df = pd.read_csv('sales_data.csv')
total_revenue = df['revenue'].sum()

add error handling for missing file and missing column

try:
    df = pd.read_csv('sales_data.csv')
    if 'revenue' not in df.columns:
        raise ValueError("Column 'revenue' not found in data")
    total_revenue = df['revenue'].sum()
except FileNotFoundError:
    print("Error: sales_data.csv not found")
    total_revenue = 0

filtered_data = []
for item in data:
    if item['revenue'] > 1000:
        filtered_data.append(item)

change the loop to a list comprehension

filtered_data = [item for item in data if item['revenue'] > 1000]

def calculate_mrr(subscriptions):
    active = [s for s in subscriptions if s['status'] == 'active']
    return sum(s['price'] for s in active)

add docstring and inline comments

def calculate_mrr(subscriptions):
    """
    Calculate Monthly Recurring Revenue from subscription data.

    Args:
        subscriptions (list): List of subscription dicts with 'status' and 'price'

    Returns:
        float: Total MRR from all active subscriptions
    """
    # Filter for only active subscriptions
    active = [s for s in subscriptions if s['status'] == 'active']

    # Sum up monthly prices
    return sum(s['price'] for s in active)