Data Analysis and Visualization with R

• When: 14-15 August 2017
• Where: CRTP classroom in Hock Plaza, 2424 Erwin Road, Durham, NC.
• Who: Members and associate members of Duke/UNC Center for AIDS Research (CFAR)
• What: Data cleaning, analysis and visualziaiotn in R with tidyr, dplyr and ggplot2
• How much: FREE

The course will be limited to a maximum of 30 participants on a first-come-first served basis. Registration indicates a commitment to attend BOTH days of the workshop. No programming experience is required. You will be required to bring your own laptop to the workshop.

Click here to register

Please contact Kelly Plonk <kell.plonk@duke.edu> with questions.

Update: The course is now full. If you register now, you will be put on a wait list.

Before the course starts

• Install R
• Install RStudio Desktop

Check that you can launch RStudio successfully.

Schedule

Course Coverage

• Day 1 AM: Introduction to R, RStuido and the data.frame
  • Using R and RStudio
  • Overview of the exploratory data analysis pipeline
  • Types, collections and variable assignments
  • Getting data into a data.frame
  • Understanding the data.frame
  • Exporting a data.frame
  • Installing packages from CRAN and BioConductor
• Day 1 PM: Visualizing data with ggplot2
  • The Grammar of Graphics
  • Example data set 1
  • Example data set 2
  • Raster plots
• Day 2 AM: Analyzing data with dplyr
  • Chaining data transformations with pipe (%>%)
  • Filtering rows with filter
  • Selecting columns with select
  • Sorting data with arrange
  • Creating new columns with mutate and transmute
  • Split-apply-combine with group_by and summarize
• Day 2 PM: Preparing data for analysis with tidyr
  • Splitting columns with separate
  • From columns to key-value pairs with gather
  • From key-value pairs to columns with spread
  • When variables are stored in both rows and columns (advanced)
  • Working with missing data
  • Combining data with join (part of dplyr)

Exercise sheets

Exercises

• Exercises: Session 1
• Exercises: Session 2
• Exercises: Session 3
• Exercises: Session 4