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Here's a comprehensive Python function to analyze website traffic data: ```python import pandas as pd import numpy as np from datetime import datetime def analyze_traffic_peaks(traffic_data): # Convert timestamp to datetime if needed traffic_data['datetime'] = pd.to_datetime(traffic_data['timestamp']) traffic_data['hour'] = traffic_data['datetime'].dt.hour # Calculate hourly traffic hourly_traffic = traffic_data.groupby('hour')['visitors'].mean() # Identify peak hours (top 25% of traffic) peak_threshold = hourly_traffic.quantile(0.75) peak_hours = hourly_traffic[hourly_traffic >= peak_threshold] return { 'peak_hours': peak_hours.index.tolist(), 'peak_traffic': peak_hours.values.tolist(), 'hourly_averages': hourly_traffic.to_dict() } ``` This function provides detailed insights into your website's peak traffic patterns!