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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
by ShredKazoo 4y ago
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 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.
- ImaCake 4y ago>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.
- zmmmmm 4y agoeven more surprising is matplotlib .... the most infuriating plotting library I've encountered and yet its de facto standard for most of data science now!
- dr_zoidberg 4y agoThat 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.