[Pandas plots](https://pandas.pydata.org/pandas-docs/stable/visualization.html "pandas documentation") provides the "basics to easily create decent looking plots" from data frames. It provides about 70% of what I want to do day-to-day. Importantly, it lacks robust faceting capabilities.

"[Seaborn](https://seaborn.pydata.org/ "Seaborn: statistical data visualization") is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics." Seaborn makes beautiful plots but is geared toward specific statistical plots, not general purpose plotting. It does have a powerful [faceting utility function](http://seaborn.pydata.org/tutorial/axis_grids.html) that I use regularly.