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)
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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)
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Output: