Why Polars uses less memory than Pandas
Processing large amounts of data with Pandas can be difficult; it’s quite easy to run out of memory and either slow down or crash.
The Polars dataframe library is a potential solution.
While Polars is mostly known for running faster than Pandas, if you use it right it can sometimes also significantly reduce memory usage compared to Pandas.
In particular, certain techniques that you need to do manually in Pandas can be done automatically in Polars, allowing you to process large datasets without using as much memory—and with less work on your side!
This does require you to use the correct Polars APIs.
And it won’t solve all your problems, even if it does make your life easier.
In this article we’ll:
- See how we can optimize Pandas