Data Mastery: SQL — Inner Join There are so many exciting projects out there in the Data World. Artificial Intelligence, Machine Learning, Neural Nets, Blockchain, and more are sweeping the technology industry. In order to get to the cutting-edge stuff, first and foremost, data needs to be stored, evaluated, and tested. The best place to do that is SQL (or a library that operates with SQL-like commands, ). see my article on Python’s Pandas library This series , will teach you the essential subjects. These are not exhaustive tutorials. Instead they are focused preparation guides — with brevity and efficiency in mind. It is meant for: Data Mastery: SQL Software Engineers who want to analyze their creation’s data Product Managers, Marketers, and others who want to be data-driven Beginning Data Scientists, Data Engineers, Data Analysts, or Business Intelligence Developers preparing for interviews See my resource list of the books I used to prepare for my big interview Each article will contain a brief technical explanation of the subject, an example question, and an answer. Follow up articles will contain challenging questions so you can evaluate your learning. This series does not come with accompanying data sets. The advantage to this is when you are on the drawing board, whether in an interview or project design, you do not have test data to play with. You have to think abstract. Inner Join A join matches up two tables around chosen columns that contain the same data. Then you can analyze data from both tables. Recall our daily_user_score table from earlier in the series: date | userid | sessionid | score ------------------------------------------ 2018–09–01 | 983489272 | 125 | 112 2018–09–01 | 234342423 | 34 | 112 2018–09–01 | 567584329 | 207 | 618 2018–09–02 | 983489272 | 126 | 410 2018–09–02 | 983489272 | 127 | 339 Let’s introduce a new table, user_revenue: userid | revenue -------------------- 983489272 | 100 234342423 | 33 567584329 | 57 305852827 | 8 867736361 | 29 An INNER JOIN only returns data where the chosen columns match up exactly in both tables. You choose columns with the ON/AND keywords and a condition. Say we want to see for each user who has played a game their total score and how much they paid our company. Here is the query: SELECT d.userid, SUM(d.score) AS total_score, r.revenue FROM daily_user_score AS d INNER JOIN user_revenue AS r ON d.userid = r.userid GROUP BY d.userid, r.revenue; And here are the results: userid | total_score | revenue --------------------------------- 234342423 | 112 | 33 567584329 | 618 | 57 983489272 | 861 | 100 Two things to note: It is good practice is to assign an alias to each table. Also notice the users in the results exist in both tables — this is the INNER JOIN. Try it yourself Find each user who has played a game, the most recent day they played, and how much money they paid. Answer SELECT d.userid, MAX(d.date) AS recent_date, r.revenue FROM daily_user_score AS d INNER JOIN user_revenue AS r ON d.userid = r.userid GROUP BY d.userid, r.revenue; This query returns: userid | recent_date | revenue --------------------------------- 234342423 | 2018–09–01 | 33 567584329 | 2018–09–01 | 57 983489272 | 2018–09–02 | 100 Thanks for reading! If you have questions feel free to comment & I will try to get back to you. Connect with me on Instagram @lauren__glass Connect with me on LinkedIn Check out my essentials list on Amazon Search for me using my nametag on Instagram!
