Upcoming Events (please note that meetings have been a bit erratic because of working from home and other disruption due to COVID-19)

  • 28 May 2021: Naomi Waterlow will present on web scraping
  • 25 June 2021: Antonio Gasparrin will present on reproducible analysis
  • July 2021: Joseph Timothy will present on RStudio Cloud

Past Events

  • 19 April 2021: Andrei Morgan presented on analysing sensitive data via DataSHIELD – his slides can be downloaded here.
  • 07 May 2020: Calum Davey presented on how to produce a reproducible PhD using Bookdown in R, materials here
  • 27 March 2020: Amy MacDougall, Carl Pearson, Julia Shen, Lauren Bell, Martina Cusinato, and Calum Davey presented their plots. You can find their materials here.
  • 31 January 2020: Michelle Clements talked about using Shiny — her materials here
  • 12 December 2019: Chris Jarvis presented on how to use the tools in the Tidyverse — his materials are here
  • 29 November 2019: Chathika Weerasuriya explained how to use Git to keep track of changes that you make to your projects — materials here.
  • October 31 2019: Sam Clifford led a seminar creating the best and the worst plots in gglot2. His materials are here
  • 27 September 2019: Kamaryn Tanner talked about machine learning in R using Super Learner — her materials are here
  • In August we met and made plans for the year.
  • 26 July 2019: Sam Clifford talked about ggplot2 — one of the most popular packages in R, but also one of the least accessible without some introduction. His materials are here
  • 28 June 2019: Jenny Thompson and Amy Mulick explained how to do parallel processing in R using two alternative methods, based on the package parallel (material available here) and foreach/doParallel (material available here), respectively. Carl Pearson provided some additional info on parallelization within the LSHTM HPC system (here) and parallelization through data table (here).
  • 30 May 2019: Rosalind Eggo and Hunter Blanks introduced us to the wonderful world of Git — materials available here, and Hunter’s nice hand-drawn diagrams here.
  • 26 April 2019: Carl Pearson presented on data.table and make files. His presentation slides are here, and the .R files created during the session here.
  • 4 April 2019: Hannah Brindle and Hope Simpson presented on using spatial data in R. The materials from Hope’s presentation are here (Hannah’s are awaiting approval from collaborators).
  • 01 March 2019:Leonard Roth presented on using the package Rcpp as an alternative to using loops in R, which are known to be slow. Moving-on from using loops is a difficult but necessary step for those transitioning from Stata to R. The extensive materials from the session can be found here: Rcpp
  • 31 January 2019: Missing Data: Matteo Quartangno presented on missing data in R — NA, NULL, NaN; what do they mean, and how do we deal with them? You can find the presentation slides and .R scripts here: NA NaN NULL R script.R Of NA, NaN, NULL & friends
  • 29 November 2018: High Performance Cluster: Peninah Murage talked about how to use the high performance cluster available at the school. Her slides can be downloaded from here.
  • 25 October 2018: Regression in R:Antonio Gasparrini presented on regression in R, getting us thinking again about the bread-and-butter of statistical research with R. The R code used during the seminar can be downloaded from here.
  • 27 September 2018: Shiny Apps in R: Liz Fearon and Nick Magill shared their experiences of producing Shiny Apps in R. Here you can download the materias (slides and R code) used for the talk. 
  • 20 July 2018: Reproducible Research in R: Claudio Fronterre gave a presentation on Reproducible Research in R, followed by discussion. Comprehensive notes and a tutorial here.
  • 28 June 2018: The Tidyverse: Chris Jarvis gave a presentation on the Tidyverse, covering dplyr and piping. Everything that he presented is available here.

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