HOWTO · R
How to Omit NA in R
This tutorial demonstrates how to remove unnecessary NA values using na.omit() in R.
The na.omit() method from R omits all unnecessary values from a data frame in R. NA denotes these values.
This tutorial demonstrates how to use na.omit in R.
Use na.omit() to Remove NA Values From a Vector in R
na.omit() can remove NA values from a vector; see example.
#define the vector
a <- c(13, NA, NA, 7, NA, 19)
print(a)
#remove NA values from vector using na.omit
a <- na.omit(a)
a
The code first prints the vector with NA values and then omits the NA values. See output:
[1] 13 NA NA 7 NA 19
[1] 13 7 19
attr(,"na.action")
[1] 2 3 5
attr(,"class")
[1] "omit"
The output for na.omit is the remaining values and the index numbers of NA values; we can get the simple remaining values by using the code below.
#define the vector
a <- c(13, NA, NA, 7, NA, 19)
print(a)
#remove NA values from vector using na.omit, as.numeric
a <- as.numeric(na.omit(a))
a
The output will be simple.
[1] 13 NA NA 7 NA 19
[1] 13 7 19
Use na.omit() to Remove Rows With NA Values From a Data Frame in R
na.omit() can remove the rows with NA values from a data frame. See example:
Delftstack = data.frame(Name=c('Jack', 'John', 'Mike', 'Michelle', 'Jhonny'),
LastName=c(NA, 'Cena', 'Chandler', 'McCool', 'Nitro'),
Id=c(101, 102, NA, 104, NA),
Designation=c('CEO', 'Project Manager', NA , 'Junior Dev', 'Intern'))
# Data frame before omit
Delftstack
# Use omit
Delftstack <- na.omit(Delftstack)
# Data frame after omit
Delftstack
The code above will remove all the rows with NA values from the given data frame. See output:
Name LastName Id Designation
1 Jack <NA> 101 CEO
2 John Cena 102 Project Manager
3 Mike Chandler NA <NA>
4 Michelle McCool 104 Junior Dev
5 Jhonny Nitro NA Intern
Name LastName Id Designation
2 John Cena 102 Project Manager
4 Michelle McCool 104 Junior Dev
Use na.omit() to Remove Rows With NA Values From Specific Columns in R
na.omit() can be specified based on the columns; we can pass the column name to remove rows with NA values based on that specific column. See example:
Delftstack = data.frame(Name=c('Jack', 'John', 'Mike', 'Michelle', 'Jhonny'),
LastName=c(NA, 'Cena', 'Chandler', 'McCool', 'Nitro'),
Id=c(101, 102, NA, 104, NA),
Designation=c('CEO', 'Project Manager', NA , 'Junior Dev', 'Intern'))
# Data frame before omit
Delftstack
# Use omit
Delftstack <- Delftstack[!(is.na(Delftstack$Id)), ]
# Data frame after omit
Delftstack
The code removes the rows with NA values based on the Id column. See output:
Name LastName Id Designation
1 Jack <NA> 101 CEO
2 John Cena 102 Project Manager
3 Mike Chandler NA <NA>
4 Michelle McCool 104 Junior Dev
5 Jhonny Nitro NA Intern
Name LastName Id Designation
1 Jack <NA> 101 CEO
2 John Cena 102 Project Manager
4 Michelle McCool 104 Junior Dev
