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hadley

Re:Too many R packages: CRAN is inundated with submissions on Wednesday June 24, 2026 @12:06PM (#48661966)
You can learn about the theory that underlies tidyeval at https://adv-r.hadley.nz/quasiquotation.html. I'd claim that it's neither reinventing the wheel (because it solves problems that the base equivalents do not) nor bizarre (because it is backed by a deep, well-founded theory).
Re:Too many R packages: CRAN is inundated with submissions on Wednesday June 24, 2026 @10:20AM (#48660382)
CRAN is a weird universe, but not (just) for the reasons you mention. CRAN is still heavily human maintained which means that there's a high chance that an actual human will look at your packages (at least for your first package). This imposes a considerably higher barrier to entry than most package repos, and hence I suspect CRAN actually has a considerably lower percentage of slop.
Re:ggsql: A Grammar of Graphics for SQL on Monday April 20, 2026 @10:45PM (#47843915)
You’ll be able to adjust plots. But you have to do it with code, not UI.
Re:Nano Banana 2: Google's latest AI image generation model on Thursday February 26, 2026 @05:28PM (#47172906)
Let alone that Nano Banana 2 is Gemini Image 3.1
Re:Positron – A next-generation data science IDE on Friday July 25, 2025 @07:19AM (#44681916)
Students also pay :)
Re:Positron – A next-generation data science IDE on Friday July 25, 2025 @07:18AM (#44681914)
We're working on this! Education is really important to us so this is 100% a problem we want to solve.
Re:Positron – A next-generation data science IDE on Friday July 25, 2025 @06:58AM (#44681797)
We do discount heavily for academia: get 50% off for research and 100% off (i.e. free) for teaching. But I do get that our pro products largely solve problems that folks encounter in larger enterprises, and you may not see the value inside an academic department. I'm also always happy to learn how we could do better, please feel free to reach out to [email protected].
Re:Big Book of R on Friday April 11, 2025 @12:50PM (#43655889)
You might be interested in https://github.com/posit-dev/plumber2
Re:Big Book of R on Thursday April 10, 2025 @04:16PM (#43647659)
I've wrapped a bunch of providers with ellmer: https://ellmer.tidyverse.org
Re:Show HN: Create Music with R on Saturday July 13, 2024 @02:28PM (#40955850)
That’s exactly how ggplot (not 2!) worked: https://github.com/hadley/ggplot1
Re:Generalizing Support for Functional OOP in R on Tuesday May 28, 2024 @06:51PM (#40506437)
Why is that disappointing?
Re:The design philosophy of Great Tables on Thursday April 04, 2024 @02:46PM (#39934305)
You should check out https://siuba.org and https://plotnine.org :)
Re:R: Introduction to Data Science on Saturday March 02, 2024 @06:36PM (#39576865)
Hmmmm, I think that's something we could probably help with in dbplyr by providing something like `last_sql()` that would return the most recent SQL sent to the database. (By analogy to ggplot2::last_plot() and httr2::last_request()/last_response()).

I filed an issue so I don't forget about this: https://github.com/tidyverse/dbplyr/issues/1471

Re:R: Introduction to Data Science on Saturday March 02, 2024 @06:35PM (#39576855)
I love this framing :)
Re:R: Introduction to Data Science on Saturday March 02, 2024 @06:34PM (#39576848)
For the most common cases, the tidyverse now only requires {{ }}. This allows you to tell tidyeval functions that you have the name of a df-var stored in an env-var. Do you have specific cases that you find frustrating?
Re:R: Introduction to Data Science on Saturday March 02, 2024 @06:33PM (#39576838)
Oh, you mean the pro drivers? Unfortunately we can't give those away because we have to pay several $100k a year just to get access for our customers. Most of the pro drivers do have equivalent open source versions that you should be able to use instead.

Hmmm, I'd still try generating the table with quarto (since you can output word documents), or try gt (https://gt.rstudio.com), which I know has much greater control over output, and supports RTF output (https://gt.rstudio.com/reference/as_rtf.html) which should import cleanly into word.

Re:R: Introduction to Data Science on Saturday March 02, 2024 @06:31PM (#39576816)
(1) You might want to check out https://github.com/t-kalinowski/Rapp by my colleague Tomasz

(2) I think part of that is in scope for strict (https://github.com/hadley/strict). You might also be well served by adopting some more data validation tooling, e.g. pointblank (https://rstudio.github.io/pointblank/).

Re:R: Introduction to Data Science on Saturday March 02, 2024 @06:28PM (#39576792)
I'd highly encourage you to look into shiny more. No, it's not django, but it's a much richer framework than dash, and you can always bring your own HTML if what it generates for you isn't sufficient.
Re:R: Introduction to Data Science on Saturday March 02, 2024 @01:19PM (#39574524)
R definitely has its warts, but I strongly believe that underneath them lies a beautiful and quite elegant language that's extremely well suited to the challenges of data analysis. If you're already a programmer, you might find something like Advanced R (https://adv-r.hadley.nz) to be useful to get a sense of what R really is as a programming language.
Re:R: Introduction to Data Science on Saturday March 02, 2024 @12:57PM (#39574321)
We now provide snapshotted CRAN binaries (for many platforms) at https://packagemanager.posit.co.
Re:R: Introduction to Data Science on Saturday March 02, 2024 @12:57PM (#39574311)
I'd love to hear more about this because from my perspective renv does seem to solve 95% of the challenges the folks face in practice. I wonder what makes your situation different? What are we missing in renv?
Re:R: Introduction to Data Science on Saturday March 02, 2024 @12:56PM (#39574305)
We (Posit) have hired Hassan (the maintainer of plotnine) so this is great to hear :)
Re:R: Introduction to Data Science on Saturday March 02, 2024 @12:55PM (#39574294)
If you have specific issues around error messages and tracebacks please feel free to let me know directly or to file issues on Github. We really do care about the legibility of errors and tracebacks and me and my team have put a lot of effort into them in the last few years. But there's always room to do better and I'd love to know where the pain points are.

(The intersection of tidyverse and shiny tracbacks are a known pain point that's hard to resolve. Unfortunately shiny and tidyverse did a bunch of parallel work that took us in slightly different directions and now it's hard to re-align.)

One thing we are missing is a guide to reading traceback for newer users. Often experts can get a good sense of where the problem is, but we've failed to teach newer users how to get the most value from a traceback.

Re:R: Introduction to Data Science on Saturday March 02, 2024 @12:51PM (#39574257)
What are the premium packages you're talking about? As far as I know all of our R packages are 100% open source.

I'd love to hear more why you're using webshot etc to talk screenshots of your shiny app. A more typical workflow would be to generate a separate HTML/PDF with quarto/RMarkdown.

Re:R: Introduction to Data Science on Saturday March 02, 2024 @12:49PM (#39574247)
I have noodled on this problem a bit in https://github.com/hadley/strict, which I'm contemplating bringing back to life over the coming year. It's certainly very difficult to cover 100% of all possible problems, but I suspect we can get good coverage of the most common failure points (specifically around recycling and coercion) with a decent amount of work.
Re:R: Introduction to Data Science on Saturday March 02, 2024 @12:48PM (#39574229)
A lighterweight alternative to renv is to use Posit Public Package Manage (https://packagemanager.posit.co/) with a pinned date. That doesn't help if you're installing packages from a mix of places, but if you're only using CRAN packages it lets you get everything as of a fixed date.

And of course on the web side you have shiny (https://shiny.posit.co), which now also comes in a python flavour.

Re:R: Introduction to Data Science on Saturday March 02, 2024 @08:28AM (#39572377)
If you tell me what makes R hard to integrate into data pipelines I will do my best to fix it :)
Re:Pandoc on Friday February 02, 2024 @06:08PM (#39235711)
That's true, but quarto also has full support for Python and Jupyter notebooks, not to mention julia, and observable. It's really built from the ground up to be multi-language so that everyone can benefit from all the goodies in RMarkdown.
Re:Pandoc on Friday February 02, 2024 @02:52PM (#39233308)
And sweave is built on noweb :)

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