Python Polars: The Definitive Guide

Chapter 9. Combining Expressions

A Note for Early Release Readers

With Early Release ebooks, you get books in their earliest form—the author’s raw and unedited content as they write—so you can take advantage of these technologies long before the official release of these titles.

This will be the 9th chapter of the final book. Please note that the GitHub repo will be made active later on.

If you have comments about how we might improve the content and/or examples in this book, or if you notice missing material within this chapter, please reach out to the editor at [e-mail].

Now that you understand the fundamentals of expressions and know various methods to continue them, it’s time to learn how to combine them.

Combining expressions is necessary whenever the Series you want to construct is based on more than one value or column. This happens to be the case more often than you might think: for example, when you want to compute the ratio between two Float columns, filter rows based on multiple conditions, or concatenate multiple String columns into one.

In fact, you’ve already combined expressions several times in the previous chapters. Let’s look at an example from Chapter 7 to refresh your memory:

fruit = pl.read_csv("data/fruit.csv")
fruit.filter(pl.col("is_round") & (pl.col("weight") > 1000))

shape: (2, 5) ┌────────────┬────────┬────────┬──────────┬────────┐ │ name │ weight │ color │ is_round │ origin │ │ --- │ --- │ --- │ --- │ --- │ │ str │ i64 │ str │ bool │ str ...