PySAL: A Python Library of Spatial Analytical Methods
AbstractPySAL is an open source library for spatial analysis written in the object-oriented language Python. It is built upon shared functionality in two exploratory spatial data analysis packages--GeoDA and STARS--and is intended to leverage the shared development of these components. This paper presents an overview of the motivation behind and the design of PySAL, as well as suggestions for how the library can be used with other software projects. Empirical illustrations of several key components in a variety of spatial analytical problems are given, and plans for future development of PySAL are discussed.
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Bibliographic InfoArticle provided by Southern Regional Science Association in its journal Review of Regional Studies.
Volume (Year): 37 (2007)
Issue (Month): 1 ()
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Open Source; Software; Spatial;
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- repec:asg:wpaper:1051 is not listed on IDEAS
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