Instructor: Dr. Duncan Temple Lang

Dates: July 11, 13, 18, 20

Time: 9am – noon

Location: DataLab classroom (Shields Library room 360)

Description:

The aim of this course is to help participants understand the
relatively small but fundamental computational model underlying the R
language. This will help you reason about code before you write
and run it, and to debug it if it doesn’t do what you want. A sound
understanding of this computational model makes programming in R much
easier and more productive. Basically, we want you to understand how
the R interpreter works.

Prerequisites:

This is not an introductory course. Participants are expected to have an
elementary understanding and prior experience using R, be comfortable
with basic R syntax, and to have it pre-installed and running on their laptops.
This course is appropriate for motivated beginners as well as intermediate
to advanced users who want a better understanding of base R. It is open
to UC Davis faculty, graduate students, postdocs, staff, and undergraduates;
DSI affiliates will receive priority registration. Not sure if this course is
appropriate for you? Contact us (datascience@ucdavis.edu).

Learner objectives:

• What is a REPL
• The Global workspace/environment
• Variables and Assignment (=, <- )
• Basic data types – vectors
• Hierarchy of data types and implicit coercion
• Querying an object: class, typeof, length, dim, names, str
• Subsetting rules
• Categorical data – factors
• Aggregate functions – sum, mean, summary, table,
• Vectorized functions
• Apply functions
• How function calls work
• Lists
• Data Frames
• Subsetting in 2-Dimensions
• Scoping Rules
• Writing Functions
• Debugging