But what if we want to choose a car with small mileage, let it be less than 5000 miles. We need to set the condition to a numeric column.

This also can be done with `WHERE` statement. For example,

SELECT *
FROM audi_cars
WHERE mileage < 5000

Comparison operators you also can use for numeric columns: 
- `<` - less than
- `<=` - less-equal
- `>=` - greater-equal
-`>` - greater
- `=` - equal
- `<>` - not equal.

Now let's try to find the cheapest car in this dataset.

SQL is a domain-specific programming language widely used by data scientists, analysts, etc for manipulating and extracting necessary data. Nowadays, SQL is a must-have point in the CV for every potential analyst, data scientist. In this course, you will be introduced to the very basics of SQL.

In this section, you will be introduced to the very basics of SQL: extracting one or multiple columns from a database.

In this section, you will learn how to filter observations so only necessary rows will be extracted.

In this section, you will learn about the usage of different aggregating functions for your table, such as minimum, maximum, average... 

In this section, you will learn how to sort your table, even having filters and aggregate functions applied to a table.

In this section, you will learn about grouping observations and usage of this principle.

This chapter is designed for users who have completed the previous sections and want to consolidate knowledge.

Number filtering

Oplossing