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Comment by d--b | Hacker News Reader

Yeah it is dated. Python got hyped and now people learn it because data science hires python people, and data science pays well, not because they care.

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I used to interview people for data science roles. We let people use whatever language they wanted in the interview. I expected to see a split between Python and R, but the reality was that almost everyone used Python, which was a bit of a surprise.

It's even more surprising to me given that Pandas is such a poorly designed library. (Apparently the guy who developed it was learning Python while he was writing Pandas.) I saw candidates make mistakes due to quirks in Pandas often. And quirks can be extra deadly with data science code: https://news.ycombinator.com/item?id=33797339 So overall it's a weird situation. I think a big factor is that a lot of data scientists are newbie programmers who are just piling in to what's popular & established.

even more surprising is matplotlib .... the most infuriating plotting library I've encountered and yet its de facto standard for most of data science now!

That comes from mimicking Matlabs plotting API, as a way to move people from Matlab into scientific python. "It's a feature not a bug", a bit taken to an extreme. But it was successful.

>Apparently the guy who developed it was learning Python while he was writing Pandas

This makes a lot of sense. I remember trying to learn Pandas before v0.24 and finding the syntax changing a lot between versions which just confused me even more. I later learnt some R and was blown away by how easy tidyverse, and even base R data.frames were to use.

I remember Python being hyped for being a good beginner language and a good web programming language(Django, Flask).

It does seem that Python has settled into a niche as one of the mainstream data science languages.

There's a saying "Python is the second-best language for everything".

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