Data wrangling, exploration, and analysis with R

UBC STAT 545A and 547M

Learn how to

  • explore, groom, visualize, and analyze data
  • make all of that reproducible, reusable, and shareable
  • using R

Selected topics

  • Introduction to R and the RStudio IDE: scripts, the workspace, RStudio Projects, daily workflow
  • Generate reports from R scripts and R Markdown
  • Coding style, file and project organization
  • Data frames or “tibbles” are the core data structure for data analysis: care for them with the tidyverse
  • Data visualization with ggplot2
  • How to write functions and work with R in a functional style
  • Version control with Git; collaboration via GitHub
  • Be the boss of non-numeric data, esp. character and factor
  • Interactive pages, apps, and graphics with Shiny
  • Get data off the web and expose data, code, results on the web
  • Distribute data and code via an R package
  • Automate an analytical pipeline, e.g. via Make

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