In this section we show how to select rows and/or columns from a
DataFrame. We can
select data with expressions or select data with square bracket indexing.
The Expression API is key to writing performant queries in
Polars. The simplest way to get started with the Expression API is to get familiar with the
select methods in this section.
Although they may give the same output, selecting data with expressions or square bracket indexing are not equivalent. The implementation of selecting data with expressions is completely different from the implementation of selecting data with square bracket indexing.
We strongly recommend selecting data with expressions for almost all use cases. Square bracket indexing is perhaps useful when doing exploratory data analysis in a terminal or notebook when you just want a quick look at a subset of data.
For all other use cases we recommend using expressions because:
- expressions can be parallelized
- the expression approach can be used in lazy and eager mode while the indexing approach can only be used in eager mode
- in lazy mode the query optimizer can optimize expressions