hadley

9 ms·

31.
by hadley 3y ago
Is there some way we could advertise this better? The quarto homepage already says “Quarto is a multi-language, next generation version of R Markdown from Posit, with many new new features and capabilities.” When talking about Quarto within
32.
by hadley 3y ago
There are few differences in performance due between the base pipe and magrittr due to the work we did in 2.0.0: https://www.tidyverse.org/blog/2020/11/magrittr-2-0-is-here/ . This release also cleaned up
33.
by hadley 3y ago
Just a small note that R is not pass-by-value, it’s more copy-on-modify. See some of the details at https://adv-r.hadley.nz/names-values.html
34.
by hadley 3y ago
Quarto will support output to typst in the upcoming 1.4 release: https://quarto.org/docs/prerelease/1.4/typst.html I think the big different between quarto and typst is the scope. quarto is a tool for combini
35.
by hadley 3y ago
A scale isn’t exactly a function because it also needs the inverse in order to draw axes and legends. And it turns out axes and legends are where most of the complexity of scales lie.
36.
by hadley 5y ago
This was fun to play around with. I made some very minor changes and posted at https://gist.github.com/hadley/d54895557fbb0fe0402d2277b9011... . It revealed to me that there's a buglet in `forcats::last()` ( https:
37.
by hadley 5y ago
Have you seen https://dtplyr.tidyverse.org ? It gives you the syntax of dtplyr and (almost all of) the speed of data.table.
38.
by hadley 5y ago
They don't often come with code, but one of my recent sources of R programming joy is the folks posting their generative art to twitter: https://twitter.com/search?q=%23rstats%20%23generativeart&sr...
39.
by hadley 5y ago
Ah yeah, connecting the dots in ggplot2 docs is hard. It's hard for us to document because, under the hood, the pieces quite decoupled and different pieces are responsible for different arguments. But since we last took a deep dive on
40.
by hadley 5y ago
I love the phrase "eviscerate a fresh data set" :D
41.
by hadley 5y ago
100% this :)
42.
by hadley 5y ago
Do you have any specific examples that illustrate the general problem? I'd love to better understand what you're looking for in docs.
43.
by hadley 5y ago
Yeah, that's my current position. It's possible that we might be able to add it in optionally (by adding a new `.by` argument to summarise and friends), but just the analysis to determine how it would affect existing code is a lot
44.
by hadley 5y ago
From dbplyr experience, folks want to be able to do stuff like `across(which(is.numeric), mean)`, which you can't do currently because dplyr doesn't know the column types (although it does maintain a list of the column names).
45.
by hadley 5y ago
acquero uses derive ( https://uwdata.github.io/arquero/api/verbs#derive ) which I rather like (it's better than mutate, IMO)
46.
by hadley 5y ago
FWIW the separate `group_by()` is one of my greatest design regrets with dplyr — I wish I had made `by` a parameter of `summarise()`, `mutate()`, `filter()` etc.
47.
by hadley 6y ago
We are in the middle of a process to systematically re-license as much as possible as MIT. More on that soon.
48.
by hadley 6y ago
Could you shoot me an email? I’m always on the lookout for pandoc freelancers.
49.
by hadley 7y ago
Doh - I filed an issue on our internal tracker to fix this
50.
RStudio becomes a public benefit corporation(blog.rstudio.com)
312 points by hadley 7y ago|49 comments
51.
by hadley 7y ago
A lot depends on what you’re doing. Most of the time, when I’m not doing data analysis, I don’t find pipes to be that useful so I don’t use them.
52.
by hadley 7y ago
Beware that apply() coerces data frames to matrices, which is time consuming and forces all columns to have the same type.
53.
by hadley 7y ago
Let’s keep the discussion civil please. People have legitimately different needs, and just because a package isn’t well suited to your needs doesn’t mean that it doesn’t help people with different backgrounds and goals.
54.
by hadley 7y ago
I don’t think anyone is arguing that the pipe should be the -only- form of composition. Just that it’s a useful form when you have a linear sequence of transformations. Sometimes it’s useful to force something close to being linear into a l
55.
by hadley 7y ago
Pretty much all of the individual components of the tidyverse were created before the tidyverse since it’s only 3 years old. But there’s no reason to use only the tidyverse. That’s not something I’ve ever recommended and it would be extreme
56.
by hadley 7y ago
If you find data.table more useful, you should by all means use it. My greatest regret about coining the word tidyverse is that for some reason people seem to think it’s a monolith. It’s not; you’re totally free to pick and choose whatever
57.
by hadley 7y ago
You are of course free to dispute what is in the tidyverse, but I pretty strongly believe that it is part of the tidyverse
58.
by hadley 8y ago
I think that is good advice but it’s not a great fit for R packages due to the requirements that CRAN has for package submission. I’ve wrapped up my recommended practices in usethis::use_mit_license().
59.
by hadley 8y ago
dplyr does not do deep copies. See discussion in https://adv-r.hadley.nz/names-values.html#df-modify
60.
by hadley 8y ago
You should take a look at tourrr which implements a bunch of "grand tour" algorithms in R. These take your on a smooth tour of random projections of your data, visualised in various ways (including into 3d if you have some red-blu

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