Topic list
- Install R and Rstudio
- All the Git and GitHub (and RStudio) things
- Basic R and RStudio, workspace, working directory, RStudio Project
- Basic care and feeding of data in R
- R objects (beyond data.frames) and indexing
- Test drive R Markdown
- All the graph things
- R graphics landscape slides
ggplot2tutorial, heavy on code and examples- Do’s and don’ts of making effective graphs
- R Graph Catalog, a visual, clickable index of 100+ figures +
ggplot2code to make them - Using colors in R
- Taking control of qualitative colors in
ggplot2 - Secrets of a happy graphing life
- Writing figures to file
- Multiple plots on a page
- The
dplyrpackage for data manipulation- Introduction to dplyr
dplyrfunctions for a single dataset- Overview of split-apply-combine: slides on speakerdeck
- Split-apply-combine with
dplyr::do() - Example: a wrapper around
lmto use withdplyr::do() - Cheatsheet for
dplyrjoin functions - Legacy material on split-apply-combine with
plyr
- Writing your own R functions
- Part 1: get something that works, check arguments
- Part 2: generalize, set default argument values
- Part 3:
NAhandling,..., unit test - Function-writing Practicum: fit a linear model and return estimated coefficients
- Be the boss of your factors
- Writing and reading files
- Why and how to tidy data
- Strings and Regular Expressions
- (2014) Intro to regular expressions and more about character data
- (2015) Regular expressions and character data in R: applying regex in R
- All the package things
- All the automation things
- slides
- Special considerations for Windows
- Test drive
Makefrom a shell and RStudio - Hands-on activity
- Example pipelines
- Get data from the web
- Slides
- Lesson 1: Use API-wrapping packages
- Lesson 2: DIY web data
- All the Shiny things
Homework
- Homework 01 Edit
README.md - Homework 02 Explore Gapminder and use R markdown
- Homework 03 Manipulate, summarize, visualize Gapminder with
dplyrandggplot2 - Homework 04 Use split-apply-combine with your functions within data.frames
- Homework 05 Prove you are in control of factors and figures. Clean up your repo.
- Homework 06 did not exist; it’s “clean up your repo” and was folded into homework 05
- Homework 07 Clean and wrangle the
candysurvey - Homework 08 Write an R package
- Homework 09 Automate a data analysis pipeline
- Homework 10 Get data from the web
- Homework 11 Building Shiny apps
Short random things
- Draw the rest of the owl, a pep talk for building off simple examples
- Using
dplyr+purrr+tidyrto analyze data about GitHub repos via theghpackage - Using
dplyr+purrr+tidyr+xml2to tame the annoying XML from Google Sheets - Make browsing your GitHub repos more rewarding
- Cheatsheet for
dplyrjoin functions - Workflow for sending email with R and
gmailr - Store an API key as an environment variable
- Lesson I contributed to Data Carpentry on tidying data