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import pandas as pd | |
from scipy.stats import pearsonr | |
df = pd.read_csv("traffic.csv") | |
total_pageviews = df['pageviews'].sum() | |
average_daily_pageviews = df['pageviews'].mean() | |
print("Total Pageviews:", total_pageviews) | |
print("Average Daily Pageviews:", average_daily_pageviews) | |
total_events = df['events'].sum() | |
event_distribution = df['events'].value_counts() | |
print("Total Events:", total_events) | |
print("Event Distribution:\n", event_distribution) | |
country_distribution = df.groupby('country')['pageviews'].sum() | |
print("Geographical Distribution:\n", country_distribution) | |
df['CTR'] = df['clicks'] / df['pageviews'] # Calculate CTR | |
overall_ctr = df['CTR'].mean() | |
print("Overall CTR:", overall_ctr) | |
print("CTR by Link:\n", df.groupby('link')['CTR'].mean()) | |
correlation, _ = pearsonr(df['pageviews'], df['clicks']) | |
print("Correlation between Pageviews and Clicks:", correlation) | |