SQL tutorial: five SQL skills that data scientists need to master

Introduce

Structured query language （SQL） Is the preferred programming language for data practitioners to retrieve data stored in relational databases . Writing effective query requests is no longer considered a necessary skill , It is a basic skill of data scientists . This trend can be seen in DS The job posting and interview cycle specifically includes SQL Experience to support .

Besides programming ( Python )、 machine learning 、A/B Beyond testing and statistics , Data scientists are also often responsible for defining and extracting data from multiple sources to build indicators of interest . Unfortunately ,SQL Still an underrated skill , And there is not enough data for scientists to fully realize its versatility and importance .

In the past few months , I have been in close contact with senior data scientists and hiring managers of major technology companies . One of the most acclaimed suggestions I have received is to master SQL Skills and know how to extract data effectively .

So , I created a trilogy post that is specially coded for beginners . It goes from simple to medium difficulty through step-by-step practice LeetCode The problem is . If you have recently started SQL The journey , I suggest you review the following three articles before reading this article ：1. Easy、 2. Easy/Medium and 3. Medium.

problem 1： Total by gender

Write a SQL Query to find the total score of each gender every day .

Sort the result table by gender and date

The query result format is as follows ：

Scores table:
+-------------+--------+------------+--------------+
| player_name | gender | day        | score_points |
+-------------+--------+------------+--------------+
| Aron        | F      | 2020-01-01 | 17           |
| Alice       | F      |