SQL GROUP BY
Starting here? This lesson is part of a full-length tutorial in using SQL for Data Analysis. Check out the beginning.
In this lesson we'll cover:
- The SQL GROUP BY clause
- GROUP BY column numbers
- Using GROUP BY with ORDER BY
- Using GROUP BY with LIMIT
- Practice problems
SQL aggregate function like
SUM have something in common: they all aggregate across the entire table. But what if you want to aggregate only part of a table? For example, you might want to count the number of entries for each year.
In situations like this, you'd need to use the
GROUP BY clause.
GROUP BY allows you to separate data into groups, which can be aggregated independently of one another. Here's an example using the Apple stock prices dataset:
SELECT year, COUNT(*) AS count FROM tutorial.aapl_historical_stock_price GROUP BY year
You can group by multiple columns, but you have to separate column names with commas—just as with
SELECT year, month, COUNT(*) AS count FROM tutorial.aapl_historical_stock_price GROUP BY year, month
ORDER BY, you can substitute numbers for column names in the
GROUP BY clause. It's generally recommended to do this only when you're grouping many columns, or if something else is causing the text in the
GROUP BY clause to be excessively long:
SELECT year, month, COUNT(*) AS count FROM tutorial.aapl_historical_stock_price GROUP BY 1, 2
Note: this functionality (numbering columns instead of using names) is supported by Mode, but not by every flavor of SQL, so if you're using another system or connected to certain types of databases, it may not work.
The order of column names in your
GROUP BY clause doesn't matter—the results will be the same regardless. If you want to control how the aggregations are grouped together, use
ORDER BY. Try running the query below, then reverse the column names in the
ORDER BY statement and see how it looks:
SELECT year, month, COUNT(*) AS count FROM tutorial.aapl_historical_stock_price GROUP BY year, month ORDER BY month, year
There's one thing to be aware of as you group by multiple columns: SQL evaluates the aggregations before the
LIMIT clause. If you don't group by any columns, you'll get a 1-row result—no problem there. If you group by a column with enough unique values that it exceeds the
LIMIT number, the aggregates will be calculated, and then some rows will simply be omitted from the results.
This is actually a nice way to do things because you know you're going to get the correct aggregates. If SQL cuts the table down to 100 rows, then performed the aggregations, your results would be substantially different. The above query's results exceed 100 rows, so it's a perfect example. Try removing the limit and running it again to see what changes.
Learn about the difference between "Group By" in SQL and Python.