Fundamental Interactions

R as a Calculator

Reading

R4DS 2.1: Coding Basics

Among the simplest possible commands you could execute would be using R as a very over-powered pocket calculator. In the examples shown below, we evaluate a few simple arithmetic expressions involving two integer values.

## Add 2 and 2
2 + 2
[1] 4
## Subtract 6 from 14
14 - 6
[1] 8
## Multiply 3 and 4
3 * 4
[1] 12
## Divide 225 by 15
225 / 15
[1] 15
Practice
  1. Calculate the number of whole days left in the month.
  2. Calculate the number of weeks left in the month.
    • Account for partial weeks with a decimal-valued answer.

At time-of-writing, it’s 18 July. Since July has 31 days, we get 13 days remaining in the month.

31 - 18
[1] 13

To find the number of remaining weeks, I’ll just divide the answer from above by 7.

13 / 7
[1] 1.857143

Comments

Reading

R4DS 2.2: Comments

The comment character in R is #. Each commented line must be preceded by a # symbol. There are no block comments in R. Comments are not evaluated when you run your code

Run the following R code to generate two integer vectors and print the results.

In the following code, the expression 1:10 is “commented out”, so R doesn’t evaluate that line. So, running the code will only print the second vector.

Assignment

Reading

R4DS 2.3: Object Names

Advanced Reading

Advanced R 2.2: Binding Basics

To do anything useful, we need to create objects that hold data. We ‘assign’ values to objects via the ‘assignment’ operator, <-.

The following code assigns the values 7, 2.5, and "foo" to the objects x, y, and z, respectively.

x <- 7
y <- 2.5
z <- "foo"

Notice the lack of printed output. These three commands create three new objects in your environment (x, y, z) that store the assigned data values (7, 2.5, "foo"). However, we haven’t yet asked R to do anything with those stored values, so we don’t see any printed output.

To view the contents of an object, we can evaluate the object’s name without assignment.

Run the following code to print the values saved as x and y.

We can also create new objects by assigning them the values of existing objects.

The following code creates a new object, w, that takes the value of the existing object z. When we print the value of w, you can see that it has the same value as z.

w <- z
w
[1] "foo"
z
[1] "foo"

When we create w above, we are not replacing z with w: we’re making a copy of z and calling that copy w. So, both w and z are still available. In almost all cases, R will copy objects during assignment. This behavior is good to keep in mind when you’re working with larger datasets: you can quickly flood your memory with unnecessary copies of your data, if you’re not careful.

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