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R&Py Spatial Analysis Workshop, 5 September 2019: European Colloquium on Theoretical and Quantitative Geography
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README.md

ectqg19-workshop

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R&Py Spatial Analysis Workshop, 5 September 2019: European Colloquium on Theoretical and Quantitative Geography

Summary text

A spatial analysis workshop will be offered on Thursday 5 September, 09:00-16:00 in connection with the European Colloquium on Theoretical and Quantitative Geography 2019 in Mondorf (time and exact location to be confirmed). This workshop is intended to provide up to date overviews of open source software for spatial analysis in Python and R. The instructors, Daniel Arribas Bel, Roger Bivand and colleagues, hope to explore with participants shared features of software tools and data representation in both language environments. We will be canvassing interested participants about substantive topics to be covered, and whether participants would benefit most from working using their own laptops directly, or rather from containerising the workshop software environment to avoid setup issues. We intend to use Python 3, Pysal 2 and associated packages, and in R the CRAN sf and stars packages and packages using their data representations for spatial analysis. The workshop materials as they appear are currently hosted at (https://github.com/rsbivand/ectqg19-workshop).

Aims (morning)

Core coverage

  • Provide an up to date overview of spatial data representation in Python and R

  • Provide an introduction to software for static and interactive visualization, especially maps in Python and R

Aims (afternoon)

  • Provide an overview of tools for exploratory spatial data analysis in Python and R

  • Provide an overview of tools for spatial regression in Python and R

  • Provide an overview of tools interoperability between Python and R, including the R reticulate package for running Python from R

Target audience

Conference participants with some coding/scripting experience in R and/or Python or other relevant environments, using applied methods in teaching and/or research.

Structure

Working environment R, Python, RStudio(/Jupyter?), R Markdown files(/other notebooks?); participants working using own laptops, need WiFi and power supplies.

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