Web analytics data pattern in Data Analysis Python - Mini Project: Build & Apply

Web analytics data pattern

📖 Scenario: You work as a data analyst for a website. You have daily visitor counts for a week. You want to find which days had visitor counts above a certain threshold to understand busy days.

🎯 Goal: Build a small program that stores daily visitor counts, sets a threshold, finds days with visitors above that threshold, and prints those days with their counts.

📋 What You'll Learn

Create a dictionary with exact day names as keys and visitor counts as values

Create a variable for the visitor threshold

Use a dictionary comprehension to find days with visitors above the threshold

Print the resulting dictionary of busy days

💡 Why This Matters

🌍 Real World

Web analysts often need to find patterns in visitor data to understand peak usage days and plan resources accordingly.

💼 Career

This skill helps data analysts and marketers identify important trends and make data-driven decisions for website improvements.

1

Create the daily visitors dictionary

Create a dictionary called daily_visitors with these exact entries: 'Monday': 120, 'Tuesday': 85, 'Wednesday': 150, 'Thursday': 90, 'Friday': 200, 'Saturday': 75, 'Sunday': 110.

Data Analysis Python

# Create the daily_visitors dictionary with exact day names and counts
# Your code here

Hint

Use curly braces {} to create a dictionary. Put day names as keys and visitor counts as values.

2

Set the visitor threshold

Create a variable called visitor_threshold and set it to 100.

Data Analysis Python

daily_visitors = {'Monday': 120, 'Tuesday': 85, 'Wednesday': 150, 'Thursday': 90, 'Friday': 200, 'Saturday': 75, 'Sunday': 110}
# Create visitor_threshold variable and set it to 100
# Your code here

Hint

Just assign the number 100 to the variable visitor_threshold.

3

Find busy days using dictionary comprehension

Use a dictionary comprehension to create a new dictionary called busy_days that contains only the days from daily_visitors where the visitor count is greater than visitor_threshold. Use day and count as the loop variables.

Data Analysis Python

daily_visitors = {'Monday': 120, 'Tuesday': 85, 'Wednesday': 150, 'Thursday': 90, 'Friday': 200, 'Saturday': 75, 'Sunday': 110}
visitor_threshold = 100
# Create busy_days dictionary with days having counts > visitor_threshold
# Your code here

Hint

Use {day: count for day, count in daily_visitors.items() if count > visitor_threshold} to filter days.

4

Print the busy days dictionary

Write a print statement to display the busy_days dictionary.

Data Analysis Python

daily_visitors = {'Monday': 120, 'Tuesday': 85, 'Wednesday': 150, 'Thursday': 90, 'Friday': 200, 'Saturday': 75, 'Sunday': 110}
visitor_threshold = 100
busy_days = {day: count for day, count in daily_visitors.items() if count > visitor_threshold}
# Print the busy_days dictionary
# Your code here

Hint

Use print(busy_days) to show the filtered dictionary.