Our dependencies policy (https://matplotlib.org/devel/min_dep_policy.html) states that we'll only

• support minor versions of Python initially released in the previous 3 years
• support minor versions of numpy initially released in the previous 3 years or oldest that supports the minimum python version (which ever is higher)

We will bump the minimum python and numpy versions as we can every minor and major release, but never on a patch release.

Python 3.5 was released on Sept. 13, 2015 (https://www.python.org/dev/peps/pep-0478/) and numpy 1.10 was released on Oct. 6th, 2015; we should thus be able to drop support for them in Matplotlib 3.1. Python 3.6 brings in quite a few nice features (f-strings, __fspath__, ordered kwargs); the last one, in particular, is relevant for our "batch setters" (artist.set(foo=bar, baz=quux), rather than "just" being a source-code nicety). A quick look at numpy 1.11's changelog doesn't suggest anything particularly relevant, but if anyone needs it they should feel free to bump the dependency.

For those keeping score at home, the following relevant release dates are
Python 3.6: Dec. 23, 2016
Python 3.7: Jun. 27, 2018
numpy 1.11: Mar. 27, 2016
numpy 1.12: Jan. 15, 2017 (np.full respects the filler's dtype -> #10571/#12379)
numpy 1.13: Jun. 07, 2017
numpy 1.14: Jan. 06, 2018 (np.genfromtxt defaults to latin-1 -> #13621)
numpy 1.15: Jul. 23, 2018 (adds np.histogram_bin_egdes -> #8638)