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Modern Pandas (Part 2): Method Chaining

tomaugspurger.github.io

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Re: Modern Pandas (Part 2): Method Chaining

#71

Earlier quoted context omitted.

Given how much of a role pandas seems to have played in the growth of Python over the last decade I suspect you aren't really the only person that loves pandas :) I think you'll find a similar selection bias if you ask HN commenters what they think about Excel.

Good point, also there are a lot of similarities between Excel and Pandas as well. I think this also is a fundamental distinction between normal SWEs and People who use Excel as well as Data Engineers. You always start with data, and you have no control over it. So this means: 1. you need state base programming env (excel, Jupyter) 2. you need to look at it to see whats there (plots) I guess HN is mostly comprised of…

Agreed about the similarities between Excel and Pandas. I started out as more of an data analyst and am now a SWE and I think one of the things that SWEs who dismiss Excel and Jupyter don't understand is how little you can assume about the data you might be working with.

If you're an analyst who knows some VBA, that can be super useful but it would probably be a mistake to try to make your VBA-driven applications bullet proof. Nobody wants you to spend that much time on it, and the odds that something completely out of your control will change and break it anyway are quite high.

Re: Modern Pandas (Part 2): Method Chaining

#72
For large workflows, you'll probably want to move away from pandas to something more structured, like Airflow or Luigi.

How are they a replacement for pandas ? I thought the would or at least could wrap around them for scheduled execution / chaining. You would still need a Data frame handling glibrart no?

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