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Re:Enhancing R: The Vision and Impact of Jan Vitek's Maintai... by mbreese on Thursday May 16, 2024 @08:54AM (#40377766)
It’s also training dependent.

It took a long time for Perl to go away from daily use in bioinformatics, solely dependent upon how common it was twenty years ago.

In our lab, there is me, a (mid career) polyglot who mixes Python, Go, Java, and R daily. I use tab delimited text files to transfer data. I also grew up coding in C++ and like learning new languages.

We also have a (mid career) staff scientist who grew up in Perl, but switched 100% to R and an (early career) postdoc who has always used 100% R. For both of these people, if work can be done in R, it is. If it can’t be done in R, they figure out how to do it in R anyway (even if that is shelling out to another program).

We also have a (young) grad student that is 95% Python. They try to keep to the Python tooling, even though they are quite aware of the R ecosystem.

There is a generational shift in the field, and it is more apparent each year. I find it interesting that Python took over from Perl first and now it’s trying to take over from R.

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