Skip to content
Materials for PySAL Workshop at NARSC 2013 Atlanta
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
data
images
00_notebook_intro.ipynb
01_spatial_data_processing.ipynb
02_plotting.ipynb
03_choropleth_mapping.ipynb
04_spatial_weights.ipynb
05_global.ipynb
06_global_south.ipynb
07_local_south.ipynb
08_gol.ipynb
09_spatial_dynamics.ipynb
99_shapefiles_json.ipynb
README.md

README.md

Spatial Data Analysis with PySAL

Sergio Rey

November 13, 2013

NARSC 2013, Atlanta, Ga

Workshop Description

A unique feature of this tutorial is the use of Python based software tools for spatial data analysis. Python is an object oriented scripting language that is gaining rapid adoption in the computational sciences. To facilitate this adoption within the GIScience community, Rey and Anselin have collaborated on the creation of PySAL: Python Library for Spatial Analysis. Since its initial release in July 2010, PySAL has been downloaded over 25,000 times. This three-part tutorial will introduce participants to version 1.6 of PySAL. The first component provides hands-on experience in the use of PySAL, installation and related packages. Part 2 deals with the use of PySAL for spatial data processing and visualization. Part three covers the exploratory spatial data analysis components of PySAL.

Prerequisites

Example data sets will be made available

Outline

  • Part 1: Introduction and Setup (30 minutes)
    • PySAL Overview
    • Software Configuration
    • IPython Notebook
  • Part 2: PySAL for Spatial Data Processing (60 minutes)
    • Spatial Data Processing with PySAL
    • Spatial Weights
    • Visualization
  • Break (15 Minutes)
  • Part 3: PySAL for Exploratory Spatial Data Analysis (75 Minutes)
    • Global Spatial Autocorrelation Analysis
    • Local Spatial Autocorrelation Analysis
You can’t perform that action at this time.