poorman VS tidytable

You might find the poorman package interesting: https://github.com/nathaneastwood/poorman

It's true that their packages are heavy on dependencies, and if that is a concern, you have alternatives: - poorman: no dependencies, same syntax as dplyr, but only includes basic verbs. - datawizard: low dependencies, slightly different syntax, has base-R implementations of most of dplyr / tidyr functions, plus some other goodies likes scaling, mean-centering, rank transforming, ... - And of course, data.table: 0 dependencies, ultra-fast (everything is written in optimized C under the hood), can manipulate much bigger data than the Tidyverse, and can do everything the tidyverse can when it comes to data wrangling (however, sometimes the tidyverse has convenience functions that make some operations shorter than with data.table). The downside is that data.table's syntax requires more efforts to learn / is less intuitive to read for neophytes.

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

And the Github link if you want to dive into the code.

Other than that you can check the news for other changes!

What do you think of this instead?

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.

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.

Github page - (if you want to browse the source code)