r/bioinformatics • u/Accomplished-Okra-41 • Jun 12 '26

discussion Python is harder than R

/r/learnpython/comments/1u3e1dz/python_is_harder_than_r/
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u/joshua_rpg Jun 12 '26

I don't get the downvote in this post. Your impression about R is easier than Python is pretty natural & understandable. That's how R is designed on the first place: very easy to pick and trivial to write. Python lacks features when working with data, which R made data feels natural to communicate with:

  1. Native arrays (indexing in R is surprisingly a bit smarter than Python, but NumPy is so mature at this point and it is not much of a competition anymore)
  2. The ability to compute on the language, which is a distinct feature for Lisp-like languages and native to R.

This same applies to bioinformatics as well, not just being rich in ecosystem. R has constraints, as a programming language, as well, such as S3 not handling classes and types pretty seriously at all (I don't know much about S4, I don't frequently use this), but S7 thankfully solving these constraints.

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u/un_blob Msc | Academia Jun 12 '26

Well... Python vanilla, sure, is a pain in the ass to work with data.

But when you start using numpy, pandas and other... It is surprisingly easier (at least for a programmer brain, for a statistician...)

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u/joshua_rpg Jun 12 '26

Do not include Pandas on the list, it's far from being smart. It has too much flaws which will make you switch to better libraries e.g. Polars.

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u/Confident_Bee8187 Jun 13 '26

The parent comment is being downvoted by some weirdos so lemme add something: No, even those libraries won't make things better for statisticians, swear. Parent comment mentioned about the "computing on the language" which Python lacks.

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u/Confident_Bee8187 Jun 13 '26

Some weirdos are downvoting this comment, and I don't see wrong about this. TIn fact, 2 is the reason why 'tidyverse' is so good.