How to find the length of columns for missing values in R?

The length of columns for missing values means the number of missing values in the data frame. This can be easily done with the help of colSums function where we will find the total number of NA values with is.na. For example, if we have a data frame called df that contains some missing values then the length of columns for missing values can be found by using the command colSums(is.na(df)).

Example1

Consider the below data frame −

Live Demo

> x1<-sample(c(1,NA),20,replace=TRUE)
> x2<-sample(c(5,NA),20,replace=TRUE)
> x3<-sample(c(2,NA),20,replace=TRUE)
> x4<-sample(c(2,NA),20,replace=TRUE)
> df1<-data.frame(x1,x2,x3,x4)
> df1

Output

   x1 x2 x3 x4
1  NA NA  2  2
2  NA NA NA  2
3   1 NA  2 NA
4  NA  5 NA NA
5   1  5 NA NA
6  NA  5 NA  2
7   1 NA NA  2
8   1  5 NA NA
9  NA NA  2 NA
10  1  5 NA NA
11 NA NA NA NA
12 NA NA  2  2
13  1 NA NA  2
14  1 NA NA  2
15 NA NA NA NA
16  1 NA NA NA
17  1  5 NA NA
18 NA NA  2 NA
19  1 NA NA NA
20  1 NA  2  2

Finding the length of columns for missing values in df1 −

> colSums(is.na(df1))

Output

x1 x2 x3 x4
9 14 14 12

Example2

Live Demo

> y1<-sample(c(101,NA),20,replace=TRUE)
> y2<-sample(c(325,NA),20,replace=TRUE)
> y3<-sample(c(250,NA),20,replace=TRUE)
> df2<-data.frame(y1,y2,y3)
> df2

Output

    y1  y2  y3
1  101 325  NA
2   NA  NA  NA
3  101  NA  NA
4  101 325 250
5   NA  NA  NA
6  101 325 250
7  101 325  NA
8   NA 325 250
9  101 325 250
10  NA 325  NA
11 101 325 250
12  NA  NA 250
13 101  NA  NA
14  NA 325  NA
15  NA 325  NA
16  NA  NA  NA
17  NA  NA  NA
18 101 325 250
19 101  NA  NA
20  NA 325 250

Finding the length of columns for missing values in df2 −

> colSums(is.na(df2))

Output

y1 y2 y3
10 8 12

Nizamuddin Siddiqui

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Updated on: 05-Mar-2021

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