• Data wrangling and analysis in R
  • Introduction
  • 1. Install R and Rstudio
    • 1.1. All the Git and GitHub (and RStudio) things
      • 1.1.1. Install Git
      • 1.1.2. Install a Git client
      • 1.1.3. Introduce yourself to Git
      • 1.1.4. GitHub, can you hear me?
      • 1.1.5. Test connection between RStudio and GitHub
      • 1.1.6. GitHub credential caching
      • 1.1.7. When RStudio can't find Git
      • 1.1.8. Take possession of your STAT 545 repo
      • 1.1.9. Troubleshooting
      • 1.1.10. The Shell
    • 1.2. Basic R and RStudio, workspace, working directory, RStudio Project
    • 1.3. Basic care and feeding of data in R
    • 1.4. R objects (beyond data.frames) and indexing
    • 1.5. Test drive R Markdown
    • 1.6. All the graph things
      • 1.6.1. R graphics landscape (slides)
      • 1.6.2. `ggplot2` tutorial
      • 1.6.3. Do's and don'ts of making effective graphs
      • 1.6.4. R Graph Catalog
      • 1.6.5. Using colors in R
      • 1.6.6. Taking control of qualitative colors in `ggplot2`
      • 1.6.7. Secrets of a happy graphing life
      • 1.6.8. Writing figures to file
      • 1.6.9. Multiple plots on a page
    • 1.7. The `dplyr` package for data manipulation
      • 1.7.1. Introduction to dplyr
      • 1.7.2. `dplyr` functions for a single dataset
      • 1.7.3. Cheatsheet
    • 1.8. Writing your own R functions
      • 1.8.1. Part 1
      • 1.8.2. Part 2
      • 1.8.3. Part 3
      • 1.8.4. Function-writing Practicum
    • 1.9. The `plyr` package for split-apply-combine
      • 1.9.1. Data aggregation overview (slides)
      • 1.9.2. Using `plyr` with data.frames
    • 1.10. Be the boss of your factors
    • 1.11. Writing and reading files
      • 1.11.1. Indicative code from hands on activities
      • 1.11.2. 2013 lesson
    • 1.12. Why and how to tidy data
    • 1.13. Regular expressions
    • 1.14. All the automation things
      • 1.14.1. slides
      • 1.14.2. Special considerations for Windows
      • 1.14.3. Test drive `Make`
      • 1.14.4. Hands-on activity
    • 1.15. All the package things
      • 1.15.1. slides
      • 1.15.2. System preparation for package development
      • 1.15.3. Hands-on activity, part 1
      • 1.15.4. Hands-on activity, part 2
    • 1.16. All the Shiny things
      • 1.16.1. slides
      • 1.16.2. Getting your system set up for Shiny
      • 1.16.3. Hands-on activity-build a shiny app
      • 1.16.4. Shiny and other interactive plotting links
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Data wrangling and analysis in R

Stat 545 shiny tutorial using Gapminder data

Julia Gustavsen
2014-11-17

Link section for further help and ideas

Tutorials:

  • R studio Shiny tutorial
  • Shiny tutorial by Hadley Wickam (pdf)
  • Make a bilingual Shiny app
  • Baby Names Shiny Tutorial from Strata in NY (dropbox folder)
  • Shiny Cheatsheet by RStudio

Demos:

  • R Graph Catalog
  • Shiny Dashboard example using some toy data
  • World Bank population data and using the "animint" package for animation
  • dygraphs (pretty time-series graphs)
  • Gallery of Shiny Apps

Interactive plots (not neccessarily Shiny):

  • Karl Broman: "Why aren't all of our graphs interactive"(using json d3.js) (presentation)
  • New York Times: Corporate Taxes in the US