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How to find the number of groupwise missing values in an R data frame?
In data science, we often face the problem of missing values and we need to define a way to replace them with an appropriate value or we can complete remove them. If we want to replace the missing then we also need to know how many missing values are there. Therefore, if we have a data frame with grouping column then finding the number of groupwise missing values can be done with aggregate function as shown in the below examples.
Example1
Consider the below data frame −
> Group<-sample(c("A","B"),20,replace=TRUE)
> x<-sample(c(NA,2),20,replace=TRUE)
> df1<-data.frame(Group,x)
> df1Output
Group x 1 A 2 2 A NA 3 A NA 4 B 2 5 B 2 6 B NA 7 A 2 8 B NA 9 A 2 10 B NA 11 A NA 12 A 2 13 B 2 14 B 2 15 B NA 16 A NA 17 A 2 18 B 2 19 B NA 20 A NA
Finding groupwise missing values in df1 −
> aggregate(x~Group,data=df1, function(x) {sum(is.na(x))},na.action=NULL)Output
Group x 1 A 5 2 B 5
Example2
> Class<-sample(c("First","Second"),20,replace=TRUE)
> Score<-sample(c(NA,10,15),20,replace=TRUE)
> df2<-data.frame(Class,Score)
> df2Output
Class Score 1 Second 15 2 First 15 3 Second 10 4 First 10 5 First 15 6 Second 10 7 First 15 8 Second NA 9 Second 15 10 First 15 11 Second NA 12 Second NA 13 Second NA 14 Second 10 15 Second NA 16 First 10 17 First NA 18 First 15 19 First 10 20 Second NA
Finding groupwise missing values in df2 −
> aggregate(Score~Class,data=df2, function(x) {sum(is.na(x))},na.action=NULL)Output
Class Score 1 First 1 2 Second 6
Updated on: 05-Mar-2021
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