R

“It's a shame it's so hard to make it work for a large swath of production use cases.”

“have been a happy Apple Numbers and Wolfram Mathematica (and SPSS, PSPP, and R, and Python) user ever since”

“Nearly all languages designed for mathematics are 1-based - R, Matlab, Mathematica, etc.”

“R really is/was the superior traditional data science language”

“The only good use case for dynamic typing is notebooks (niche of R lang)”

“The fundamental advantage R holds over other languages/libraries is expressions.”

“Base R is arguably nicer to work with data than pandas is for example.”

“the ergonomics of the dplyr + ggplot + the rest of the tidyverse are very tough to beat”

“three of the Diátaxis categories map quite nicely onto R package constructs”

“I don't think there is a better language for wrangling tabular data to be honest.”

“R is a really powerful and flexible functional language”

“it taught me a lot of programming stuff and statistics stuff at the same time”

“R was too late to the game and catered too much to professional math/stats/datascience people”

“Such a comfortable language for data wrangling and analysis”

“R and Python don't work like this; if you install everything during the Docker image build, they will not suddenly trigger a lengthy recompilation”

“did everything with open source R then, and it worked !”

“give everyone Libreoffice , python, r, or any-other-linux-stuff”

“I had mostly stopped doing that kind of work and moved on to R for my bioinformatics things.”

“while it's great, there are little things that it can't do that Excel can.”

“python can integrate into production systems whereas R was (and maybe still is) geared towards writing reports”

“R and Matlab workflows have been fairly stable for the past decade”

“it is impressive that R is able to transcend in the interactivity with just internet browser”

“Rs copy on write, for example makes it a much more functional language without unintended side effects”

“R is a serious scientific programming language used in non-trivial programs for industrial applications”

“R has a clunky feel with a bunch of modules that can be a challenge to automate.”

“The amount of ceremony and constant API changes just to have something as an argument in a function drove me mad.”

“R is not good at looping over hundreds of files in the gigabytes”

“I don't see R as much easier, there are plenty of ugly things as well there.”

“R makes for much simpler cleaner code, less silent errors, and the 1 indexing makes dealing with biological sequences much less hassle.”

“R is great for EDA, but really doesn't work well for iteratively building larger software projects”

“writing custom loops (or functional equivalents with map or reduce) was pretty clunky last I tried it”

“R is made for the way statisticians work and think, not the way computer programmers work and think”

“If I want to wrangle, explore, or visualise data I’ll always reach for R.”

“R definitely is an efficient DSL for doing stats this way, but it’s a painful way to build a durable piece of software.”

“R is nice nice, but do they really want to learn a "niche" language”

“In R and Julia tables are great, and they are libraries.”

“If you optimize on what is best for science then I think it is hard not to argue that Python (and R) are the best choices.”

“R is perhaps the closest, because it has data.frame as a 'first class citizen'”

“once you get used to the building blocks it gives you, it has all these powers to do very dynamic things in very easy ways”

“The R programming language was a mess for data wrangling, but once it was popular, people built things like the tidyverse or the data.table library.”