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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Southern Regional Science Association in its journal Review of Regional Studies.
Volume (Year): 37 (2007)
Issue (Month): 1 ()
Contact details of provider:
Web page: http://www.srsa.org
Open Source; Software; Spatial;
Find related papers by JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
- C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
- L17 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Open Source Products and Markets
- R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Sergio Rey, 2009.
"Show me the code: spatial analysis and open source,"
Journal of Geographical Systems,
Springer, vol. 11(2), pages 191-207, June.
- Rey, S.J., 2008. "Show me the code: Spatial analysis and open source," MPRA Paper 9260, University Library of Munich, Germany.
- Sergio Rey & Alan Murray & Luc Anselin, 2011. "Visualizing regional income distribution dynamics," Letters in Spatial and Resource Sciences, Springer, vol. 4(1), pages 81-90, March.
- Pedro Amaral & Luc Anselin & Daniel Arribas-Bel, 2013. "Testing for spatial error dependence in probit models," Letters in Spatial and Resource Sciences, Springer, vol. 6(2), pages 91-101, July.
- Alan T. Murray, 2010. "Quantitative Geography," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 143-163.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mark L. Burkey).
If references are entirely missing, you can add them using this form.