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The Matplotlib FAQ

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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 cd into a directory containing a minimal example in a file. Something like for example:

from pylab import *

and run it with:

python --verbose-helpful

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.

The process for removing an installation of matplotlib depends on how matplotlib was originally installed on your system. Follow the steps below that goes with your original installation method to cleanly remove matplotlib from your system.

Easy Install

  1. Delete the caches from your .matplotlib configuration directory.

  2. Run:

    easy_install -m matplotlib
  3. Delete any .egg files or directories from your installation directory.

Windows installer

  1. Delete the caches from your .matplotlib configuration directory.
  2. Use Start ‣ Control Panel to start the Add and Remove Software utility.

Source install


python clean

does not properly clean the build directory, and does nothing to the install directory. To cleanly rebuild:

  1. Delete the caches from your .matplotlib configuration directory.
  2. Delete the build directory in the source tree.
  3. Delete any matplotlib directories or eggs from your installation directory.

How to Install

Source install from git

Clone the main source using one of:

git clone


git clone git://

and build and install as usual with:

> cd matplotlib
> python install


If you are on debian/ubuntu, you can get all the dependencies required to build matplotlib with:

sudo apt-get build-dep python-matplotlib

If you are on Fedora/RedHat, you can get all the dependencies required to build matplotlib by first installing yum-builddep and then running:

su -c "yum-builddep python-matplotlib"

This does not build matplotlib, but it does get all of the build dependencies, which will make building from source easier.

If you want to be able to follow the development branch as it changes just replace the last step with (make sure you have setuptools installed):

> python develop

This creates links in the right places and installs the command line script to the appropriate places.


Mac OSX users please see the Building on OSX guide.

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 the python develop command again to compile them.

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

Linux Notes

Because most Linux distributions use some sort of package manager, we do not provide a pre-built binary for the Linux platform. Instead, we recommend that you use the “Add Software” method for your system to install matplotlib. This will guarantee that everything that is needed for matplotlib will be installed as well.

If, for some reason, you can not use the package manager, Linux usually comes with at least a basic build system. Follow the instructions found above for how to build and install matplotlib.

OS-X Notes

Which python for OS X?

Apple ships with its own python, and many users have had trouble with it. There are several alternative versions of python that can be used. If it is feasible, we recommend that you use the enthought python distribution EPD for OS X (which comes with matplotlib and much more). Also available is MacPython or the official OS X version from


Before installing any of the binary packages, be sure that all of the packages were compiled for the same version of python. Often, the download site for NumPy and matplotlib will display a supposed ‘current’ version of the package, but you may need to choose a different package from the full list that was built for your combination of python and OSX.

Installing OSX binaries

If you want to install matplotlib from one of the binary installers we build, you have two choices: a mpkg installer, which is a typical, or a binary OSX egg, which you can install via setuptools’ easy_install.

The mkpg installer will have a “zip” extension, and will have a name like The name of the installer depends on which versions of python, matplotlib, and OSX it was built for. You need to unzip this file using either the “unzip” command, or simply double clicking on the it. Then when you double-click on the resulting mpkd, which will have a name like matplotlib-1.2.0-py2.7-macosx10.5.mpkg, it will run the, prompt you for a password if you need system-wide installation privileges, and install to a directory like /Library/Python/2.7/site-packages/ (exact path depends on your python version). This directory may not be in your python ‘path’ variable, so you should test your installation with:

> python -c 'import matplotlib; print matplotlib.__version__, matplotlib.__file__'

If you get an error like:

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

then you will need to set your PYTHONPATH, eg:

export PYTHONPATH=/Library/Python/2.7/site-packages:$PYTHONPATH

See also ref:environment-variables.

Building and installing from source on OSX with EPD

If you have the EPD installed (Which python for OS X?), it might turn out to be rather tricky to install a new version of matplotlib from source on the Mac OS 10.5 . Here’s a procedure that seems to work, at least sometimes:

  1. Remove the ~/.matplotlib folder (“rm -rf ~/.matplotlib”).

1. Edit the file (make a backup before you start, just in case): /Library/Frameworks/Python.framework/Versions/Current/lib/python2.5/config/Makefile, removing all occurrences of the string -arch ppc, changing the line MACOSX_DEPLOYMENT_TARGET=10.3 to MACOSX_DEPLOYMENT_TARGET=10.5 and changing the occurrences of MacOSX10.4u.sdk into MacOSX10.5.sdk

2. In /Library/Frameworks/Python.framework/Versions/Current/lib/pythonX.Y/site-packages/easy-install.pth, (where X.Y is the version of Python you are building against) Comment out the line containing the name of the directory in which the previous version of MPL was installed (Looks something like ./matplotlib-

3. Save the following as a shell script, for example ./

git clone git://
cd matplotlib
if [ $branch = "release" ]
    echo getting the maintenance branch
    git checkout -b $VERSION origin/$VERSION
export CFLAGS="-Os -arch i386"
export LDFLAGS="-Os -arch i386"
export PKG_CONFIG_PATH="/usr/x11/lib/pkgconfig"
export ARCHFLAGS="-arch i386"
python build
# use --prefix if you don't want it installed in the default location:
python install #--prefix=$PREFIX
cd ..

Run this script (for example sh ./ in the directory in which you want the source code to be placed, or simply type the commands in the terminal command line. This script sets some local variable (CFLAGS, LDFLAGS, PKG_CONFIG_PATH, ARCHFLAGS), removes previous installations, checks out the source from github, builds and installs it. The backend should to be set to MacOSX.

Windows Notes

Binary installers for Windows

If you have already installed python, you can use one of the matplotlib binary installers for windows – you can get these from the download site. Choose the files that match your version of python (eg py2.7 if you installed Python 2.7) which have the exe extension. If you haven’t already installed python, you can get the official version from the python web site.

There are also two packaged distributions of python that come preloaded with matplotlib and many other tools like ipython, numpy, scipy, vtk and user interface toolkits. These packages are quite large because they come with so much, but you get everything with a single click installer.