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Geocomputation and Data Analysis with R

25th April 2019 @ 9:30 am - 26th April 2019 @ 4:30 pm

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**In conjunction with Leeds Digital Festival 2019**

The aim of Geocomputation and Data Analysis with R is to get you up-to-speed with high performance geographic processing, analysis, visualisation and modelling capabilities from the command-line. The course will be delivered in R, a statistical programming language popular in academia, industry and, increasingly, the public sector. It will teach a range of techniques using recent developments in the package sf and the ‘metapackage’ tidyverse, based on the open source book Geocomputation with R (Lovelace, Nowosad, and Meunchow 2019).


Learning Objectives

By the end of the course participants should:

  • Be able to use R and RStudio as a powerful Geographic Information System (GIS)
  • Know how R’s spatial capabilities fit within the landscape of open source GIS software
  • Be confident with using R’s command-line interface (CLI) and scripting capabilities for geographic data processing
  • Understand how to import a range of data sources into R
  • Be able to perform a range of attribute operations such as subsetting and joining
  • Understand how to implement a range of spatial data operations including spatial subsetting and spatial aggregation
  • Have the confidence to output the results of geographic research in the form of static and interactive maps.


Course Tutor

Robin Lovelace is a researcher at the Leeds Institute for Transport Studies (ITS) and the Leeds Institute for Data Analytics (LIDA). Robin has many years of experience of using R for academic research and has taught numerous R courses at all levels. He has developed popular R resources including the recently published book Efficient R Programming (Gillespie and Lovelace 2016), Introduction to Visualising Spatial Data in R and Spatial Microsimulation with R (Lovelace and Dumont 2016). These skills have been applied on a number of projects with real-world applications, including the Propensity to Cycle Tool, a nationally scalable interactive online mapping application, and the stplanr package.


Prior reading/ experience

If you are new to R, ensure you have completed a basic introductory course such as DataCamp’s introduction to R free course or equivalent.

If you’re interested in R for ‘data science’ and installing/updating/choosing R packages, these additional resources are recommended (these optional resources are all freely available online):


Fees and Further Information

The course is open to students, academic staff and external delegates.

Early Bird rate (until 18th March 2019)

£400 – Students

£600 – Academics, charitable and public sector

£800 – Other

Rates 18th March-18th April 2019

£500 – Students

£700 – Academics, charitable and public sector

£900 – Other

The fee includes learning materials, lunch and refreshments during the course, but not overnight accommodation. The course is also available as bespoke or in-company training.


For all enquiries please contact Kylie Norman.



25th April 2019 @ 9:30 am
26th April 2019 @ 4:30 pm
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Leeds Institute for Data Analytics
University of Leeds
Leeds, LS2 9JT United Kingdom
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