esda

statistics and classes for exploratory spatial data analysis

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Exploratory Spatial Data Analysis in PySAL

unittests codecov DOI

Methods for testing for global and local autocorrelation in areal unit data.

Documentation

Installation

Install esda by running:

$ pip install esda

Requirements

  • libpysal

Optional dependencies

  • numba, version 0.50.1 or greater, is used to accelerate computational geometry and permutation-based statistical inference. Unfortunately, versions before 0.50.1 may cause some local statistical functions to break, so please ensure you have numba>=0.50.1 installed.

Contribute

PySAL-esda is under active development and contributors are welcome.

If you have any suggestion, feature request, or bug report, please open a new issue on GitHub. To submit patches, please follow the PySAL development guidelines and open a pull request. Once your changes get merged, you’ll automatically be added to the Contributors List.

Support

If you are having issues, please talk to us in the gitter room.

License

The project is licensed under the BSD 3-Clause license.

Funding

National Science Foundation Award #1421935: New Approaches to Spatial Distribution Dynamics

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