Convert Data Frame Column to Numeric in R (2 Examples) | Change Factor, Character & Integer


In this R tutorial, I’ll explain how to convert a data frame column to numeric in R. No matter if you need to change the class of factors, characters, or integers, this tutorial will show you how to do it.

The article is structured as follows:

Let’s dive right in!


Create Example Data

First we need to create some data in R that we can use in the examples later on:

data <- data.frame(x1 = c(1, 5, 8, 2),       # Create example data frame
                   x2 = c(3, 2, 5, 2),
                   x3 = c(2, 7, 1, 2))
data$x1 <- as.factor(data$x1)                # First column is a factor
data$x2 <- as.character(data$x2)             # Second column is a character
data$x3 <- as.integer(data$x3)               # Third column is an integer
data                                         # Print data to RStudio console

You can see the structure of our example data frame in Table 1. The data contains three columns: a factor variable, a character variable, and an integer variable.


Example Data with Factor, Character and Integer Data Type

Table 1: Example Data Frame with Factor, Character & Integer Variables.


We can check the class of each column of our data table with the sapply function:

sapply(data, class)                          # Get classes of all columns
#       x1          x2          x3 
# "factor" "character"   "integer"

The data is set up, so let’s move on to the examples…


Example 1: Convert One Variable of Data Frame to Numeric

In the first example I’m going to convert only one variable to numeric. For this task, we can use the following R code:

data$x1 <- as.numeric(as.character(data$x1))  # Convert one variable to numeric

Note: The previous code converts our factor variable to character first and then it converts the character to numeric. This is important in order to retain the values (i.e. the numbers) of the factor variable. You can learn more about that in this tutorial.

However, let’s check the classes of our columns again to see how our data has changed:

sapply(data, class)                           # Get classes of all columns
#        x1          x2          x3 
# "numeric" "character"   "integer"

As we wanted: The factor column was converted to numeric.

If you need more explanation on the R syntax of Example 1, you might have a look at the following YouTube video. In the video, I’m explaining the previous R programming code in some more detail:



Example 2: Change Multiple Columns to Numeric

In Example 1 we used the as.numeric and the as.character functions to modify one variable of our example data. However, when we want to change several variables to numeric simultaneously, the approach of Example 1 might be too slow (i.e. too much programming). In this example, I’m therefore going to show you how to change as many columns as you want at the same time.

First, we need to specify which columns we want to modify. In this example, we are converting columns 2 and 3 (i.e. the character string and the integer):

i <- c(2, 3)                                  # Specify columns you want to change

We can now use the apply function to change columns 2 and 3 to numeric:

data[ , i] <- apply(data[ , i], 2,            # Specify own function within apply
                    function(x) as.numeric(as.character(x)))

Let’s check the classes of the variables of our data frame:

sapply(data, class)                           # Get classes of all columns
#        x1        x2        x3 
# "numeric" "numeric" "numeric"

The whole data frame was converted to numeric!


Further Resources

Converting variable classes in R is a complex topic. I have therefore listed some additional resources about the Modification of R data classes in the following.

If you want to learn more about the basic data types in R, I can recommend the following video of the Data Camp YouTube channel:



Also, you could have a look at the following R tutorials of this homepage:

I hope you liked this tutorial! Let me know in the comments if you have any further questions and of cause I am also happy about general feedback.



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