Michael Gicheru

A month or two ago someone posted a link to their really amazing set of LLM system instructions for writing #rstats code with good tidy/NSE patterns. (They were also good for humans!) Does anyone recall who or where that was?

Ah, was mistaken then. Base R's `file.choose()` is probably the next best thing. Or `choose.files()` for multiple files and much more customisable.
L

I think it's the same? The rstudioapi package is largely compatible with positron

There’s a billboard in Nairobi advertising a luxury development with the tagline “luxury is waking up to lush green views”. And it really it goes to the heart of how neoliberal approaches to development screw over poor countries. They really are paving paradise to put up a parking lot.

Look, I just want all of the #rstats peeps out there to know - this is why the @rconsortium.bsky.social exists. We direct money to projects that directly support the R language and community. Apply and engage with others who are just as enthusiastic and committed to this language as you are.

To remove the need to use them, you could use the {janitor} package to clean your variable/column names. For example:

```
library(janitor)
x <- data.frame("Month Name" = 1:12) |> clean_names()
```

This should turn the column name to month_name and allow you to refer to it without quotes.

You typically don't need those while working with R. I think it comes up because of how you are creating/reading in variable/column names eg from excel. The names probably have spaces in them hence the need to use ' or " or `. You can totally work with them as is but R does not play well with them

I know a guy

Would you consider having literate programming a first class feature? Scripts with special comments could be compiled into a pdf/html etc?

Otherwise, looks really good!

oh hi! I know what you're thinking, insurance sounds super boring. trust me it's not, and we have the panelists to prove it! ⤵️

Thank you! I'll add it to the list!

Thank you so much, this is helpful!

I am trying to improve upon a package that primarily uses matrices. But it's limited by the two-dimensional nature of them, and arrays seem like the natural step up.

Hello #rstats hivemind,

Does anyone know of any good reading material for arrays in R? Particularly multi-dimensional arrays?

Looking for a product scientist to join us on the teamworks soccer group (my team)!

Happy to answer any questions 😁

ats.rippling.com/en-CA/teamwo...

{tinytable} is a dead simple, ultra-flexible, and dependency-free #Rstats 📦 to turn data frames into beautiful tables: html, word, pdf, latex, typst, markdown, etc.

v0.10.0 has cool new features and important bug fixes. Check out the detailed tutorials at:

vincentarelbundock.github.io/tinytable/

Best table making in #rstats. Hands down. Cannot recommend it enough

nation DAILY©NATION Black Wednesday: Nine killed, 400 injured as protests rock 27 counties Nine people were killed, about 400 injured, and 61 arrested on Wednesday as at least 27 counties witnessed protests marking the first anniversary of the June 25, 2024, demonstrations that saw youth protesters storm Parliament.

The final tally of yesterday’s protests in #Kenya. Nine killed, 400 injured and 61 arrests. All killed by the police because the president will not listen to the young people who put him in power.

Ok found a solution. Turns out scales::label_number(style_negative = "parents") does this.
Note to future self: read the documentation of functions!!

Hey #rsats hivemind, does anyone have a custom function to format negative numbers/percentages to have brackets instead of negative signs for a table generated by {tinytable}?

This is fun! A merge of my 2 interests: #Rstats and #gamedev🤌 On top of that it is a source of inspiration for learning the new #S7 classes.
I am really thinking about making making turn-based RPG in R using procedural generation, but incorporating #LLM never came to mi mind! Really cool!🙌
#OOP

Hi #rstats friends!

I'm starting consulting! I've had a great journey in academia working with brilliant people, and while it's bittersweet (and a bit scary!), I'm excited for this next step. I'll still be maintaining {greta} and am hoping to be even more involved with the R community.

1/n

Screenshot of Google Colab's 'Change runtime type' dialog box showing runtime options. The dropdown menu displays language options including Julia, Python, and R. Hardware accelerator options show T4 GPU, A100 GPU, L4 GPU, and v5e-1 TPU. A message at the bottom offers access to premium GPUs

Julia has joined Python and R as a native kernel in Google Colab for a complete JuPyteR experience! Now you can use Julia with a free T4 GPU and leverage packages like Reactant without complex setup.

Details: github.com/googlecolab/...

#JuliaLang #Colab #DataScience

It's the lack of any arrow between 9 and 17 for me Clive

The 2nd wave of uv is here — developers of other systems building on top of uv to make new and effortless workflows that use Python virtual environments behind the scenes 🤩

So maybe more on pak/rig integration

I do have to say though, pak, renv and rig are really great tools and have changed how I work with R.

I feel like uv is a lot more frictionless for package and project management.

The equivalent in R would be pak+renv+rig. I would need to learn 3 tools and their quirks vs one tool with uv. I believe this is one of the few places a unified tool excels compared to decoupling, add onto the caveat that the 3 tools in R, from my experience, don't have great interoperability

Reproducible Data Science Environments with Nix Simplifies the creation of reproducible data science environments using the Nix package manager, as described in Dolstra (2006) <ISBN 90-393-4130-3>. The included `rix()` function generates a complete...

Use Nix, and all your worries will be forgotten: docs.ropensci.org/rix/