GRSEB9S / notebooks-1

jupyter/ipython notebooks demonstrating PySAL functionality

Examples

Below are illustrative use cases for PySAL. You may also be interested in the tutorials and short courses on PySAL.

Reading Geospatial Data

• Shapefiles: read and write shapefiles, dbf files.

Visualizing Geospatial Data

Viz interfaces:

• PySAL viz
• PySAL + cartopy
• PySAL + geopandas
• PySAL + folium

Viz task views:

• Choropleth Mappping
• LISA Cluster Maps

Spatial Weights

• Spatial Weights: understand, create and manipulate spatial weights objects.

Global Spatial Autocorrelation Analysis

• Global Autococorrelation: overview of Exploratory Spatial Data Analysis (ESDA) techniques.

Local Spatial Autocorrelation Analysis

• Local Autocorrelation

Space-Time Analysis

• Spatial Dynamics

Python Scientific Computing Stack (SciPy)

• Stack: brief introduction to the main libraries for scientific computing in Python (ipython, numpy, scipy, pandas, matplotlib).