Complete the code to identify the key metric that measures the number of times a post is seen.
metric = "[1]" # This metric counts how many times content is displayed
Impressions count how many times a post or content is shown to users, regardless of interaction.
Complete the code to calculate the engagement rate as a percentage.
engagement_rate = (engagements / [1]) * 100 # Calculate engagement rate
The engagement rate is usually calculated by dividing total engagements by the number of followers, then multiplying by 100 to get a percentage.
Fix the error in the KPI calculation to correctly measure click-through rate (CTR).
ctr = (clicks / [1]) * 100 # Calculate click-through rate
Click-through rate (CTR) is calculated by dividing clicks by impressions, then multiplying by 100 to get a percentage.
Fill both blanks to create a dictionary comprehension that maps each post to its engagement rate if the post has more than 1000 impressions.
engagement_rates = {post: ([1] / impressions) * 100 for post, impressions, [2] in posts_data if impressions > 1000}The engagement rate is calculated using engagements divided by impressions. The third variable in the loop should be clicks to unpack the data correctly.
Fill all three blanks to create a filtered dictionary of posts with a high CTR (greater than 5%).
high_ctr_posts = {post: ([1] / [2]) * 100 for post, [3] in posts_data.items() if ([1] / [2]) * 100 > 5}To calculate CTR, divide clicks by impressions. The loop unpacks each post and its data dictionary. The condition filters posts with CTR above 5%.