Factors are variables in R which take on a limited number of different values; such variables are often referred to as categorical variables.
In a dataset, we can distinguish two types of variables: categorical and continuous.
In a categorical variable, the value is limited and usually based on a particular finite group. For example, a categorical variable can be countries, year, gender, occupation.
A continuous variable, however, can take any values, from integer to decimal. For example, we can have the revenue, price of a share, etc..
R stores categorical variables into a factor. Let's check the code below to convert a character variable into a factor variable. Characters are not supported in machine learning algorithm, and the only way is to convert a string to an integer.
factor(x = character(), levels, labels = levels, ordered = is.ordered(x))
x: A vector of data. Need to be a string or integer, not decimal.
Levels: A vector of possible values taken by x. This argument is optional. The default value is the unique list of items of the vector x.
Labels: Add a label to the x data. For example, 1 can take the label `male` while 0, the label `female`.
ordered: Determine if the levels should be ordered.
Let's create a factor data frame.
# Create gender vector
gender_vector <- c("Male", "Female", "Female", "Male", "Male")
# Convert gender_vector to a factor
##  "character"
##  "factor"
Ordinal Categorical Variable
Ordinal categorical variables do have a natural ordering. We can specify the order, from the lowest to the highest with order = TRUE and highest to lowest with order = FALSE.
We can use summary to count the values for each factor.
# Create Ordinal categorical vector
day_vector <- c('evening', 'morning', 'afternoon', 'midday', 'midnight', 'evening')
# Convert `day_vector` to a factor with ordered level
factor_day <- factor(day_vector, order = TRUE, levels =c('morning', 'midday', 'afternoon', 'evening', 'midnight'))
# Print the new variable
##  evening morning afternoon midday
Continuous class variables are the default value in R. They are stored as numeric or integer. We can see it from the dataset below. mtcars is a built-in dataset. It gathers information on different types of car. We can import it by using mtcars and check the class of the variable mpg, mile per gallon. It returns a numeric value, indicating a continuous variable.