51–60 of 66 posts
RStudio-2022.07.2-576 cannot start without R installed by the look of it: Error reading R script (), system error 2 (No such file or directory); Unable to find libR.dylib in expected locationswithin R Home directory /Library/Frameworks/R.framework/Resources
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As a relatively new programmer who entered it through statistics, I've still yet to have a better UX or "it just works" moment than using the tidyverse. Years after moving to Julia, Python, and Rust I still go back to R to do any tabular data work. Speed isn't an issue, I always have data.table, and I'm productive in a way that I could only hope to be while doing non tabular data tasks. RStudio is the perfect IDE. RE…
R is great, and so are some of the packages that lead to the tidyverse, but I think the latter was a bit too much. Re-inventing what already worked with new packages, always overloading R syntax in weird ways (looking at you, ggplot2). I've actually found myself moving back to base R for many of the more basic manipulation tasks.
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As a relatively new programmer who entered it through statistics, I've still yet to have a better UX or "it just works" moment than using the tidyverse. Years after moving to Julia, Python, and Rust I still go back to R to do any tabular data work. Speed isn't an issue, I always have data.table, and I'm productive in a way that I could only hope to be while doing non tabular data tasks. RStudio is the perfect IDE. RE…
I've found the Jupiter lab IDE to be ideal for my DS and EDA workflows, which typically involves having several notebooks, scripts, and terminal windows open in the IDE. I switched from preferring R to python because having a global shared state across everything in RStudio kept switching the working directory or loading a different file than expected, and I just had very little confidence that things I wrote in R wo…
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> acknowledges the shitshow that is the python library/package/environment management I'm puzzled by this and wonder if you can provide some examples. The scientists I know tend to have incredibly disorganized R code, with a bunch of hard-coded paths and a single global environment in their home directory that all their R packages get installed to. Even stuff that seems critically important like reproducible science…
Most of the replies to your query have addressed the big issue, which is that "data scientists" are almost universally mediocre (at best) coders. It's endemic to that job position and is guaranteed to be language-invariant. One factor that isn't helping generations younger than mine (mid-50's) is the continual evolution of tools that remove the user from all the underlying parts. I recently worked with someone who to…
VScode feels more refreshing as compared to RStudio. I love the extensions within VScode that allows it more flexibility as compared to RStudio. Also ability to view hex code as colors in the editor itself. Plus the ability to sync settings using GitHub is so convenient when using multiple computers. On the flip side, Rstudio is more convenient for beginners and being very R focused helps to focus on the "Statistics and data munging".
As for the Rstudio as a company, they have supported Python in the past but with the Quarto they went to extend beyond that. I feel Quarto is still work in progress and has more ambitious outlook as compared to RMarkdown. RStudio cloud is a good option when one have to use specific version of R and alleviates the "Reproducibility" issue to some extent. Especially, when someone does not want to deal with Docker or similar platform. I think RStudio cloud is one of my favorite offering from the company.
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Agree. Org-babel makes the alternatives look like toys.
"Org-Mode" requires the use of Emacs, though, correct? Can you offer a tool that doesn't involve having to join that cult, I'm asking for a friend who's already a loooooong time member of a completely different cult. One with less RSI, and RMS ;)
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R is great, and so are some of the packages that lead to the tidyverse, but I think the latter was a bit too much. Re-inventing what already worked with new packages, always overloading R syntax in weird ways (looking at you, ggplot2). I've actually found myself moving back to base R for many of the more basic manipulation tasks.
Base R is loved only by those who were unlucky enough to spend years using it when there was no alternative.
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My workflow for the past year has been develop/analyze in Rstudio and port to Python when ready to deploy to production. Notebooks and VSCode still feel cumbersome to me and not designed as an analytics-first solution. The time needed to re-write a script in another language, and often using different packages, seems more than made up for by the ease of use of Rstudio.
I honestly don't understand why we all went this route of "port to Python". I mean we do it too (not my choice) but it really makes no sense to me.