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How to check if a data frame has any missing value in R?
To check if a data frame has any missing value in R, we can use any function along with is.na function. For Example, if we have a data frame called df then we can use the below command to check whether df contains any missing value or not
any(is.na(df))
Example 1
Following snippet creates a sample data frame −
x1<-rpois(20,5) x2<-sample(c(NA,2,6),20,replace=TRUE) df1<-data.frame(x1,x2) df1
The following dataframe is created −
x1 x2 1 4 6 2 8 6 3 5 6 4 5 2 5 6 NA 6 5 6 7 3 NA 8 4 2 9 9 NA 10 2 6 11 6 NA 12 6 NA 13 6 6 14 6 NA 15 3 6 16 5 6 17 5 NA 18 4 2 19 2 6 20 3 NA
To check whether df1 has any NA on the above created data frame, add the following code to the above snippet −
x1<-rpois(20,5) x2<-sample(c(NA,2,6),20,replace=TRUE) df1<-data.frame(x1,x2) any(is.na(df1))
Output
If you execute all the above given snippets as a single program, it generates the following Output −
[1] TRUE
Example 2
Following snippet creates a sample data frame −
y1<-sample(c(NA,rnorm(5)),20,replace=TRUE) y2<-rnorm(20) df2<-data.frame(y1,y2) df2
The following dataframe is created −
y1 y2 1 -1.4175108 1.8349444 2 -2.7647068 -0.6014623 3 NA -0.8020289 4 -1.0745120 -0.8106467 5 -2.7647068 0.6680208 6 -2.7647068 -0.5579063 7 NA 1.7695050 8 -1.0745120 -0.1914589 9 0.4555854 0.5047105 10 -1.4175108 -0.6461347 11 -1.0745120 0.7005221 12 -1.0745120 1.9436422 13 0.4555854 -0.4179736 14 0.4555854 -0.2962887 15 0.5136818 1.5961105 16 -1.4175108 0.6244578 17 -1.0745120 -0.4413115 18 0.5136818 -1.4493746 19 0.5136818 -0.1654110 20 -2.7647068 0.7870973
To check whether df2 has any NA on the above created data frame, add the following code to the above snippet −
y1<-sample(c(NA,rnorm(5)),20,replace=TRUE) y2<-rnorm(20) df2<-data.frame(y1,y2) any(is.na(df2))
Output
If you execute all the above given snippets as a single program, it generates the following Output −
[1] TRUE
Example 3
Following snippet creates a sample data frame −
z1<-runif(20,1,5) z2<-runif(20,1,5) df3<-data.frame(z1,z2) df3
The following dataframe is created −
z1 z2 1 4.199921 3.974369 2 1.362028 2.467372 3 3.970619 4.989726 4 1.969228 4.985778 5 4.238796 1.545944 6 3.406546 3.301960 7 2.345338 1.012634 8 2.181524 4.013063 9 2.187973 3.121378 10 2.136693 3.059296 11 3.430986 1.243260 12 1.427495 1.387059 13 4.714494 3.976311 14 3.235821 3.264096 15 4.604128 4.383884 16 1.398644 3.596508 17 3.139503 1.853239 18 1.764061 3.128764 19 3.234675 3.491583 20 4.461674 3.580696
To check whether df3 has any NA on the above created data frame, add the following code to the above snippet −
z1<-runif(20,1,5) z2<-runif(20,1,5) df3<-data.frame(z1,z2) any(is.na(df3))
Output
If you execute all the above given snippets as a single program, it generates the following Output −
[1] FALSE
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