import pandas as pd
from datetime import datetime

def process_data(addresses_file, boundaries_file):
    """
    Reads address and boundary CSVs, merges them, and returns a consolidated DataFrame.
    """
    try:
        # Read the addresses and count occurrences of each TerritoryID
        address_counts = pd.read_csv(addresses_file).groupby('TerritoryID').size().reset_index(name='Address Count')

        # Read the boundaries file
        boundaries_df = pd.read_csv(boundaries_file)

        # Merge the address counts with the boundaries data
        merged_df = pd.merge(boundaries_df, address_counts, on='TerritoryID', how='left')

        # Fill missing address counts with 0 and ensure the column is integer type
        merged_df['Address Count'] = merged_df['Address Count'].fillna(0).astype(int)

        return merged_df

    except FileNotFoundError as e:
        raise FileNotFoundError(f"Error during data processing: {e}")
    except Exception as e:
        raise Exception(f"An unexpected error occurred during data processing: {e}")