R factor is a data structure which is used for fields which take only predefined finite number of values. These are the variable which takes a limited number of different values. These are the data objects which are used to categorize the data and to store it on multiple levels. It can store both integers and strings values, and are useful in the column that has a limited number of unique values.
Factors have labels which are associated with the unique integers stored in it. It contains predefined set value known as levels and by default R always sorts levels in alphabetical order.
Attributes of a factor
There are the following attributes of a factor in R
- X
It is the input vector which is to be transformed into a factor. - levels
It is an input vector that represents a set of unique values which are taken by x. - labels
It is a character vector which corresponds to the number of labels. - Exclude
It is used to specify the value which we want to be excluded, - ordered
It is a logical attribute which determines if the levels are ordered. - nmax
It is used to specify the upper bound for the maximum number of level.
How to create a factor?
In R, it is quite simple to create a factor. A factor is created in two steps
- In the first step, we create a vector.
- Next step is to convert the vector into a factor,
R provides factor() function to convert the vector into factor. There is the following syntax of factor() function
Let’s see an example to understand how factor function is used.
Example
# Creating a vector as input.
data <- c("Shubham","Nishka","Arpita","Nishka","Shubham","Sumit","Nishka","Shubham","Sumit","Arpita","Sumit")
print(data)
print(is.factor(data))
# Applying the factor function.
factor_data<- factor(data)
print(factor_data)
print(is.factor(factor_data))
Output:
[1] "Shubham" "Nishka" "Arpita" "Nishka" "Shubham" "Sumit" "Nishka" [8] "Shubham" "Sumit" "Arpita" "Sumit" [1] FALSE [1] Shubham Nishka Arpita Nishka Shubham Sumit Nishka Shubham Sumit [10] Arpita Sumit Levels: Arpita Nishka Shubham Sumit [1] TRUE
Accessing components of factor
Like vectors, we can access the components of factors. The process of accessing components of factor is much more similar to the vectors. We can access the element with the help of the indexing method or using logical vectors. Let’s see an example in which we understand the different-different ways of accessing the components.
Example
# Creating a vector as input.
data <- c("Shubham","Nishka","Arpita","Nishka","Shubham","Sumit","Nishka","Shubham","Sumit","Arpita","Sumit")
# Applying the factor function.
factor_data<- factor(data)
#Printing all elements of factor
print(factor_data)
#Accessing 4th element of factor
print(factor_data[4])
#Accessing 5th and 7th element
print(factor_data[c(5,7)])
#Accessing all elemcent except 4th one
print(factor_data[-4])
#Accessing elements using logical vector
print(factor_data[c(TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE)])
Output:
[1] Shubham Nishka Arpita Nishka Shubham Sumit Nishka Shubham Sumit [10] Arpita Sumit Levels: Arpita Nishka Shubham Sumit [1] Nishka Levels: Arpita Nishka Shubham Sumit [1] Shubham Nishka Levels: Arpita Nishka Shubham Sumit [1] Shubham Nishka Arpita Shubham Sumit Nishka Shubham Sumit Arpita [10] Sumit Levels: Arpita Nishka Shubham Sumit [1] Shubham Shubham Sumit Nishka Sumit Levels: Arpita Nishka Shubham Sumit
Modification of factor
Like data frames, R allows us to modify the factor. We can modify the value of a factor by simply re-assigning it. In R, we cannot choose values outside of its predefined levels means we cannot insert value if it’s level is not present on it. For this purpose, we have to create a level of that value, and then we can add it to our factor.
Let’s see an example to understand how the modification is done in factors.
Example
# Creating a vector as input.
data <- c("Shubham","Nishka","Arpita","Nishka","Shubham")
# Applying the factor function.
factor_data<- factor(data)
#Printing all elements of factor
print(factor_data)
#Change 4th element of factor with sumit
factor_data[4] <-"Arpita"
print(factor_data)
#change 4th element of factor with "Gunjan"
factor_data[4] <- "Gunjan" # cannot assign values outside levels
print(factor_data)
#Adding the value to the level
levels(factor_data) <- c(levels(factor_data),"Gunjan")#Adding new level
factor_data[4] <- "Gunjan"
print(factor_data)
Output:
[1] Shubham Nishka Arpita Nishka Shubham Levels: Arpita Nishka Shubham [1] Shubham Nishka Arpita Arpita Shubham Levels: Arpita Nishka Shubham Warning message: In `[<-.factor`(`*tmp*`, 4, value = "Gunjan") : invalid factor level, NA generated [1] Shubham Nishka Arpita Shubham Levels: Arpita Nishka Shubham [1] Shubham Nishka Arpita Gunjan Shubham Levels: Arpita Nishka Shubham Gunjan
Factor in Data Frame
When we create a frame with a column of text data, R treats this text column as categorical data and creates factor on it.
Example
# Creating the vectors for data frame.
height <- c(132,162,152,166,139,147,122)
weight <- c(40,49,48,40,67,52,53)
gender <- c("male","male","female","female","male","female","male")
# Creating the data frame.
input_data<- data.frame(height,weight,gender)
print(input_data)
# Testing if the gender column is a factor.
print(is.factor(input_data$gender))
# Printing the gender column to see the levels.
print(input_data$gender)
Output:
height weight gender 1 132 40 male 2 162 49 male 3 152 48 female 4 166 40 female 5 139 67 male 6 147 52 female 7 122 53 male [1] TRUE [1] male male female female male female male Levels: female male
Changing order of the levels
In R, we can change the order of the levels in the factor with the help of the factor function.
Example
data <- c("Nishka","Gunjan","Shubham","Arpita","Arpita","Sumit","Gunjan","Shubham")
# Creating the factors
factor_data<- factor(data)
print(factor_data)
# Apply the factor function with the required order of the level.
new_order_factor<- factor(factor_data,levels = c("Gunjan","Nishka","Arpita","Shubham","Sumit"))
print(new_order_factor)
Output:
[1] Nishka Gunjan Shubham Arpita Arpita Sumit Gunjan Shubham Levels: Arpita Gunjan Nishka Shubham Sumit [1] Nishka Gunjan Shubham Arpita Arpita Sumit Gunjan Shubham Levels: Gunjan Nishka Arpita Shubham Sumit
Generating Factor Levels
R provides gl() function to generate factor levels. This function takes three arguments i.e., n, k, and labels. Here, n and k are the integers which indicate how many levels we want and how many times each level is required.
There is the following syntax of gl() function which is as follows
gl(n, k, labels)
- n indicates the number of levels.
- k indicates the number of replications.
- labels is a vector of labels for the resulting factor levels.
Example
gen_factor<- gl(3,5,labels=c("BCA","MCA","B.Tech"))
gen_factor
Output:
[1] BCA BCA BCA BCA BCA MCA MCA MCA MCA MCA [11] B.Tech B.Tech B.Tech B.Tech B.Tech Levels: BCA MCA B.Tech
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