This 2-part workshop series for
intermediate R programmers focuses on how to load and prepare data for
analysis. First, you'll learn how to screen a data set for potential
problems in its structure and data types, as well as how to correct
these. Data sets loaded from text files or scraped from the web often
have features in text format that need additional processing before they
can be used, so the series will include a deep dive into R's "stringr”
package for text processing. Dates and times are another kind of data
that can be difficult to handle, so the series will explore the basics
of using the "lubridate" package for processing temporal data. You'll
also learn how to use loops to automate repetitive tasks such as loading
and combining similar data sets from many different files.
Prerequisites: These workshops are not an
introduction to R. Participants are expected to have prior experience
using R, be comfortable with basic R syntax, and to have it
pre-installed and running on their laptops. This series is appropriate
for motivated intermediate to advanced users who want a better
understanding of base R. While not required, we recommend learners also
attend the prior 2-part "Intermediate R: Thinking in R" workshop series.
Software: Latest version of the R programming language.
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.
