How to check missing values in R dataframe ?
Last Updated :
21 Apr, 2021
In this article, we are going to see how to find out the missing values in the data frame in R Programming Language.
Approach:
Step 1: Create DataFrame.
Let us first create a data frame with some missing values and then demonstrate with an example how to find the missing values.
R
data <- data.frame (x1 = c ( NA , 5, 6, 8, 9),
x2 = c (2, 4, NA , NA , 1),
x3 = c (3,6,7,0,3),
x4 = c ( "Hello" , "value" ,
NA , "geeksforgeeks" , NA ))
display (data)
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Output:
We have created a data frame with some missing values (NA).
Step 2: Now to check the missing values we are using is.na() function in R and print out the number of missing items in the data frame as shown below.
Syntax: is.na()
Parameter: x: data frame
Example 1:
In this example, we have first created data with some missing values and then found the missing value in particular columns x1,×2, x3, and x4 respectively using the above function.
R
data <- data.frame (x1 = c ( NA , 5, 6, 8, 9),
x2 = c (2, 4, NA , NA , 1),
x3 = c (3,6,7,0,3),
x4 = c ( "Hello" , "value" ,
NA , "geeksforgeeks" , NA ))
data
which ( is.na (data$x1))
which ( is.na (data$x2))
which ( is.na (data$x3))
which ( is.na (data$x4))
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Output:
Print the variables which have missing values and the number of missing values.
Example 2:
Let’s find the number of missing values using a different approach, here in this example, we have created data with missing values and then find the number of missing values in the data.
R
Name <- c ( "John" , "Sunny" , NA )
Age <- c (31, 18, NA )
number<- c ( "0" , "1" , "2" )
data <- data.frame (Name, Sex, number)
display (data)
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Output:
We have a data frame, and we have to find the number of missing values in this data frame.
R
Name <- c ( "John" , "Sunny" , NA )
Age <- c (31, 18, NA )
number<- c ( "0" , "1" , "2" )
data <- data.frame (Name, Sex, number)
sum ( is.na (data))
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Output:
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