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Mogady OP t1_isthauc wrote

No man it doesn't work like that, yes you might be worried if this is the only thing you asked about, but The Nans part came late when I already used almost all the features but the last two had them and I had 5 min left, I can do that easily with Pandas but NumPy is a little complex a[~np.isnan(a).any(axis=1), :], also when you say 97% like you, what is us? let's say this month you worked with tabular data, and the next month you worked with a CV project, are you expected to remember all the syntax of openCV, Pandas, Numpy,Sklearn at that point?

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Azmisov t1_istr5kb wrote

You have 100 data scientists who all have a degree, career experience, maybe a few cool projects under their belt. If you can only pick three of them, why not pick the ones that can solve a problem faster and show a little more skill in coding? Tough, but if there's a lot of competition for a job, that's just how it goes. Also you said you were also allowed to use the documentation, which I think is pretty reasonable, so you don't have to have the entire API memorized.

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