',
            'inspector_name', 'violation_street_number', 'violation_street_name',
            'violation_zip_code', 'violation_description',
            'mailing_address_str_number', 'mailing_address_str_name',
            'non_us_str_code', 'agency_name', 'state', 'disposition',
            'ticket_issued_date', 'hearing_date', 'grafitti_status', 'violation_code'
        ]
        
    train_data.drop(string_remove_list, axis=1, inplace=True)
    test_data.drop(string_remove_list, axis=1, inplace=True)
    
    
        
    # Fill NaN Lat Lon Values
    train_data.lat.fillna(method='pad',inplace=True)
    train_data.lon.fillna(method='pad',inplace=True)
    test_data.lat.fillna(method='pad',inplace=True)
    test_data.lon.fillna(method='pad',inplace=True)