10 Most Important SQL Statements to Know to Get a Job

As a data scientist, one of the most important skills you can have is the ability to manipulate and extract insights from large datasets. And when it comes to querying and analyzing data, SQL is one of the most powerful and widely used tools at your disposal.

But with so many SQL statements to choose from, where do you even begin? In this article, we’ll explore 10 of the most important SQL statements for data science tasks, along with examples of how you can use them to gain insights from your data.

1. SELECT Statement

The SELECT statement is used to retrieve data from one or more tables. It allows you to specify the columns you want to retrieve and the conditions that must be met for a row to be included in the result set. For example, let’s say you have a table called “orders” with columns “order_id”, “customer_id”, “order_date”, and “total_amount”. To retrieve the order IDs and total amounts for all orders placed on or after January 1st, 2022, you could use the following SQL statement:

SELECT order_id, total_amount
FROM orders
WHERE order_date >= '2022-01-01';

2. COUNT Statement

The COUNT statement is used to return the number of rows that match a specified condition. For example, let’s say you have a table called “customers” with columns “customer_id”, “first_name”, and “last_name”. To count the number of customers with the last name “Smith”, you could use the…