Can we calculate more than one aggregate statistic while grouping? Surely we can!

For example, from the `audi_cars` table, we can calculate the maximum `price` and `tax` for each `year`.

SELECT AVG(price) AS "avg_price", AVG(tax) AS "avg_tax", year
FROM audi_cars
GROUP BY year

> Please note, while grouping you can put non-aggregated function within `SELECT` statement **only** if it figures within `GROUP BY`, otherwise - it has to be aggregated.

> Also note, that in the example above without aliases (`AS`) there will be two columns with identical names, which is unacceptable in SQL.

> Another note: you can use aggregate functions for ordering after `GROUP BY` statement. It will filter based on calculations within groups.

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.

More aggregate statistics!

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