Lesson 4a - Vectors

Collections are items that contain other items. In R, vectors, matrices, lists, and data frames are four types of collections. In this lesson, we’ll cover vectors.

Lesson Objectives

• Use vectors to group values of the same data type
• Access values in vectors

What’s a Vector?

Vectors are one of the four types of collections we will cover. They contain elements of the same type, so you can have a vector of logicals, a vector of strings, and so on.

Creating a Vector

The format to create a vector is the following:

myVector <- c(item1, item2, item3, ...)

Don’t forget that all items in a vector must be of the same type.

myVector <- c(1, 2.0, 6, -4)
myVector2 <- c(1, 4.2, 3.2, "hello")

myVector
myVector2

[1]  1  2  6 -4
[1] "1"     "4.2"   "3.2"   "hello"

In the example above, you’ll notice that in myVector2, all the numeric data values are turned into strings. Rather than throwing an error, R will do what it think is most appropriate and turn all the values into one data type.

Creating a Vector of Consecutive Numbers

You can use the : operator to create a vector of consecutive numbers.

x <- 1:10
x

[1] 1 2 3 4 5 6 7 8 9 10

Adding an Element to a Vector

The c() function can also add elements to an existing vector.

myVector <- c(1, 2.0, 6, -4)

myVector <- c(myVector, -6)
myVector

[1]  1  2  6 -4  -6

Concatenating Vectors

To concatenate vectors, you can use the same c() function.

myVector <- c(1, 2.0, 6, -4)
myVector2 <- c(5, 6, 7, 8)

myVector3 <- c(myVector, myVector2)
myVector3

[1]  1  2  6 -4  5  6  7  8

Storing Values by Name

You can also store individual values in a vector by name (usually referred to as a key), which will be useful when indexing values (coming up in the next section).

myVector <- c(first = 1, second = 2, third = 3, fourth = 4)
myVector

first second  third fourth 
    1      2      3      4

Accessing Vector Contents

There are several ways to access the individual contents of a vector.

Just like with strings, in R, indexing starts at 1.

myVector <- c(a = "apple", b = "banana", c = "cow", d = "donkey", e = "elephant")

myVector[3]             # This returns the third value in the vector.
myVector[2:4]           # This returns every value starting from the second value until the fourth value. (inclusive)
myVector[c(1, 3, 4)]    # This returns specific values #1, #3, and #4.
myVector[-2]            # This returns all items excluding the second item.
myVector[-2:-4]         # This returns all items excluding all values from the second item until the fourth item. (inclusive)
myVector[c(-2, -4)]     # This returns all items excluding the speicifc values #2 and #4.

# The following lines access vectors with items that are named
myVector['a']           # This returns the value with the name 'a'
myVector[c('a', 'b')]   # This returns the values with the name 'a' and 'b'

# You can also index all elements that fulfil a condition
myVector[ grepl("le", myVector, fixed=TRUE) ] # This returns `a` and `e`, because they both contain "le".

Try these in RStudio and experiment, the best way to learn R is to code!

Modifying a Value in a Vector

To modify the value at a specific, index the value as usual and assign a value to it just like you would a regular variable.

myVector <- c(3, 4, 5)
myVector[3] <- 6
myVector

[1] 3 4 6

Key Points / Summary

• You can use vectors to make a collection of values.
• Values in a vector must be of the same data type.
• You can access and modify values in a vector using indexing.
• Indexes in R start at 1.