Fill NA Values by 0 in a data.table in R (Example Code)
This tutorial demonstrates how to replace the NA values in a data.table by 0 in the R programming language. The replacement works for all kinds of columns like numeric, stringr, and logical.
Setting up the Example
Install and load the data.table package.
install.packages("data.table") # Install & load data.table package library("data.table") |
As an example, we take the iris dataset.
data(iris) # Load iris data set head(iris) # Sepal.Length Sepal.Width Petal.Length Petal.Width Species # 1 5.1 3.5 1.4 0.2 setosa # 2 4.9 3.0 1.4 0.2 setosa # 3 4.7 3.2 1.3 0.2 setosa # 4 4.6 3.1 1.5 0.2 setosa # 5 5.0 3.6 1.4 0.2 setosa # 6 5.4 3.9 1.7 0.4 setosa |
With class(), we see that iris data is a data.frame.
class(iris) # Object class of the data # [1] "data.frame" |
Copy the data to a new object called iris_dt and transform iris_dt into a data.table.
iris_dt <- data.table::copy(iris) # Replicate iris data set setDT(iris_dt) # Convert iris to a data.table class(iris_dt) # Object class of the data # [1] "data.table" "data.frame" |
Example: Replace NA values in all columns of the iris dataset
In data.table iris_dt, there are no NAs as we see from the following command.
iris_dt_no_na <- iris_dt # Replicate iris data.table anyNA(iris_dt_no_na) # Test if data.table contains NA # [1] FALSE |
We therefore create a new data.table object iris_dt_with_na which contains the information of iris_dt, but were we set the first 10 values of column Sepal.Length as NA.
iris_dt_with_na <- iris_dt # Replicate iris data.table iris_dt_with_na$Sepal.Length[1:10] <- NA # Set first 10 values of Sepal.Length as NA anyNA(iris_dt_with_na) # Test if data.table contains NA # [1] TRUE |
We can substitute the NA values in iris_dt_with_na by 0 with the following lines of code.
iris_dt_with_na_new <- iris_dt_with_na # Replicate data.table with NA iris_dt_with_na_new[is.na(iris_dt_with_na_new), ] <- 0 # Fill all NA entries by 0 head(iris_dt_with_na_new) # Sepal.Length Sepal.Width Petal.Length Petal.Width Species # 1: 0 3.5 1.4 0.2 setosa # 2: 0 3.0 1.4 0.2 setosa # 3: 0 3.2 1.3 0.2 setosa # 4: 0 3.1 1.5 0.2 setosa # 5: 0 3.6 1.4 0.2 setosa # 6: 0 3.9 1.7 0.4 setosa |
anyNA(iris_dt_with_na_new) # Test if data.table contains NA # [1] FALSE |
Applying function anyNA() assures us that there are no NAs left in the data.
Related Articles
In addition, you could have a look at the related tutorials on this website.
Note: This article was created in collaboration with Anna-Lena Wölwer. Anna-Lena is a researcher and programmer who creates tutorials on statistical methodology as well as on the R programming language. You may find more info about Anna-Lena and her other articles on her profile page.