R : Converting Multiple Columns to Factor

In this article, we will explain how you can convert multiple columns (variables) to factor in R using both base R and dplyr packages.

In R, categorical variables need to be set as factor variables. Some of the numeric variables which are categorical in nature need to be transformed to factor so that R treats them as a grouping variable.

Let's create a sample data frame called mydata having 5 variables.

# Create a dummy data frame
mydata <- data.frame(
  var1 = c("A", "B", "C"),
  var2 = c("X", "Y", "Z"),
  var3 = c(1, 2, 3),
  var4 = c(7, 8, 9),
  var5 = c("G", "H", "I")
)

How to Convert Numeric Columns to Factor

In the dataframe named 'mydata', we have two numeric columns 'var3' and 'var4'. We do not want to explicitly name these columns while converting them to factor.

is.numeric function is used to identify the numeric columns. Then, the as.factor function is applied to convert the columns to factors.

Base R

numeric_cols <- sapply(mydata, is.numeric)
mydata[numeric_cols] <- lapply(mydata[numeric_cols], as.factor)
str(mydata)

In base R, you can convert multiple columns (variables) to factor using lapply and sapply functions. The lapply and sapply functions are used to perform multiple iterations (loops) in R. The only difference between them is that lapply returns list. Whereas sapply returns vector or matrix.

dplyr

library(dplyr)

mydata <- mydata %>%
  mutate(across(where(is.numeric), as.factor))

str(mydata)

In dplyr package, the across function allows you to apply a transformation across multiple columns. The mutate function is used to modify the columns of a dataframe.

How to Convert All Columns to Factor

names(mydata) command returns a character vector containing the names of all the columns in the dataframe named "mydata".

Base R

col_names <- names(mydata)
mydata[,col_names] <- lapply(mydata[,col_names] , factor)
str(mydata)

dplyr

library(dplyr)

col_names <- names(mydata)
mydata <- mydata %>%
  mutate(across(all_of(col_names), as.factor))

str(mydata)

Converting Columns to Factor using Column Position

In this case, we are converting first, second, third and fifth variables to factor variables. mydata is a data frame.

Base R

names <- c(1:3,5)
mydata[,names] <- lapply(mydata[,names] , factor)
str(mydata)

dplyr

library(dplyr)

names <- c(1:3, 5)
mydata <- mydata %>%
  mutate(across(names, as.factor))

str(mydata)

Converting Columns to Factor using Column Names

In this case, we are converting two columns 'var2' and 'var5' to factor variables.

Base R

names <- c('var2' ,'var5')
mydata[,names] <- lapply(mydata[,names] , factor)
str(mydata)

dplyr

library(dplyr)

names <- c('var2', 'var5')
mydata <- mydata %>%
  mutate(across(names, as.factor))

str(mydata)

Convert Columns to Factor Based on Condition

Suppose you want to convert only those columns to factors which have a number of unique values less than 4.

Base R

col_names <- sapply(mydata, function(col) length(unique(col)) < 4)
mydata[ , col_names] <- lapply(mydata[ , col_names] , factor)

dplyr

library(dplyr)

col_names <- sapply(mydata, function(col) length(unique(col)) < 4)
mydata <- mydata %>%
  mutate(across(names(col_names)[col_names], as.factor))

str(mydata)

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Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has over 10 years of experience in data science. During his tenure, he worked with global clients in various domains like Banking, Insurance, Private Equity, Telecom and HR.

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