Now that you know how to calculate basic math and add comments explaining your code, let’s dive into how R “thinks about” different types of data. In R and in programming, data types are the classifications we give different kinds of information pieces. In this lesson, we will explore the following R data types:
- Numeric: Any number with or without a decimal point:
0.03and the numeric null value
- Character: Any grouping of characters on your keyboard (letters, numbers, spaces, symbols, etc.) or text. Most strings are surrounded by single quotes:
' ... 'or double quotes
" ... ", though we prefer single quotes. Sometimes you will hear this type referred to as “string.”
- Logical: This data type only has two possible values— either
FALSE(without quotes). It’s helpful to think of logical types or booleans as on and off switches or as the answers to a “yes” or “no” question.
- Vectors: A list of related data that is all the same type.
- NA: This data type represents the absence of a value, and is represented by the keyword
NA(without quotes) but it has its own significance in the context of the different types. That is there is a numeric NA, a character NA, and a logical NA.
Let’s get comfortable with checking the data type of the following:
class(2) # numeric class('hello') # character class('23') #character class (FALSE) #logical class(NA) #logical
In the example above, notice that the third line is labeled a character type. Why? Because the characters
23 are in quotes, so it gets classified as a character.
In order to print a value, you must put the value inside the following syntax:
print(). Print your name as a character string.
Print your age as a numeric type.
On a new line of code, print your age as a character type.