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That’s cool and everything, but I don’t know many DS people who still use R. Maybe academics still do?
by professionalguy 5y ago
That’s cool and everything, but I don’t know many DS people who still use R. Maybe academics still do?
- legobmw99 5y agoIt’s sadly still quite popular in the research world
- jazzyjackson 5y agoWhat about it makes you sad?
- vore 5y agoNot the original poster, but the language has some really weird edges. For instance, check out this wild behavior: http://www.hep.by/gnu/r-patched/r-lang/R-lang_41.html http://www.hep.by/gnu/r-patched/r-lang/R-lang_41.html
- deleted 5y ago[deleted]
- asdff 5y agoThis is because R borrows a lot of syntax from S. When R came out, statisticians were using S, so it was natural to make it like this. If they went another way, you'd get statisticians in mailing lists 20 years ago bemoaning how its so much not like familiar S, rather than regular old programmers 20 years later today who bemoan that R isn't like familiar python like what happens on HN whenever there is an R thread.
- vore 5y agoI think the behavior is so wildly inconsistent that it's not really justifiable, regardless of being a statistician or not: https://github.com/tidyverse/design/issues/13#issuecomment-407453348 https://github.com/tidyverse/design/issues/13#issuecomment-4...
- asdff 5y agoI mean compared to other languages these sorts of quirks might seem like big deals, but they rarely come up. You see that error, you copy paste and find a stack overflow thread explaining it, you know what to do next time and move on. R is certainly no C.
- hugh-avherald 5y agoIdiosyncrasies are not something unique to R. One could express the same surprise at an empty list being considered false in some contexts.
- kgwgk 5y agoAs far as weird edges go, that one is really, really mild. It may even be considered a good idea! For people interested in weirder things, check The R Inferno (I think it's somewhat outdated by now, though): https://www.burns-stat.com/documents/books/the-r-inferno/ https://www.burns-stat.com/documents/books/the-r-inferno/
- jsmith99 5y agoThat book isn't so much about R weirdness. It's more about teaching data scientists to consider the implications of practices like copying a huge table in memory on every loop iteration.
- rcthompson 5y agoR sees significant use both in academic/research settings and industry.
- wespiser_2018 5y agoThere are a lot of DS folks using it for Bayesian Statistics
- iafiaf 5y agoR is overwhelmingly used in bioinformatics. There is nothing quite like bioconductor. Most new tools/methods (for ex, in the scRNA-seq) release R packages first.
- asdff 5y agoWell I'd say conda is quite like bioconductor with the ease of installing relevant packages. scRNAseq has popular r packages like seurat but also popular python packages like scanpy.
- fatboy93 5y agoI didn't understand your comment, which is probably my fault. But you can absolutely install many bioconductor packages from conda. I love using conda as my environment manager rather than compiling and installing 1000p different libraries and tools. Also, I install mamba for drastically faster resolution of the dependencies.
- cardosof 5y agoReally depends on the application. For clean, concise and reproducible ad hoc statistical analytics and modelling, there isn't a better tool than tidyverse+tidymodels. It's a classic case of the best tool for the job. I usually create simple stuff in R and then move to bigger datasets and production in py+spark.
- mellavora 5y agotidyverse may be clean, but it is nowhere near as concise as data.table. data.table is also typically orders of magnitude faster.
- cardosof 5y agoThanks for the point of view, I can't argue since I don't really know data.table. Will check out!
- stanbiryukov 5y agoCheck out dtplyr- lazy data.table backend and tidyverse syntax
- Fomite 5y agoIt's the dominant language among academic statisticians.
- listenallyall 5y agoAlthough I agree and don't like R very much, I believe ggplot is still the gold standard for creating top-quality visualizations. None of the python (or other language) clones are quite as good. For projects where the end goal is a complex or detailed graph or plot, it's sometimes worth trudging through R to achieve the best final result.
- tonyarkles 5y agoYup, not a data scientist but often do data processing to analyze the outcome of experiments (drone-flight related). I'll use Python/Jupyter if there's a significant amount of clean-up that needs to happen, but R/ggplot is unbeatable if I'm trying to look at the data from different perspectives. As an example, I was trying to look at GPS data the other day and ggplot() + geom_point() + geom_density_2d() was an absolutely perfect way to better grok what was going on.
- otabdeveloper4 5y agoI've used Python since 1995, so I should be biased, but switching from Python to R is a huge productivity boost - like switching from Excel to Python. R is just years ahead.
- f6v 5y agoR absolutely dominates some of the life sciences. For example, most of the state-of-the-art bioinformatics tools are in R.