Installing an official release#

Matplotlib releases are available as wheel packages for macOS, Windows and Linux on PyPI. Install it using pip:

python -m pip install -U pip
python -m pip install -U matplotlib

If this command results in Matplotlib being compiled from source and there's trouble with the compilation, you can add --prefer-binary to select the newest version of Matplotlib for which there is a precompiled wheel for your OS and Python.


The following backends work out of the box: Agg, ps, pdf, svg

Python is typically shipped with tk bindings which are used by TkAgg.

For support of other GUI frameworks, LaTeX rendering, saving animations and a larger selection of file formats, you can install Optional dependencies.

Third-party distributions#

Various third-parties provide Matplotlib for their environments.

Conda packages#

Matplotlib is available both via the anaconda main channel

conda install matplotlib

as well as via the conda-forge community channel

conda install -c conda-forge matplotlib

Python distributions#

Matplotlib is part of major Python distributions:

Linux package manager#

If you are using the Python version that comes with your Linux distribution, you can install Matplotlib via your package manager, e.g.:

  • Debian / Ubuntu: sudo apt-get install python3-matplotlib

  • Fedora: sudo dnf install python3-matplotlib

  • Red Hat: sudo yum install python3-matplotlib

  • Arch: sudo pacman -S python-matplotlib

Installing a nightly build#

Matplotlib makes nightly development build wheels available on the scipy-wheels-nightly Anaconda Cloud organization. These wheels can be installed with pip by specifying scipy-wheels-nightly as the package index to query:

python -m pip install \
  --upgrade \
  --pre \
  --index-url \
  --extra-index-url \

Installing from source#

If you are interested in contributing to Matplotlib development, running the latest source code, or just like to build everything yourself, it is not difficult to build Matplotlib from source.

First you need to install the Dependencies.

A C compiler is required. Typically, on Linux, you will need gcc, which should be installed using your distribution's package manager; on macOS, you will need xcode; on Windows, you will need Visual Studio 2015 or later.

For those using Visual Studio, make sure "Desktop development with C++" is selected, and that the latest MSVC, "C++ CMake tools for Windows," and a Windows SDK compatible with your version of Windows are selected and installed. They should be selected by default under the "Optional" subheading, but are required to build matplotlib from source.

The easiest way to get the latest development version to start contributing is to go to the git repository and run:

git clone


git clone

If you're developing, it's better to do it in editable mode. The reason why is that pytest's test discovery only works for Matplotlib if installation is done this way. Also, editable mode allows your code changes to be instantly propagated to your library code without reinstalling (though you will have to restart your python process / kernel):

cd matplotlib
python -m pip install -e .

If you're not developing, it can be installed from the source directory with a simple (just replace the last step):

python -m pip install .

To run the tests you will need to install some additional dependencies:

python -m pip install -r requirements/dev/dev-requirements.txt

Then, if you want to update your Matplotlib at any time, just do:

git pull

When you run git pull, if the output shows that only Python files have been updated, you are all set. If C files have changed, you need to run pip install -e . again to compile them.

There is more information on using git in the developer docs.


The following instructions in this section are for very custom installations of Matplotlib. Proceed with caution because these instructions may result in your build producing unexpected behavior and/or causing local testing to fail.

If you would like to build from a tarball, grab the latest tar.gz release file from the PyPI files page.

We provide a mplsetup.cfg file which you can use to customize the build process. For example, which default backend to use, whether some of the optional libraries that Matplotlib ships with are installed, and so on. This file will be particularly useful to those packaging Matplotlib.

If you are building your own Matplotlib wheels (or sdists) on Windows, note that any DLLs that you copy into the source tree will be packaged too.

Installing for development#

See Setting up Matplotlib for development.

Frequently asked questions#

Report a compilation problem#

See Getting help.

Matplotlib compiled fine, but nothing shows up when I use it#

The first thing to try is a clean install and see if that helps. If not, the best way to test your install is by running a script, rather than working interactively from a python shell or an integrated development environment such as IDLE which add additional complexities. Open up a UNIX shell or a DOS command prompt and run, for example:

python -c "from pylab import *; set_loglevel('debug'); plot(); show()"

This will give you additional information about which backends Matplotlib is loading, version information, and more. At this point you might want to make sure you understand Matplotlib's configuration process, governed by the matplotlibrc configuration file which contains instructions within and the concept of the Matplotlib backend.

If you are still having trouble, see Getting help.

How to completely remove Matplotlib#

Occasionally, problems with Matplotlib can be solved with a clean installation of the package. In order to fully remove an installed Matplotlib:

  1. Delete the caches from your Matplotlib configuration directory.

  2. Delete any Matplotlib directories or eggs from your installation directory.

OSX Notes#

Which python for OSX?#

Apple ships OSX with its own Python, in /usr/bin/python, and its own copy of Matplotlib. Unfortunately, the way Apple currently installs its own copies of NumPy, Scipy and Matplotlib means that these packages are difficult to upgrade (see system python packages). For that reason we strongly suggest that you install a fresh version of Python and use that as the basis for installing libraries such as NumPy and Matplotlib. One convenient way to install Matplotlib with other useful Python software is to use the Anaconda Python scientific software collection, which includes Python itself and a wide range of libraries; if you need a library that is not available from the collection, you can install it yourself using standard methods such as pip. See the Anaconda web page for installation support.

Other options for a fresh Python install are the standard installer from, or installing Python using a general OSX package management system such as homebrew or macports. Power users on OSX will likely want one of homebrew or macports on their system to install open source software packages, but it is perfectly possible to use these systems with another source for your Python binary, such as Anaconda or Python.

Installing OSX binary wheels#

If you are using Python from, Homebrew, or Macports, then you can use the standard pip installer to install Matplotlib binaries in the form of wheels.

pip is installed by default with and Homebrew Python, but needs to be manually installed on Macports with

sudo port install py38-pip

Once pip is installed, you can install Matplotlib and all its dependencies with from the command line:

python3 -m pip install matplotlib

You might also want to install IPython or the Jupyter notebook (python3 -m pip install ipython notebook).

Checking your installation#

The new version of Matplotlib should now be on your Python "path". Check this at the command line:

python3 -c 'import matplotlib; print(matplotlib.__version__, matplotlib.__file__)'

You should see something like

3.6.0 /Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/matplotlib/

where 3.6.0 is the Matplotlib version you just installed, and the path following depends on whether you are using Python, Homebrew or Macports. If you see another version, or you get an error like

Traceback (most recent call last):
  File "<string>", line 1, in <module>
ImportError: No module named matplotlib

then check that the Python binary is the one you expected by running

which python3

If you get a result like /usr/bin/python..., then you are getting the Python installed with OSX, which is probably not what you want. Try closing and restarting before running the check again. If that doesn't fix the problem, depending on which Python you wanted to use, consider reinstalling Python, or check your homebrew or macports setup. Remember that the disk image installer only works for Python, and will not get picked up by other Pythons. If all these fail, please let us know.