The 4th post in the Scientist’s Guide to R series introduces data transformation techniques useful for wrangling/tidying/cleaning data. Specifically, we will be learning how to use the 6 core functions (and a few others) from the popular dplyr package, perform similar operations in base R, and chain operations with the pipe operator (%>%) to streamline the process. Click here for the full post.
data manipulation with dplyr
ASGR: 2.1 - Data Transformation - Part 1
data manipulation with dplyr
ASGR: 2.1 - Data Transformation - Part 1
Craig Hutton
Postdoctoral Research Fellow, University of Victoria
I use a combination of methods from psychology, neuroscience, and statistics to examine how brain plasticity, memory, and mood are affected by mild traumatic injuries and neurodegenerative diseases.