We now transition to Part III of our textbook: Transform. In this part
of our textbook you are learning specific tools to transform the observations,
variables, and values of your data.
In R the concept of a vector has a special importance. At this stage,
you may think of a vector as a column in a data frame, an object that contains
the values of a variable.
When we work with large data frames with many observations, variables, and values,
we need tools for manipulating not just values, but collections of values. A
vector is fundamentally a collection of values.
The two chapters that you are covering this week deal with the two simplest types
of vectors, logical vectors (chapter 12) and numeric vectors (chapter 13).
These chapters are going to expose you to many tools, and you will not immediately
remember all of them, but when you practice them here you are more likely to
remember that they exist when the need arises.
With logical vectors, pay special attention to missing values, NA, and
how you manage them. With numeric variables, pay special attention to the
large selection of summary functions that you have available to you.
Assessment deadlines will be 11:59pm each Saturday.
All assessments are submitted to the Homework Folder inside your assigned
Google Drive folder.
There are no make-ups for missed assessments. Contact me before a deadline
if you have an issue meeting the deadline and we will find a mutually
agreeable solution.
Homework
Homework 8 (due Saturday, March 1)
The instructions for your homework are contained in the R script
file
homework_08.R.