Essential SQL Commands for Data Science
Tags: sql, database, datascience, beginners
Published: 2023-03-13 18:35:38

Structured Query Language (SQL) is a programming language used for managing and manipulating data in a database. As a data scientist, having a strong understanding of SQL commands is essential to effectively work with databases and extract the information needed for your analysis. In this article, we'll cover some essential SQL commands for data science.

**SELECT**
The SELECT statement is the most commonly used SQL command for querying a database. It allows you to retrieve specific columns of data from a table based on certain conditions. The basic syntax is as follows:

```
SELECT column1, column2, ... 
FROM table_name 
WHERE condition;
```

For example, if you want to retrieve all the data from a table called "customers", you can use the following command:

```
SELECT * FROM customers;
```

This will return all the columns and rows of data from the customers table. You can also specify certain columns by replacing the * with the names of the columns you want to retrieve:

```
SELECT first_name, last_name, email FROM customers;
```
**WHERE**
The WHERE clause is used to filter data based on specific conditions. It allows you to retrieve only the data that meets the conditions you specify. The basic syntax is as follows:

```
SELECT column1, column2, ... 
FROM table_name 
WHERE condition;
```
For example, if you only want to retrieve data for customers who live in California, you can use the following command:

```
SELECT * FROM customers 
WHERE state = 'California';
```
This will return all the columns and rows of data from the customers table where the state column is equal to 'California'.

**GROUP BY**
The GROUP BY statement is used to group data based on one or more columns. It allows you to perform aggregate functions on the grouped data, such as calculating the average or sum. The basic syntax is as follows:

```
SELECT column1, aggregate_function(column2) 
FROM table_name 
GROUP BY column1;
```
For example, if you want to calculate the average salary of employees in each department, you can use the following command:

```
SELECT department, AVG(salary) 
FROM employees 
GROUP BY department;
```
This will return a table with two columns: department and the average salary for that department.

**ORDER BY**
The ORDER BY statement is used to sort data in ascending or descending order based on one or more columns. It allows you to easily view the data in the way that is most useful for your analysis. The basic syntax is as follows:

```
SELECT column1, column2, ... 
FROM table_name 
ORDER BY column1 ASC|DESC;
```
For example, if you want to sort the customers table by last name in descending order, you can use the following command:

```
SELECT * FROM customers 
ORDER BY last_name DESC;
```

**LIMIT**
The LIMIT statement is used to limit the number of rows returned by a query. It allows you to focus on a specific subset of the data that is most relevant to your analysis. The basic syntax is as follows:

```
SELECT column1, column2, ... 
FROM table_name 
LIMIT number_of_rows;
```
For example, if you only want to retrieve the first 10 rows from the customers table, you can use the following command:

```
SELECT * FROM customers 
LIMIT 10;
```

**JOIN**
The JOIN statement is used to combine data from two or more tables based on a related column between them. It allows you to merge data from different tables into a single table for analysis. The basic syntax is as follows:

```
SELECT column1, column2, ... 
FROM table1 
JOIN table2 
ON table1.column = table2.column;
```
For example, if you have a customers table and an orders table, and you want to retrieve the names of customers who have placed an order, you can use the following command:

```
SELECT customers.first_name, customers.last_name, orders.order_date 
FROM customers 
JOIN orders 
ON customers.customer_id = orders.customer_id;
```

This will return a table with three columns: first name, last name, and order date for all customers who have placed an order.

**SUM**
The SUM function is used to calculate the sum of a column in a table. It allows you to quickly calculate total values for numerical data. The basic syntax is as follows:

```
SELECT SUM(column_name) 
FROM table_name;
```
For example, if you want to calculate the total sales for all orders in an orders table, you can use the following command:

```
SELECT SUM(sales) 
FROM orders;
```
This will return a single value: the total sales for all orders in the orders table.

**COUNT**
The COUNT function is used to count the number of rows in a table. It allows you to quickly determine the size of a table or the number of rows that meet certain conditions. The basic syntax is as follows:

```
SELECT COUNT(*) 
FROM table_name;
```
For example, if you want to determine the number of orders in an orders table, you can use the following command:

```
SELECT COUNT(*) 
FROM orders;
```
This will return a single value: the total number of rows in the orders table.


SQL is a powerful language for managing and manipulating data in a database, and having a strong understanding of SQL commands is essential for any data scientist. In this article, we covered some essential SQL commands for data science, including SELECT, WHERE, GROUP BY, ORDER BY, LIMIT, JOIN, SUM, and COUNT. By mastering these commands, you'll be able to extract the data you need for your analysis and gain valuable insights from your data.

You can find more resources about SQL here:
DataCamp's "[SQL Commands for Data Scientists](https://www.datacamp.com/tutorial/tutorial-sql-commands-for-data-scientists)" tutorial
Level Up's "[13 SQL Statements for 90% of Your Data Science Tasks](https://levelup.gitconnected.com/13-sql-statements-for-90-of-your-data-science-tasks-27902996dc2b)"