This 2-part workshop series for intermediate R programmers focuses on
how to load and prepare data for analysis. We’ll explore how to screen a
data set for potential problems with its structure and data types, as
well as how to correct these issues. For example, it is increasingly
popular to to use datasets loaded from text files or scraped from the
web, but these data often have formatting features that need additional
processing before they can be used. Thus, we’ll take a deep dive into
R’s “stringr” package for text processing. Dates and times are another
kind of data that can be difficult to work with, and we’ll cover the
basics of using the “lubridate” package for processing temporal data.
You’ll also learn how to reshape data with structural problems and how
to combine linked data sets.
This workshop is NOT an introduction to R and
is intended for motivated intermediate to advanced learners from all
domains at UC Davis who want to hone their R skills. Please make sure
you meet the prerequisites before registering as we will be unable to
answer introductory R questions during this session. (Want to brush up
on R? Check out our R Basics 4-part introductory series.)
Prerequisites: Participants must have taken DataLab’s “R Basics” workshop series
and/or have prior experience using R, be comfortable with basic R
syntax, and have the latest versions of R and RStudio pre-installed and
running on their laptops.
The copyright on
this video is owned by the Regents of the University of California and is
licensed for reuse under the Creative Commons Attribution 4.0 International (CC
BY 4.0) License.
