Personally I think Pandas gets too much credit, credit which really belongs with Numpy, and which was probably the reason that Pandas was built on it, rather th

Personally I think Pandas gets too much credit, credit which really belongs with Numpy, and which was probably the reason that Pandas was built on it, rather than say, Ruby, which in the late 2000s was a contender. This is especially true in the world of ML. Pandas is incredibly convenient (clone as it started out being, after all, of R's eponymous DataFrame, which is also incredibly convenient for feature engineering), but it's Numpy that does the heavy lifting.