dtplyr VS tidytable

Can’t say I’ve used it, but isn’t that what dtplyr is supposed to provide?

https://dtplyr.tidyverse.org/

# I am trying to follow the example at https://dtplyr.tidyverse.org/

FYI the developer of tidytable has been developing dtplyr for the Tidyverse. You might like that too!

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

https://dtplyr.tidyverse.org/ ?

If you want data.table speed, but using dplyr/tidy then dtplyr is a good package to have handy. Personally I love R, and choose R + NodeJS as my gotos for everything I do, and use Python only when I have to.

Also, that dataset is quite big, and the "base" Tidyverse will be excessively slow. You should supplement the "base" Tidyverse packages (i.e. dplyr and tidyr) with either dtplyr or dbplyr (+ duckDB). I'd suggest starting with dtplyr, which should handle 10M+ rows fine.

If you want, there's a "substitute" for dplyr called dtplyr (also part of the Tidyverse), which "translates" your dplyr/tidyr code into data.table behind the scenes, and allows you to make your modifications apply directly to the original dataset by default:

Install the dtplyr package and change your code to:

Get the best of both worlds (tidyverse + data.tables) with dtplyr, a data.table backend for dplyr.

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 😄