How to convert a column with missing values to binary with 0 for missing values in R?

R ProgrammingServer Side ProgrammingProgramming

To convert a column with missing values to binary with 0 for missing values, we can use as.integer function with complete.cases for the data frame column. For example, if we have a data frame called df that contains a column x which has some missing values then the column x can be converted to binary with 0 for missing values by using the command −

as.integer(complete.cases(df$x))

Example1

Consider the below data frame −

Live Demo

> x1<-sample(c(NA,2),20,replace=TRUE)
> y1<-rpois(20,5)
> df1<-data.frame(x1,y1)
> df1

Output

   x1 y1 1  NA  2 2   2  5 3   2 10 4   2  2 5   2  4 6  NA  7 7  NA  5 8  NA  6 9   2  5 10  2  7 11  2  3 12  2  2 13 NA  2 14  2  5 15 NA  6 16 NA  5 17 NA  5 18  2  5 19  2  4 20  2 10

Converting column x1 to binary with 0 for missing values −

> df1$x1<-as.integer(complete.cases(df1$x1))
> df1

Output

   x1 y1 1   0  2 2   1  5 3   1 10 4   1  2 5   1  4 6   0  7 7   0  5 8   0  6 9   1  5 10  1  7 11  1  3 12  1  2 13  0  2 14  1  5 15  0  6 16  0  5 17  0  5 18  1  5 19  1  4 20  1 10

Example2

Live Demo

> x2<-sample(c(NA,rnorm(2)),20,replace=TRUE)
> y2<-rnorm(20)
> df2<-data.frame(x2,y2)
> df2

Output

         x2          y2
1  0.226603  0.25344032
2  0.226603  1.29778682
3  0.545375 -0.66657868
4        NA -1.69272917
5        NA  0.82631979
6  0.545375 -0.12555785
7  0.545375  0.06530913
8  0.545375  0.28359006
9        NA -0.36156762
10 0.226603  0.50943088
11 0.545375 -0.03497627
12 0.545375  1.04488383
13 0.226603  0.55466746
14 0.545375  2.13492023
15       NA  1.18845284
16 0.545375 -0.32171987
17 0.545375 -0.04996223
18 0.226603 -0.41604823
19 0.226603 -1.11003170
20 0.545375  0.34924872

Converting column x2 to binary with 0 for missing values −

> df2$x2<-as.integer(complete.cases(df2$x2))
> df2

Output

   x2          y2 1   1  0.25344032 2   1  1.29778682 3   1 -0.66657868 4   0 -1.69272917 5   0  0.82631979 6   1 -0.12555785 7   1  0.06530913 8   1  0.28359006 9   0 -0.36156762 10  1  0.50943088 11  1 -0.03497627 12  1  1.04488383 13  1  0.55466746 14  1  2.13492023 15  0  1.18845284 16  1 -0.32171987 17  1 -0.04996223 18  1 -0.41604823 19  1 -1.11003170 20  1  0.34924872

raja
Published on 06-Mar-2021 09:43:45
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