Matplotlib cannot find basic fonts

我是研究僧i 提交于 2019-11-28 17:48:32

This work for me::

$ sudo apt-get install msttcorefonts -qq

I had this exact same problem on a Vagrant VM running Ubuntu Xenial 64-bit. No matter how many fonts I had already installed, matplotlib was having a problem with the "system" font name "sans-serif". I fixed it by:

  • Stopping Jupyter
  • Installing font-manager: sudo apt install font-manager
  • Cleaning the matplotlib cache directory: rm ~/.cache/matplotlib -fr
  • Restarting Jupyter.

No more error messages about sans-serif.

To get it to work, I had to combine the two current top answers. Here's what worked for me:

$ sudo apt install msttcorefonts -qq
$ rm ~/.cache/matplotlib -rf

A solution for Windows users, when confronted with the warning:

UserWarning: findfont: Font family ['serif'] not found. Falling back to DejaVu Sans
(prop.get_family(), self.defaultFamily[fontext]))
  1. Delete the fonts located in matplotlib's cache.
    Cache's location: import matplotlib as mpl; print(mpl.font_manager.get_cachedir())

  2. Find matplotlib's font directory. The path might be similar to
    C:\Miniconda3\pkgs\matplotlib-2.2.2-py36_1\Lib\site-packages\matplotlib\mpl-data\fonts\ttf

  3. Copy necessary fonts like Computer Modern to this directory.

The warning may persist, but your plots' font should change appropriately.

try all the methods above, not work for me.

my way to solve this is a little dirrent cause I'm using conda on ubuntu server running jupyter

locate -b '\mpl-data'

find a folder

/usr/share/matplotlib/mpl-data

then I add the simhei fonts into the font folder in mpl-data . then remove matplotlib fonts cache

rm -rf ~/.cache/matplotlib

restart jupyter notebook, and it works.

I was facing a similar issue in a Cloud Datalab docker image running on a gcloud VM. Executing the following fixed the issue for me:

$ sudo apt install msttcorefonts -qq
$ rm ~/.cache/matplotlib -rf

Here is instructions on how to get to the docker image running on the gcloud VM containing the Datalab instance just in case.

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