Syntax error How to add two columns if both contains missing values in R?

How to add two columns if both contains missing values in R?

If we want to add two columns of an R data frame and each of them contains missing values then the addition of columns can be done in one of the following ways −

  • Adding both the column values if they are numeric.

  • Returning numeric if one of the columns has missing value.

  • Returning NA if both the columns have missing value.

To this we can take help of apply function and ifelse function as shown in the below given examples.

Example 1

Following snippet creates a sample data frame −

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

The following dataframe is created −

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

To add columns of df1, add the following code to the above snippet −

x1<-sample(c(NA,1,2),20,replace=TRUE)
x2<-sample(c(NA,5),20,replace=TRUE)
df1<-data.frame(x1,x2)
df1$Sum<-apply(cbind(df1$x1,df1$x2),1,function(x) ifelse(all(is.na(x)),NA,sum(x,na.rm=T)))
df1

Output

If you execute all the above given snippets as a single program, it generates the following output: −

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

Example 2

Following snippet creates a sample data frame −

y1<-sample(c(NA,rnorm(2)),20,replace=TRUE)
y2<-sample(c(NA,rnorm(2)),20,replace=TRUE)
df2<-data.frame(y1,y2)
df2

The following dataframe is created −

      y1              y2
1   0.5109281     -0.6697566
2   NA            -0.1898259
3   NA            -0.1898259
4  -0.9540862     -0.6697566
5   NA            -0.1898259
6   NA            -0.1898259
7   NA             NA
8   0.5109281     -0.6697566
9   NA             NA
10  0.5109281      NA
11  0.5109281     -0.6697566
12 -0.9540862      NA
13 -0.9540862     -0.6697566
14  NA            -0.1898259
15  0.5109281     -0.1898259
16  NA            -0.1898259
17  0.5109281      NA
18  NA            -0.6697566
19  NA            -0.1898259
20  NA             NA

To add columns of df2, add the following code to the above snippet −

y1<-sample(c(NA,rnorm(2)),20,replace=TRUE)
y2<-sample(c(NA,rnorm(2)),20,replace=TRUE)
df2<-data.frame(y1,y2)
df2$Sum<-apply(cbind(df2$y1,df2$y2),1,function(x) ifelse(all(is.na(x)),NA,sum(x,na.rm=T)))
df2

Output

If you execute all the above given snippets as a single program, it generates the following output: −

       y1             y2          Sum
1   0.5109281      -0.6697566  -0.1588286
2   NA             -0.1898259  -0.1898259
3   NA             -0.1898259  -0.1898259
4  -0.9540862      -0.6697566  -1.6238429
5   NA             -0.1898259  -0.1898259
6   NA             -0.1898259  -0.1898259
7   NA              NA          NA
8   0.5109281      -0.6697566  -0.1588286
9   NA              NA          NA
10  0.5109281       NA          0.5109281
11  0.5109281      -0.6697566  -0.1588286
12 -0.9540862       NA         -0.9540862
13 -0.9540862      -0.6697566  -1.6238429
14  NA             -0.1898259  -0.1898259
15  0.5109281      -0.1898259   0.3211022
16  NA             -0.1898259  -0.1898259
17  0.5109281       NA          0.5109281
18  NA             -0.6697566  -0.6697566
19  NA             -0.1898259  -0.1898259
20  NA              NA          NA
Updated on: 2021-11-10T13:44:36+05:30

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