Matplotlib's main API is pretty terrible. But it's just fine for the simple plots that scientists and engineers are often needing (e.g., just plot y vs. x). It's also pretty straightforward to get publication-quality plots. Bokeh can handle simple plotting and more complex visualizations, but it is aimed mostly at interactive visualizations rather than plotting for publication. For now, matplolib is the only real option for that in the Python world.

Matplotlib inherits most of its baggage from originally being meant to mimic Matlab plotting that many were then familiar with. As an aside, I find the pandas interface to plotting with matplotlib to generally be much easier to work with.

This. Where I work, a lot of the scientists use matlab. Transferring from that to matplotlib is relatively simple. Also, making publication quality graphics is what I use it for. If I want to make something interactive these days, I tend to just put it on the web...

Did you use something before Bokeh that you preferred, or is your comment based on Bokeh being generally better than Matplotlib?

I should clarify that my experience is pretty narrow in the python space. The comment was based on my (recent) experiences in the land of jupyter notebooks -- first using matplotlib and then switching to bokeh and finding the api to be more straightforward.