Member-only story
Pandas alternatives: Polars for super-fast DataFrames in Python
The New Kid on The Block : Why is Polars Booming for Data Manipulation
Non-Member can read full story here.
If you’ve done data manipulation in Python, Pandas is probably familiar to you. It is the Swiss Army knife of data analysis — flexible, powerful and familiar. But let’s face it: as datasets increase in volume and workflows grow more complex, Pandas starts to get the feeling of gasping for air. If you have ever had to wait minutes for a Pandas operation to finish, you know what I mean.
This is where Polars comes into play — the new kid on the block that makes big promises to take your data processing to new heights. Pandas is the reliable sedan you need to get you from point A to B. It is fast, efficient, and designed to tackle new-age data problems.
A Short Story: The Trigger For Trying Out Polars
Several month ago I was working on project that analyzed millions rows of records in customer database. Pandas was not doing the job, but just enough to get by. Operations like grouping and aggregating data took forever, and I constantly faced memory problems. Polars was mentioned in passing by one friend as “Pandas on steroids.” Skeptical but desperate, I…
