You can use the is.na() function in R to check for missing values in vectors and data frames.
#check if each individual value is NA is.na(x) #count total NA values sum(is.na(x)) #identify positions of NA values which(is.na(x))
The following examples show how to use this function in practice.
Example 1: Use is.na() with Vectors
The following code shows how to use the is.na() function to check for missing values in a vector:
#define vector with some missing values
x
#check if each individual value is NA
is.na(x)
[1] FALSE FALSE FALSE TRUE FALSE TRUE FALSE FALSE
#count total NA values
sum(is.na(x))
[1] 2
#identify positions of NA values
which(is.na(x))
[1] 4 6
From the output we can see:
- There are 2 missing values in the vector.
- The missing values are located in position 4 and 6.
Example 2: Use is.na() with Data Frames
The following code shows how to use the is.na() function to check for missing values in a data frame:
#create data frame
df frame(var1=c(1, 3, 3, 4, 5),
var2=c(7, NA, NA, 3, 2),
var3=c(3, 3, 6, NA, 8),
var4=c(NA, 1, 2, 8, 9))
#view data frame
df
var1 var2 var3 var4
1 1 7 3 NA
2 3 NA 3 1
3 3 NA 6 2
4 4 3 NA 8
5 5 2 8 9
#find total NA values in data frame
sum(is.na(df))
[1] 4
#find total NA values by column
sapply(df, function(x) sum(is.na(x)))
var1 var2 var3 var4
0 2 1 1
From the output we can see that there are 4 total NA values in the data frame.
We can also see:
- There are 0 NA values in the ‘var1’ column.
- There are 2 NA values in the ‘var2’ column.
- There are 1 NA values in the ‘var3’ column.
- There are 1 NA values in the ‘var4’ column.
Additional Resources
The following tutorials explain other useful functions that can be used to handle missing values in R.
How to Use na.omit in R
How to Use na.rm in R
How to Use is.null in R
How to Impute Missing Values in R