How to Group Data Using Polars .group_by()
One of the most common tasks you’ll encounter when analyzing Polars data is the need to summarize it. You can use the Polars .group_by() method to create groupings based on column values. A related summarization technique is aggregation, where you take a sequence of related values and condense them into a single value.
By the end of this tutorial, you’ll understand that:
- You can summarize data using aggregation.
- You can use
.filter()to view specific data. - Using
.group_by()allows you to summarize one or more columns of your data. - Your time series data can be grouped using
.group_by_dynamic(). - You can match summarized data with the original data using window functions.
- Pivot tables allow you to group and aggregate rows