Sites like FiveThirtyEight and The Economist usually have separate graphics departments who use nonstatistical tools like Illustrator to annotate and apply custom theming. Good visualization is an huge part of a persuasive argument, and so being able to do both is important (and languages like R have good native plotting as well)
Additionally, looking at the agate code Jupyter notebook, it appears that the processing syntax is very, very similar to pandas (despite the warning against it) aside from the print_bars method, so I'm confused about the specific utility of the module.
From the post comments, after someone else noted the similarities too:
> You're right, most of my problems with pandas are not in its interfaces. My problems there are with the overhead of the numpy dependency, its confusing handling of text, nulls, etc. (inherited from numpy) and its documentation aimed at advanced users rather than beginners.