Leeds R User Group

This is a test repo for Leeds R Users group.

Homework

Part 1: Background reading and exploring.

As a bit of context please have a browse around the Propensity to Cycle Tool GitHub team, which is a space for 6+ academics from different universities to develop this product that will go national in July:

• Propensity to Cycle Tool GitHub team: https://github.com/npct/

• Academic paper on it for context: http://arxiv.org/abs/1509.04425

Hopefully that this shows that GitHub is a useful way to organise large code-heavy projects.

Now please also have a look at some R User Groups who organise their stuff via GitHub:

• Article on it: http://www.r-bloggers.com/r-user-groups-on-github/

• List of GitHub R User Group projects: https://www.google.co.uk/search?q=site:github.com+R+user+group

Part 2: Contribute to the Leeds R Users Group

The involves 3 things:

1. Sign up to GitHub, as described here: https://github.com/join

2. Fork the repo onto your account as described here: https://help.github.com/articles/fork-a-repo/ You can find a more general intro to command line Git here: http://software-carpentry.org/lessons/

3. Make some changes, push them and make a pull request to https://github.com/Leeds-Rug/test-repo : https://help.github.com/articles/using-pull-requests/

Specifically, try to add a line of working R code to the script here and add your name to the comment: https://github.com/Leeds-Rug/test-repo/blob/master/test.R

The aim: to modify the test.R script with a Pull Request.

If you make a pull request, you'll be added to this 'team'. From there you can create new team repos like this one and push directly to them (although Pull Requests are usually recommended).

Part 3: example R code

library(tmap)
b <- bb("Leeds")
tm_tiles <- read_osm(b)
tm_shape(tm_tiles) +
  tm_raster()

Part 4: Useful resources

• @visser_speeding_2015 provides an excellent overview of making your R code faster
• @Wickham_2015 demonstrates how to build R packages, easily

References

Visser, Marco D., Sean M. McMahon, Cory Merow, Philip M. Dixon, Sydne Record, and Eelke Jongejans. 2015. “Speeding Up Ecological and Evolutionary Computations in R; Essentials of High Performance Computing for Biologists.” Edited by Francis Ouellette. PLOS Computational Biology 11 (3): e1004140. doi:10.1371/journal.pcbi.1004140.

Wickham, Hadley. 2015. R Packages. O’Reilly Media, Inc.