Installation Guide


In general, MetPy tries to support minor versions of dependencies released within the last two years. For Python itself, that means supporting the last two minor releases.

  • matplotlib >= 2.1.0

  • numpy >= 1.16.0

  • scipy >= 1.0.0

  • pint >= 0.10.1

  • pandas >= 0.22.0

  • xarray >= 0.13.0

  • traitlets >= 4.3.0

  • pooch >= 0.1


The easiest way to install MetPy is through pip:

pip install metpy

If you are a user of the Conda package manager, there are also up-to-date packages for MetPy (as well as its dependencies) available from the conda-forge channel:

conda install -c conda-forge metpy

The source code can also be grabbed from GitHub. From the base of the source directory, run:

pip install .

This will build and install MetPy into your current Python installation.


The MetPy source comes with a set of example scripts in the examples directory. These are also available as notebooks in the gallery in the Examples. Further examples of MetPy usage are available in the Unidata Python Gallery.