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A powerful, format-agnostic, community-driven Python package for analysing and visualising Earth science data.

Iris implements a data model based on the CF conventions giving you a powerful, format-agnostic interface for working with your data. It excels when working with multi-dimensional Earth Science data, where tabular representations become unwieldy and inefficient.

For more information see Why Iris.

Information on Iris, how to install and a gallery of examples that create plots.

Learn how to use Iris, including loading, navigating, saving, plotting and more.

Information on how you can contribute to Iris as a developer.

Browse full Iris functionality by module.

Find out what has recently changed in Iris.

Raise the profile of issues by voting on them.

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We, the Iris developers have adopted GitHub Discussions to capture any discussions or support questions related to Iris.

See also StackOverflow for “How Do I? that may be useful but we do not actively monitor this.

The legacy support resources:

  • Users Google Group

  • Developers Google Group

  • Legacy Documentation (Iris 2.4 or earlier). This is an archive of zip files of past documentation. You can download, unzip and view the documentation locally (index.html). There may be some incorrect rendering and older javascvript (.js) files may show a warning when uncompressing, in which case we suggest you use a different unzip tool.