tidytable VS tidypolars

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 😄

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