pandas is a great example of data science code at its best and its worst. If you look at the source code you will see every object and every function allows for

pandas is a great example of data science code at its best and its worst. If you look at the source code you will see every object and every function allows for way too many variations in input options and therefore about 20 conditional statements. For instance, I believe DataFrame's init method can take a dictionary, DataFrame, Series, etc. versus a class method for each one. Contrast that to requests where the public interface is a nice requests.get, requests.post. Yet, have a csv file you are only uploading once or twice to peak at? Then its super efficient. I think my biggest issue is all the effort that goes into pandas-like api's, i.e. https://github.com/ibis-project/ibis https://github.com/ibis-project/ibis. To me, it doesn't make sense to take something stable and known (SQL) and build a complex DSL so it works like pandas.