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).
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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/