A new version of Polars has landed with some important changes.

The easiest way to incorporate them in your workflow is this official migration guide: pola.rs/posts/polars-0…

Highlights include changes to horizontal aggregation and renaming of some key methods like group_by

Polars has fast-track algorithms for sorted data as I've written here: rhosignal.com/posts/polars-l…

Need to check if your column is sorted? Then you can use the .is_sorted method on a column to quickly check.

Learn more about sorted data in my online course: udemy.com/course/data-an…

One small feature in Polars that I find easier than in Pandas is setting the number of rows to display.

In Polars you do this with the pl.Config.set_tbl_rows function so use pl.Config.set_tbl_rows(4) for 4 rows.

Or if you want all the rows just run pl.Config.set_tbl_rows(-1)

Want to get accelerate your data analysis with Polars ASAP?

Check out my highly-rated course on Udemy with this discount code: udemy.com/course/data-an…

Topics covered include using lazy mode, streaming large datasets and data formats including CSV, Parquet, Excel and JSON

Need to understand *roughly* how many unique values there are in your data?

Polars has an approximate algorithm to estimate this in a speedier way.

In the example below the approx algo is out by just 0.5% while being more than 3x faster.

More info here: pola-rs.github.io/polars/py-pola…