如何用Python通过12次循环实现月度数据聚合？（有周度代码参考）

Overview #

This guide adapts your existing weekly data aggregation code to generate monthly results via a 12-month loop.

Key Implementation Steps #

• Reuse your weekly aggregation logic within a loop over each month (1-12)
• Filter weekly data to only include entries belonging to the current month
• Validate each monthly result against raw data to catch discrepancies
• Jump to Sample Code

Sample Monthly Aggregation Loop (Python) #

# Your existing weekly aggregation function (example)
def aggregate_weekly_data(weekly_entries):
    return {
        'total_sales': sum(entry['sales'] for entry in weekly_entries),
        'avg_customers': sum(entry['customers'] for entry in weekly_entries) / len(weekly_entries)
    }

# Sample weekly data structure (replace with your actual data)
weekly_data = [
    {'month': 1, 'week': 1, 'sales': 1500, 'customers': 45},
    {'month': 1, 'week': 2, 'sales': 1800, 'customers': 52},
    # ... rest of weekly entries
]

# 12-month loop for monthly aggregation
monthly_aggregates = []
for month_num in range(1, 13):
    # Filter weeks for the current month
    month_weeks = [entry for entry in weekly_data if entry['month'] == month_num]
    if not month_weeks:
        # Handle months with no data
        monthly_aggregates.append({'month': month_num, 'total_sales': 0, 'avg_customers': 0})
        continue
    # Reuse weekly aggregation function
    monthly_stats = aggregate_weekly_data(month_weeks)
    monthly_stats['month'] = month_num
    monthly_aggregates.append(monthly_stats)

# Output results
for result in monthly_aggregates:
    print(f"Month {result['month']}: Sales = ${result['total_sales']}, Avg Customers = {result['avg_customers']:.1f}")

Critical Edge Cases to Consider #

Months with no weekly data (e.g., a new business starting mid-year) should return default values instead of causing errors.

Visualization Reference #

Here’s a placeholder for a monthly aggregation chart:
Monthly Sales Aggregation Chart

内容的提问来源于stack exchange，提问作者trizy