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Meanwhile, every time I use an external library (including pandas) I still think numpy does everything you need, and does it well, and people just haven't bothered to learn it properly and keep reinventing the wheel.

(no disrespect to to the package in the article or OP who I know is active in this thread. just a general motif that I keep coming across in python).

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I used numpy a lot for my PhD research, and think you're right, in the sense that things could have been much more numpy array centric (just like how in R the dataframe is a tiny structure around arrays).

There are a lot of problems you encounter when using arrays for data analysis, like some of their funky behavior with strings [0], but it seems like extending arrays, or building new types of numpy arrays would have been better than new data structures like the pandas Series.

(pandas folks thought a lot about these problems so I could be very wrong).

[0]: https://mchow.com/posts/pandas-has-a-hard-job/

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