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I highly recommend checking out polars if you're tired of pandas' confusing API and poor ergonomics. It takes some time to make the mental switch, but polars is

I highly recommend checking out polars if you're tired of pandas' confusing API and poor ergonomics. It takes some time to make the mental switch, but polars is so much more performant and has a much more consistent API (especially if you're used to SQL). I find the code is much more readable and it takes less lines of code to do things. Just beware that polars is not as mature, so take this into consideration if choosing it for your next project. It also currently lacks some of the more advanced data operations, but you can always convert back and forth to pandas for anything special (of course paying a price for the conversion).

y1zhou 4y ago
On a related note, if you come from the R community and is already familiar with the `tidyverse` suite, `tidypolars` would be a great addition. https://github.com/markfairbanks/tidypolars https://github.com/markfairbanks/tidypolars
- mavam 4y ago
  Why does this use dot-based chaining as opposed to standard dplyr piping?
  - hugginn 4y ago
    Looks like it tries to make a dplyr-like experience for python, not replace dplyr in R.
falcor84 4y ago
>... of course paying a price for the conversion As the blog mentions, once Pandas 2.0 is released, if you use Arrows types, converting between Pandas and Polars will thankfully be almost immediate (requiring only metadata adjustments).