Essential SQL Commands for Data Science
Tags: sql, datascience, database, beginners
Published: 2023-03-11 17:57:22

**Introduction**
Structured Query Language (SQL) is a widely-used programming language used to manage and manipulate relational databases. As a data scientist, SQL is an essential skill to have as it enables you to retrieve and manipulate data from databases, which are typically the source of most data used in data science. In this article, we will cover the essential SQL commands for data science.

**SELECT**
The SELECT command is the most commonly used command in SQL. It is used to retrieve data from one or more tables in a database. The syntax for the SELECT command is as follows:


```
SELECT column_name(s)
FROM table_name
WHERE condition

```


- 'column_name(s)' refers to the columns you want to retrieve from the table.
- 'table_name' refers to the name of the table you want to retrieve data from.
- 'WHERE' is an optional clause that allows you to filter the data based on a condition.

For example, if you wanted to retrieve all the data from the "orders" table, you would use the following command:


```
SELECT *
FROM orders;

```


**WHERE**
The WHERE command is used to filter data based on a condition. The syntax for the WHERE command is as follows:


```
SELECT column_name(s)
FROM table_name
WHERE condition

```


- 'condition' is the condition that the data must meet in order to be retrieved.
For example, if you wanted to retrieve all the orders where the order amount was greater than $100, you would use the following command:


```
SELECT *
FROM orders
WHERE order_amount > 100;

```


**ORDER BY**
The ORDER BY command is used to sort the data in a specified order. The syntax for the ORDER BY command is as follows:


```
SELECT column_name(s)
FROM table_name
ORDER BY column_name(s) ASC|DESC

```


- 'column_name(s)' refers to the column(s) you want to sort the data by.
- 'ASC' is used to sort the data in ascending order (from lowest to highest).
- 'DESC' is used to sort the data in descending order (from highest to lowest).

For example, if you wanted to retrieve all the orders from the "orders" table and sort them in descending order based on the order amount, you would use the following command:


```
SELECT *
FROM orders
ORDER BY order_amount DESC;

```

**GROUP BY**
The GROUP BY command is used to group data based on one or more columns. The syntax for the GROUP BY command is as follows:


```
SELECT column_name(s)
FROM table_name
GROUP BY column_name(s)

```


- 'column_name(s)' refers to the column(s) you want to group the data by.
For example, if you wanted to retrieve the total order amount for each customer from the "orders" table, you would use the following command:


```
SELECT customer_id, SUM(order_amount)
FROM orders
GROUP BY customer_id;

```


**JOIN**
The JOIN command is used to combine data from two or more tables based on a common column. The syntax for the JOIN command is as follows:


```
SELECT column_name(s)
FROM table1
JOIN table2
ON table1.column_name = table2.column_name

```


- 'table1' and 'table2' refer to the tables you want to join.
- 'column_name' refers to the common column between the two tables.
For example, if you had two tables "orders" and "customers" and you wanted to retrieve the customer name and order amount for each order, you would use the following command:


```
SELECT customers.customer_name, orders.order_amount
FROM orders
JOIN customers
ON orders.customer_id = customers.customer_id;

```

**DISTINCT**
This command is used to remove duplicates from the result set. The syntax for the DISTINCT command is as follows:


```
SELECT DISTINCT column1, column2, column3
FROM table_name;

```


**LIMIT**
This command is used to limit the number of rows returned in the result set. The syntax for the LIMIT command is as follows:


```
SELECT column1, column2, column3
FROM table_name
LIMIT 10;

```

In conclusion, these are some essential SQL commands that are commonly used in data science. A good understanding of these commands can help in performing data manipulation and analysis tasks efficiently. However, there are many other SQL commands that are also important for data science, and it is recommended to explore and learn them for a better understanding of SQL.