Combine values into a vector
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Combine values into a vector
 Everything is a vector
 Get to know different data types in R
 Learn how to create vectors
 Use the
:
operator to create numeric sequences  Use the concatenate function
c()
to create vectors of different data types
1:100 c(1, 2, 3, 4) c("abc", "def", "ghi") c(TRUE, FALSE, TRUE)
Introduction to Vectors
A vector is a collection of elements of the same kind and the most basic data structure in R. For example, a vector could hold the four numbers 1
, 3
, 2
and 5
. Another vector could be formed with the three text strings "Welcome"
, "Hi"
and "Hello"
. These different kinds of values (numbers, text) are called data types.
A single value is also treated as a vector – a vector with only one element in it. As we will see throughout the course, this concept makes R very special. We can manipulate vectors and its values through plenty of operations that are provided by R.
One key advantage of vectors is that we can apply an operation (e.g. a multiplication) to all its values at once instead of going through each item individually. This is called vectorization.
Types of vectors
Vectors can only hold elements of the same data type. In this course we will work with the following three main data types:
Numeric values are numbers. Although they can be further split into whole numbers (integers) and numbers with decimals (doubles), R automatically converts between these subtypes if needed. Therefore, we will collectively refer to them as just numeric
values.
Character values contain textual content. These can be letters, symbols, spaces and numbers as well. They must be enclosed by quotation marks – either single quotes '___'
or double quotes "___"
.
Logical values can either be TRUE
or FALSE
. They are also often referred to as boolean or binary values. Because a logical
value can only be TRUE
or FALSE
they are most often used to answer simple questions like “Is 1 greater than 2?” or “Is it past 3 o’clock?”. These kind of questions only need answers like “Yes” (TRUE
) or “No” (FALSE
). Importantly, in R logical
values are case sensitive, which means they have to be written with capital letters.
Quiz: Data Types
Which of the following options are valid data types in R? Start ExerciseCreating a sequence of numbers
1:100 c(1, 2, 3, 4) c("abc", "def", "ghi") c(TRUE, FALSE, TRUE)
In R, even a single value is considered a vector. Creating a vector of one element is as simple as typing its value:
4 [1] 4
To create a sequence of numeric values we can use the :
operator, which takes two numbers and outputs a vector of all whole numbers in that range:
2:11 [1] 2 3 4 5 6 7 8 9 10 11
The :
operator creates a vector from the number on the lefthand side to the number on the righthand side. Therefore, the order of numbers is important. If we define the previous example the other way around, we get a vector of descending numbers, instead of ascending:
11:2 [1] 11 10 9 8 7 6 5 4 3 2
The :
operator comes handy when we need a vector of every whole number in a given range. However, if we need a vector where the numbers aren’t linear, we require something different.
Exercise: Use the : operator
Use the :
operator and create a vector from 2 to 6
Concatenating numeric values to a vector
1:100 c(1, 2, 3, 4) c("abc", "def", "ghi") c(TRUE, FALSE, TRUE)
We can combine multiple numbers into a single vector using the concatenate function c()
which links elements between the round braces together into a chain. Multiple elements need to be separated by commas.
To create our first vector holding seven different numbers we can use the concatenate function c()
like so:
c(7, 4, 2, 5, 5, 22, 1) [1] 7 4 2 5 5 22 1
Note, that the “[1]
” sign before the output above is added by R, and is always added automatically when printing out vectors. If your vectors become bigger you will see more of these prefixes. Just know that they are only added for informational purposes by R, and that they are there to help you while coding. They are not part of the vector itself.
You can see this more clearly, when the output spans over multiple lines:
1:60 [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 [22] 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 [43] 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Exercise: Concatenate numbers
Use the concatenate function c()
and create a vector containing the numbers 2, 3, 6 and 7
Creating character vectors
1:100 c(1, 2, 3, 4) c("abc", "def", "ghi") c(TRUE, FALSE, TRUE)
To create a character vector of one element, all we need to do is to type out the text. Remember that we need to use quotation marks (" "
) around character values:
"golden retriever" [1] "golden retriever"
To create a character vector of multiple elements, we can again use the concatenate function c()
. This time we will use it with characters instead of numbers:
c("golden retriever", "labrador is a family dog", "beagle") [1] "golden retriever" "labrador is a family dog" [3] "beagle"
Exercise: Create a character vector
Create a character vector with the single element: "R is awesome!"
Exercise: Concatenate text
Use the concatenate function c()
and create a vector containing four elements:

"wombat"
, 
"fennec fox"
, 
"bearded dragon"
and "tasmanian devil"
Creating logical vectors
1:100 c(1, 2, 3, 4) c("abc", "def", "ghi") c(TRUE, FALSE, TRUE)
Logical vectors can only hold the values TRUE
and FALSE
. To create a logical vector with a single value, type out one of the valid values TRUE
or FALSE
. Remember that they must be written with capital letters:
TRUE [1] TRUE
Similarly to other types of vectors, we can use the concatenate function c()
to create a logical vector of multiple elements:
c(TRUE, FALSE, TRUE, FALSE, TRUE) [1] TRUE FALSE TRUE FALSE TRUE
Exercise: Concatenate logical values
Use the concatenate function c()
and create a vector containing the three elements: TRUE
, FALSE
and TRUE
Quiz: Vectors Recap
Which of the following statements about vectors are correct? Start ExerciseRbloggers.com offers daily email updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/datascience job.
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