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How to find the number of NA’s in each column of an R data frame?
Sometimes the data frame is filled with too many missing values/ NA’s and each column of the data frame contains at least one NA. In this case, we might want to find out how many missing values exists in each of the columns. Therefore, we can use colSums function along with is.na in the following manner: colSums(is.na(df)) #here df refers to data frame name.
Consider the below data frame −
Example
set.seed(109) x1<-sample(c(0:1,NA),20,replace=TRUE) x2<-sample(c(rpois(5,2),NA),20,replace=TRUE)df1<-data.frame(x1,x2) df1
Output
x1 x2 1 0 1 2 1 NA 3 NA 0 4 NA 0 5 1 1 6 1 1 7 NA NA 8 NA NA 9 0 1 10 NA 1 11 1 1 12 0 1 13 NA 1 14 0 0 15 1 1 16 NA 0 17 1 1 18 1 NA 19 NA NA 20 0 0
Finding the number of NA’s in each column of the data frame df1 −
Example
colSums(is.na(df1))
Output
x1 x2 6 4
Let’s have a look at another example −
Example
y1<-sample(c(100,105,NA,115,120),20,replace=TRUE) y2<-sample(c(rnorm(3,1,0.04),NA),20,replace=TRUE) df2<-data.frame(y1,y2) df2
Output
y1 y2 1 NA NA 2 NA NA 3 105 NA 4 115 0.9910075 5 120 NA 6 120 0.9547570 7 105 0.9547570 8 105 1.0468139 9 120 0.9910075 10 115 0.9547570 11 115 0.9910075 12 100 0.9910075 13 NA 1.0468139 14 120 1.0468139 15 NA 1.0468139 16 115 NA 17 115 1.0468139 18 100 NA 19 120 0.9910075 20 120 0.9910075
Finding the number of NA’s in each column of the data frame df2 −
Example
colSums(is.na(df2))
Output
y1 y2 3 3
Updated on: 09-Oct-2020
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