SQL GROUP BY Practice

Table of contents

1. 1. GROUP BY

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   Turn raw data into meaningful insights — learn how GROUP BY organizes, summarizes, and analyzes information in SQL.

   List of exercises Start now
   1. Introduction
      1. Introduction
      2. Get to know the table
   2. Aggregate functions
      1. Count the rows
      2. Count the rows, ignore the NULLS
      3. Count distinctive values in a column
      4. Find the minimum and maximum value
      5. Find the average value
      6. Find the sum
   3. GROUP BY
      1. Group the rows and count them
      2. Find min and max values in groups
      3. Find the average value in groups
      4. Group by a few columns
   4. HAVING
      1. Filter groups
      2. Filter groups continued
      3. Order groups
   5. Summary
      1. Summary

2. 2. GROUP BY in the Video Games Data

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   From top-selling hits to critically acclaimed titles—use GROUP BY to uncover key gaming insights.

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   1. Introduction
      1. Get to know the tables
      2. Cost-effective games
   2. Exercises
      1. Average production cost of good games
      2. Revenue for recent good shooters
      3. Game production statistics by year
      4. Profitable games by type
      5. Gross profit by company
      6. Productions statistics
      7. Identify good games
      8. Congratulations

3. 3. GROUP BY in the Store Sales Data

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   Unlock powerful insights with GROUP BY — analyze revenue, customer purchases, and sales trends.

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   1. Introduction
      1. Get to know the tables
      2. Purchases and categories
      3. Customers and the products they bought
   2. GROUP BY one column
      1. The average unit price for each category
      2. Number of purchases for each customer
      3. Total products quantity for each purchase
      4. Total number of units in stock for each category
      5. Number of purchases for each employee
   3. GROUP BY multiple columns
      1. Total purchases price for (customer, employee) group
      2. Minimum unit price for two-columns group
      3. Total purchases prices for each city and employee
      4. Purchases with products of given quantity
      5. Lowest and highest prices, and the number of purchases
   4. HAVING
      1. Customers with more than one purchase
      2. The number of products in category
      3. The number of purchases and customers for each city
      4. Minimum price for (customer, employee) group
      5. Total quantities
   5. GROUP BY exercises
      1. Count the statistics for purchases
      2. Filter the employees
      3. Filter the customers
      4. Number of products and total quantity for purchase
      5. Maximum number of products and maximum price for category
   6. GROUP BY with WHERE, HAVING and ORDER BY
      1. The number of discontinued products
      2. Number of employees reporting to an employee
      3. The number of customers in cities
      4. The number of purchases
      5. Purchases and quantity for each product
      6. Congratulations

4. 4. GROUP BY in the University Data

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   Explore university data with GROUP BY — analyze enrollments, grades, and academic performance trends with structured SQL queries.

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   1. Introduction
      1. Get to know the tables
      2. Course editions and lecturers
      3. Students who started at the same time
   2. GROUP BY one column
      1. Number of lecturers with each degree
      2. Number of course editions for each student
      3. Number of students for each grade
      4. Total number of lecture hours for each learning path
      5. The number of ECTS points each student can get
   3. GROUP BY multiple columns
      1. Number of students – then and now
      2. Number of students with the same grade
      3. Youngest student in each course edition
      4. Average students' final grade
      5. Lecturers' hours across terms
   4. HAVING
      1. Course editions with an average final grade over 50
      2. Students who enrolled for more than one course edition
      3. Most popular courses
      4. Lecturers who failed at least 5 students
      5. Congratulations

5. 5. GROUP BY in the Sports Data

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   Use GROUP BY to break down athlete performance — analyze key stats, track trends, and compare results across events.

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   1. Introduction
      1. Get to know the tables
      2. Athletes on podium
   2. GROUP BY one column
      1. Number of athletes per nationality
      2. Most popular first name
      3. Competitions' longest runs
      4. The best time for each country
      5. Average distance for country
   3. GROUP BY multiple columns
      1. Runners' total distance
      2. How many runners in each final
      3. Country's best place
      4. Average time of each discipline at the competition
   4. HAVING
      1. Average distance for country – revisited
      2. Really popular name
      3. Times worth a medal
      4. Athlete's participation in competitions
      5. Crowded finals
   5. More exercises
      1. Republics
      2. Average wind in Rio
      3. Run it all!
      4. Who ran a marathon?
      5. Country's best in 100 meters
      6. Disqualification statistics
      7. Most runs in 2016
      8. Marathoners' best times
      9. Marathoners' speeds
      10. Year of birth
      11. Congratulations

6. 6. GROUP BY in Blog Traffic Analysis

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   Use GROUP BY to explore blog traffic, reader interactions, and engagement trends.

   List of exercises Buy course
   1. Introduction
      1. Get to know the tables
      2. The traffic to the sign-up page
      3. The product traffic on May 1, 2020
   2. GROUP BY one column
      1. The number of articles in each category
      2. Article views in May 2020
      3. Traffic from articles to products in categories Dog Health and Dog Products, in May 2020
      4. The number of articles by author
   3. GROUP BY multiple columns
      1. Traffic generated by each author in May 2020
      2. Traffic from articles to product pages in May 2020
      3. The number of articles by author and category
      4. Traffic in May 2020 by article category
   4. HAVING
      1. Authors with exactly one article
      2. Articles with more than 1000 views in April 2020
      3. Articles with traffic to at least 10 different product pages
      4. Article-product pairs with traffic over 100 in March 2020
   5. GROUP BY exercises
      1. GROUP BY practice
      2. Authors with articles in only one category
      3. Authors with total article views of 50,000 or more
      4. Total traffic from each article category to each product category in May 2020
      5. Count of the articles without any traffic to product pages, by article category
      6. Articles with 20 or more views but no traffic to product pages
      7. Articles written in June 2020 with 1000 or more total views
      8. Congratulations

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