A large e-commerce company wants to analyze customer behavior over time. You are tasked with aggregating transactions by customer ID to compute the total spent and number of purchases each month. Describe your approach using Pandas, including how you would handle date parsing and grouping by month.

def monthly_customer_summary(df): df['order_date'] = pd.to_datetime(df['order_date']) df['month'] = df['order_date'].dt.to_period('M') summary = df.groupby(['customer_id', 'month']).agg(total_spent=('total_amount', 'sum'), purchase_count=('order_id', 'count')) return summary.reset_index()