Count the number of NA values in a DataFrame column in R
Last Updated :
26 Mar, 2021
A null value in R is specified using either NaN or NA. In this article, we will see how can we count these values in a column of a dataframe.
Approach
- Create dataframe
- Pass the column to be checked to is.na() function
Syntax: is.na(column)
Parameter:
column: column to be searched for na values
Returns:
A vector with boolean values, TRUE for NA otherwise FALSE
- From the vector add the values which are TRUE
- Display this number
- Here, 0 means no NA value
Given below are few examples
Example 1:
R
df<- data.frame (x = c (1,2, NA ), y = rep ( NA , 3))
print ( "dataframe is " )
print (df)
print ( "vector is" )
vec = is.na (df[,1])
print (vec)
count = sum (vec)
print ( "count of NA in first column is" )
print (count)
|
Output:
Example 2:
R
df<- data.frame (x = c ( "kapil" , "rahul" , NA , NA ), y = c (1,2, NA ,3))
print ( "dataframe is " )
print (df)
print ( "vector is" )
vec = is.na (df[,1])
print (vec)
count = sum (vec)
print ( "count of NA in first column is" )
print (count)
|
Output:
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