10 SQL Statements for 90% of Your Data Science Tasks

SQL (Structured Query Language) is an essential tool for data scientists, as it allows them to extract and manipulate data from databases. Here are 10 SQL statements that can be used for 90% of data science tasks:

1. SELECT: The SELECT statement is used to retrieve data from a database. It allows you to specify which columns you want to retrieve, as well as any conditions that must be met.
2. FROM: The FROM statement is used to specify the table or tables from which you want to retrieve data.
3. WHERE: The WHERE statement is used to filter data based on a specified condition. For example, you could use it to retrieve all the data for a particular time period, or only the data for a specific location.
4. GROUP BY: The GROUP BY statement is used to group data based on one or more columns. This can be useful for creating summary reports or aggregating data.
5. HAVING: The HAVING statement is used to filter data that has been grouped using the GROUP BY statement. It is similar to the WHERE statement, but is used specifically for grouped data.
6. ORDER BY: The ORDER BY statement is used to sort the data in your result set. You can sort by one or more columns, and specify whether you want the data sorted in ascending or descending order.
7. LIMIT: The LIMIT statement is used to limit the number of rows returned by your query. This can be useful for testing your queries or when dealing with large datasets.
8. JOIN: The JOIN statement is used to combine data from two or more tables based on a common column. This is essential for creating complex queries that combine data from multiple sources.
9. UNION: The UNION statement is used to combine the results of two or more SELECT statements into a single result set. This can be useful for combining data from different tables or databases.
10. SUBQUERIES: Subqueries are nested queries that can be used as part of a larger query. They are useful for creating more complex queries and for filtering data based on the results of another query.

By mastering these 10 SQL statements, data scientists can perform a wide range of data manipulation tasks, from simple data retrieval to complex analysis and reporting.