Categorical Variable from the Existing column using multiple values
To create a categorical variable from the existing column, we use multiple if-else statements within the factor() function and give a value to a column if a certain condition is true, if none of the conditions are true we use the else value of the last statement.
Syntax:
df$categorical_variable <- as.factor( ifelse(condition, val,ifelse(condition, val,ifelse(condition, val, ifelse(condition, val, vale_else)))))
where
- df: determines the data frame.
- categorical_variable: determines the final column variable which will contain categorical data.
- condition: determines the condition to be checked, if the condition is true, use val.
- val_else: determines the value if no condition is true.
Example:
Here, is a basic data frame where a new column group is added as a categorical variable from multiple if-else conditions.
R
# create sample data frame df <- data.frame (x= c (10, 23, 13, 41, 15, 11, 23, 45, 95, 23, 75), y= c (71, 17, 28, 32, 12, 13, 41, 15, 11, 23, 34)) # Add categorical variable to the data frame df$group <- as.factor ( ifelse (df$x<20, 'A' , ifelse (df$x<30, 'B' , ifelse (df$x<50, 'C' , ifelse (df$x<90, 'D' , 'E' ))))) # print data frame df |
Output:
x y group 1 10 71 A 2 23 17 B 3 13 28 A 4 41 32 C 5 15 12 A 6 11 13 A 7 23 41 B 8 45 15 C 9 95 11 E 10 23 23 B 11 75 34 D
How to Create Categorical Variables in R?
In this article, we will learn how to create categorical variables in the R Programming language.
In statistics, variables can be divided into two categories, i.e., categorical variables and quantitative variables. The variables which consist of numerical quantifiable values are known as quantitative variables and a categorical variable is a variable that can take on one of a limited, and usually fixed, number of possible values, assigning each individual or other unit of observation to a particular group or nominal category on the basis of some qualitative property.