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Categorical variables are variables that take on discrete values and can be divided into groups. In R, categorical variables can be created using the factor function. This function allows you to assign values to the categories and then use those categories in further data analysis. Examples of creating a categorical variable in R include assigning labels to a vector of values and creating a factor from a numerical vector. By using the factor function in R, it is possible to easily create categorical variables and use them to draw insights from data.
You can use the following syntax to create a in R:
#create categorical variable from scratch cat_variable <- factor(c('A', 'B', 'C', 'D')) #create categorical variable (with two possible values) from existing variable cat_variable <- as.factor(ifelse(existing_variable < 4, 1, 0)) #create categorical variable (with multiple possible values) from existing variable cat_variable <- as.factor(ifelse(existing_variable < 3, 'A', ifelse(existing_variable < 4, 'B', ifelse(existing_variable < 5, 'C', ifelse(existing_variable < 6, 'D',0)))))
The following examples show how to use this syntax in practice.
Example 1: Create a Categorical Variable from Scratch
The following code shows how to create a categorical variable from scratch:
#create data frame df <- data.frame(var1=c(1, 3, 3, 4, 5), var2=c(7, 7, 8, 3, 2), var3=c(3, 3, 6, 10, 12), var4=c(14, 16, 22, 19, 18)) #view data frame df var1 var2 var3 var4 1 1 7 3 14 2 3 7 3 16 3 3 8 6 22 4 4 3 10 19 5 5 2 12 18 #add categorical variable named 'type' to data frame df$type <- factor(c('A', 'B', 'B', 'C', 'D')) #view updated data frame df var1 var2 var3 var4 type 1 1 7 3 14 A 2 3 7 3 16 B 3 3 8 6 22 B 4 4 3 10 19 C 5 5 2 12 18 D
Example 2: Create a Categorical Variable (with Two Values) from Existing Variable
The following code shows how to create a categorical variable from an existing variable in a data frame:
#create data frame df <- data.frame(var1=c(1, 3, 3, 4, 5), var2=c(7, 7, 8, 3, 2), var3=c(3, 3, 6, 10, 12), var4=c(14, 16, 22, 19, 18)) #view data frame df var1 var2 var3 var4 1 1 7 3 14 2 3 7 3 16 3 3 8 6 22 4 4 3 10 19 5 5 2 12 18 #add categorical variable named 'type' using values from 'var4' column df$type <- as.factor(ifelse(df$var1 < 4, 1, 0)) #view updated data frame df var1 var2 var3 var4 type 1 1 7 3 14 1 2 3 7 3 16 1 3 3 8 6 22 1 4 4 3 10 19 0 5 5 2 12 18 0
Using the ifelse() statement, we created a new categorical variable called “type” that takes the following values:
- 1 if the value in the ‘var1’ column is less than 4.
- 0 if the value in the ‘var1’ column is not less than 4.
Example 3: Create a Categorical Variable (with Multiple Values) from Existing Variable
The following code shows how to create a categorical variable (with multiple values) from an existing variable in a data frame:
#create data frame df <- data.frame(var1=c(1, 3, 3, 4, 5), var2=c(7, 7, 8, 3, 2), var3=c(3, 3, 6, 10, 12), var4=c(14, 16, 22, 19, 18)) #view data frame df var1 var2 var3 var4 1 1 7 3 14 2 3 7 3 16 3 3 8 6 22 4 4 3 10 19 5 5 2 12 18 #add categorical variable named 'type' using values from 'var4' column df$type <- as.factor(ifelse(df$var1 < 3, 'A', ifelse(df$var1 < 4, 'B', ifelse(df$var1 < 5, 'C', ifelse(df$var1 < 6, 'D', 'E'))))) #view updated data frame df var1 var2 var3 var4 type 1 1 7 3 14 A 2 3 7 3 16 B 3 3 8 6 22 B 4 4 3 10 19 C 5 5 2 12 18 D
Using the ifelse() statement, we created a new categorical variable called “type” that takes the following values:
- ‘A‘ if the value in the ‘var1’ column is less than 3.
- Else, ‘B‘ if the value in the ‘var1’ column is less than 4.
- Else, ‘C‘ if the value in the ‘var1’ column is less than 5.
- Else, ‘D‘ if the value in the ‘var1’ column is less than 6.
- Else, ‘E‘.