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?
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.
I’ve been reading books about GLM and Bayesian Statistics and am using the “glm” function and “brms” and “rstanarm” packages. They’re pretty fun. If any of you are interested in using those packages know that rstan is a bit weird which is why I’m using R 4.0.2 and rtools42 and not the current versions.
I’m @a_statistician! I’m a statistics professor at a midwestern state university. I teach R and python programming and research data visualization.
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Tidyverse. I’ve always wanted to get into data.table, but I find that tidy verbs are easier to teach and explain to my students, and it’s more important to me that the code is readable than that it is a bit faster in production, since I spend most of my time trying to understand WTF students’ code is doing.
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I’m primarily a user, though I have contributed to several packages and I enjoy development - I just don’t spend as much time on it as I do in R generally.
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I’ve been using R since 2009, give or take, so almost 15 years now.
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I also teach Python, though it’s definitely not my default language anymore. I can accomplish minor tasks in JavaScript or C++ given enough time and googling, but R is the primary language I’m fluent in and using day to day. I have a profound hatred of Java that stems back to the trauma of taking AP Comp Sci I in C++ and then AP Comp Sci II in Java, with no transition to teach the basics of Java.
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I use R for data visualization and data wrangling, though I wish I had enough time to play with generative art, because it seems really cool.
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I use R for work, fun, and hobbies, but fun and hobbies are usually work related because professor life is all-consuming.
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I am a total hex sticker whore. I still mourn laptop upgrades where I can’t transfer the hex stickers from laptop to laptop, but I am trying a new trick with my latest laptop: I put contact paper down first, so that I can pull all the stickers off at once and frame them after the laptop is retired.
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While my Ph.D. is in statistics, I would consider myself more on the data science side of things (e.g. right in the middle of the continuum) - I do a lot of data wrangling and visualization, and tend to not fit models unless I absolutely have to.
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I think evil.R might be the worst thing I’ve ever seen. As far as actually useful packages, I’ve contributed to ggpcp, which is a very neat package that allows you to make parallel coordinate plots with a mixture of categorical and continuous variables using tidy syntax - the nice part of the way it works is that you can usually track an entire observation through a series of variables because it breaks ties on the categorical axis.
I am a an engineering consultant, specializing in solar photovoltaic power systems.
- Tidyverse and Base R. I find people who do things the hard way tedious just to be pure.
- I suppose I am more of a user, because I haven’t released any of my packages.
- Almost 25 years.
- C++, Python. Many other languages as they have been needed, from Assembly to VBA and Matlab.
- R is to me what Excel is for a lot of people… a full featured calculator. I compose a lot using RMarkdown/Quarto. I tend to build reproducible pipelines for data or simulations.
- Both, though at work there is some pressure to use more Python.
- I have some stickers. I don’t have many.
- Probably closer to the data wrangling end.
onion… 3d space rotations made easy through obscure math (which way is the solar panel pointing anyway?)
