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PySAL is an open source library of routines for exploratory spatial data
analysis using Python. It is a community project sponsored by the GeoDa
Center for Geospatial Analysis and Computation at Arizona State University.
PySAL originated with code contributions by Luc Anselin and Serge Rey.
Since then many people have contributed to PySAL, in code development,
suggestions, and financial support. Below is a partial list. If you've
been left off, please email the "PySAL Developers List" <pysal-dev@googlegroups.com>
Pedro Amaral
Luc Anselin
Jotham Apaloo
Daniel Arribas-Bel
Roger Bivand
David C. Folch
Forest Gregg
Myunghwa Hwang
Wei Kang
Marynia Kolak
Julia Koschinsky
Jason Laura
Xun Li
Nicholas Malizia
Mark McCann
Taylor Oshan
Serge Rey
Charles R. Schmidt
Skipper Seabold
Alessandra Sozzi
Philip Stephens
Bohumil Svoma
Ran Wei
Andrew Winslow
Levi Wolf
Jing Yao
Xinyue Ye
jo-tham
sebastic
andy-esch
calebrob6
fnorf
mylons-tcc
dnadai2
MridulS
thequackdaddy
Funding from the following sources has supported PySAL development:
Google Summer of Code 2017
Google Summer of Code 2016
National Institutes of Health Award 7R01CA1266858-06, Geospatial Factors and Impacts II.
National Science Foundation New Approaches for Spatial Distribution Dynamics
National Science Foundation CyberGIS Software Integration for Sustained Geospatial Innovation
National Institute of Justice Flexible Geospatial Visual Analytics and
Simulation Technologies to Enhance Criminal Justice Decision Support Systems
National Institutes of Health Geospatial Factors and Impacts: Measurement and
Use (R01CA126858-02)
National Science Foundation An Exploratory Space-Time Data Analysis Toolkit for
Spatial Social Science Research (0433132)
National Science Foundation Hedonic Models of Location Decisions with
Applications to Geospatial Microdata (0852261)
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