tidypolars VS tidytable

I recommend trying tidypolars

There’s a tidypolars package that appears to be well-maintained https://github.com/markfairbanks/tidypolars

tidypolars is one I’ve seen. Still very new, but it’s built on top of polars (which is a little more like dplyr to begin with), so it’s much faster than pandas.

If I misunderstood your question - feel free to open a discussion with a small code example and we can talk through how you can do it in tidypolars.

Try out tidypolars. It's really close to tidyverse syntax and it's a lot faster than pandas as well

If you need speed, you should consider using dtplyr (or tidytable), or even dbplyr with duckdb.

What do you think of this instead?

Here's an example - I use this in a package I've built called tidytable. Here is the as_tidytable() function I use that uses method dispatch.

If you're having performance issues with dplyr you can also try out tidytable

I’d say tidytable is a better option these days as it supports more functions. Although I think dtplyr has improved on this front recently, but still lags. The author of tidytable contributes to dtplyr as well.

I know you said it 'feels much faster' which isn't exactly a data oriented comparison, but tidymodels performs very well. You can see one of the dplyr functions as step_* in tidymodels, for example mutate vs. step_mutate under recipes library. The author of tidytable, which uses data.table, had some revisions due to this conversation, just as an example.

Tidytable is what you might be looking for: https://markfairbanks.github.io/tidytable/, this will require a bit of refactoring (e.g group-bys happen as arguments in summarise/mutate). You'll get data.table like speed in a very compact & complete package.

People can also use tidytable and keep the same workflow they're already used to 😄