R for Data Science: Part 2

The R for Data Science workshop series is a four-part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying, analyzing, and publishing data in R.

Part 2: Clean and Tidy Data

Students will be introduced to best practices for sanitizing and tidying data. Students will learn what missingness is, and how best to accommodate missing data in their research designs. Students will be able to read in files from disk or a database, clean the data found within them, select specific data from them, and merge them with other datasets.

Knowledge requirements: R for Data Science Part 1 or equivalent

Registration note: To participate in multiple parts of this intensive, please be sure to register for each day separately. Links to the other R intensive workshops can be found below.

• R for Data Science: Part 1
• R for Data Science: Part 3
• R for Data Science: Part 4