Customizing Matplotlib with style sheets and rcParams# Tips for customizing the properties and default styles of Matplotlib. There are three ways to customize Matplotlib: Setting rcParams at …

Restore the rcParams from Matplotlib's internal default style. Style-blacklisted rcParams (defined in matplotlib.style.core.STYLE_BLACKLIST) are not updated.

I'm not trying to make a good-looking figure here, but just to show some examples of customizing rcParams on the fly.

Set the current rcParams. group is the grouping for the rc, e.g., for lines.linewidth the group is lines , for axes.facecolor , the group is axes , and so on. Group may also be a list or tuple of …

You can also dynamically change the default rc settings in a python script or interactively from the python shell. All of the rc settings are stored in a dictionary-like variable called …

rcParams ['font.family'] = 'sans-serif' and for the font.family you set a list of font styles to try to find in order: rcParams [ 'font.sans-serif' ] = [ 'Tahoma' , 'DejaVu Sans' , 'Lucida Grande' , 'Verdana' ]

Matplotlib can use LaTeX to render text. This is activated by setting text.usetex: True in your rcParams, or by setting the usetex property to True on individual Text objects.

matplotlib.ticker.EngFormatter has gained the ability to show an offset text near the axis. Using logic shared with matplotlib.ticker.ScalarFormatter, it is capable of deciding whether the data …

Matplotlib needs fonts to work with its text engine, some of which are shipped alongside the installation. The default font is DejaVu Sans which covers most European writing systems. …

Let's set the default prop_cycle using matplotlib.pyplot.rc(). We'll combine a color cycler and a linestyle cycler by adding (+) two cycler 's together. See the bottom of this tutorial for more …