R Programming

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Please use this as a forum to discuss R, and learn more about it. If you have any questions about how to do specific things in R, this is the place to ask.

Getting Started

You can download R here.

You can download RStudio here. RStudio IDE, which is supported by Posit PBC, is a powerful and well-developed IDE for R. Other development environment options include Emacs addon Emacs Speak Statistics and VSCode.

Other Communities

Other communities that may be of interest across the fediverse:

Please send @a_statistician a message to recommend additional communities to add to this list.

Learning resources:

R for Data Science - a good introductory book for learning R. Start here if you're overwhelmed.
Big Book of R - collection of more than 500 online books/tutorials covering various aspects of R. Some links are to paid books with previews, but most links are to free online textbooks.

founded 1 year ago

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Introduce yourself! (self.r_programming)

submitted 1 year ago by a_statistician to c/r_programming

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In the interests of making this community home for those of us who are reddit refugees, let's go ahead and introduce ourselves.

Some suggested things to comment on/include in your introduction:

Tidyverse, base, or data.table?
Are you primarily a user, a developer, or in between?
How long have you been using R?
What other languages do you use?
What do you use R for? Statistics? generative art? data wrangling?
Are you using R primarily for work, fun, hobbies, or something else?
Are you a hex sticker collector? Why or why not?
Where are you on the data engineering <----> pure statistics continuum?
What's your favorite obscure package?

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[–] MalditoBarbudo 2 points 1 year ago* (last edited 1 year ago)

I'm @MalditoBarbudo, a data scientist at an ecology and forestry research center.

I've been using R for 14 years, starting as an user and ending as a developer. I've done also some python, sql and web development (html, js and css).

I prefer tidyverse, it fit perfectly with my mental logic, but I reckon that sometimes data.table is needed (but in that case dtplyr comes to help!).

I maintain several packages (sapfluxnetr, meteospain...) and collaborate in others (meteoland, medfate...). I also maintain a web with several shiny apps for forest data visualization (LFC).

My favourite obscure package changes every week or so, but if I have to choose one, lately I've been playing with rayshader, trying to create nice 3d map plots.