dplyr nested ifelse errors - is it vector recycling? - r

Question

I can write this code that adds two columns to the iris data set. The first added column is a sum of the first four columns. The second added column is my attempt at "programming".
iris.size <- iris %>%
mutate(Total =
apply(.[(1:4)], 1, sum)
) %>%
mutate(Size =
ifelse(
apply(.[(1:4)], 1, sum) != 0 &
.[2] > .[3], "Output1",
ifelse(
apply(.[(1:4)], 1, sum) == 0 &
.[2] > .[3], "Output2",
"Output3")
)
)
You'll notice this code does not throw any errors and it does output what I want it to output. But watch what happens when I try my next step in analysis.
iris.size %>% arrange(Size)
Error: Column Size must be a 1d atomic vector or a list
It must be my ifelse logic. Correct? Ifelse logic seems straightforward. If condition 1 than output1, otherwise if condition 2 than output2, otherwise output3.
I ended up forcing iris.size$Size into a vector using as.vector but I'd like to know where my logic went wrong in the first place so I don't have to resort to using band aids in the future. After some googling it sounds like if statements are preferred over ifelse statements in R, but if statements only seem to work on single logical values, not vectors.

Answer 1

When you run your code, you get this output as iris.size:
Sepal.Length Sepal.Width Petal.Length Petal.Width Species Total Sepal.Width
1 5.1 3.5 1.4 0.2 setosa 10.2 Output1
2 4.9 3.0 1.4 0.2 setosa 9.5 Output1
3 4.7 3.2 1.3 0.2 setosa 9.4 Output1
4 4.6 3.1 1.5 0.2 setosa 9.4 Output1
5 5.0 3.6 1.4 0.2 setosa 10.2 Output1
6 5.4 3.9 1.7 0.4 setosa 11.4 Output1
The reason why it's not displaying Size is because the column Size has not been created. The reason that is occurring is because you're comparing two objects of class data.frame() with .[2] > .[3], not two vectors which would happen with .[, 2] > .[, 3].
I'm still trying to understand what is being created. What is that Sepal.Width column?
Adjust yours with the following:
iris.size <- iris %>% mutate(Total =
apply(.[(1:4)], 1, sum) ) %>% mutate(Size =
ifelse(
apply(.[(1:4)], 1, sum) != 0 &
.[,2] > .[,3], "Output1",
ifelse(
apply(.[(1:4)], 1, sum) == 0 &
.[,2] > .[,3], "Output2",
"Output3")
) )
iris.size
Sepal.Length Sepal.Width Petal.Length Petal.Width Species Total Size
1 5.1 3.5 1.4 0.2 setosa 10.2 Output1
2 4.9 3.0 1.4 0.2 setosa 9.5 Output1
3 4.7 3.2 1.3 0.2 setosa 9.4 Output1
4 4.6 3.1 1.5 0.2 setosa 9.4 Output1
5 5.0 3.6 1.4 0.2 setosa 10.2 Output1
6 5.4 3.9 1.7 0.4 setosa 11.4 Output1
Suggestion:
Here's a condensed version of your code, if you're interested. You can replace Sepal.Width and Sepal.Length with .[,2] and .[,3] if need be.
iris.size <- iris %>%
mutate(Total = rowSums(.[,sapply(., is.numeric)]),
Size = ifelse(Total != 0 & Sepal.Width > Sepal.Length, "Output1",
ifelse(Total == 0 & Sepal.Width > Sepal.Length, "Output2", "Output3")))%>%
arrange(Size)
iris.size
Sepal.Length Sepal.Width Petal.Length Petal.Width Species Total Size
1 5.1 3.5 1.4 0.2 setosa 10.2 Output1
2 4.9 3.0 1.4 0.2 setosa 9.5 Output1
3 4.7 3.2 1.3 0.2 setosa 9.4 Output1
4 4.6 3.1 1.5 0.2 setosa 9.4 Output1
5 5.0 3.6 1.4 0.2 setosa 10.2 Output1
6 5.4 3.9 1.7 0.4 setosa 11.4 Output1

Answer 2

Making use of rowwise and splitting things up a bit for readability...
iris.size <- iris %>%
mutate(Total =
apply(.[(1:4)], 1, sum)
)
iris.size <-iris.size %>% rowwise %>% mutate(Size =
if(
Total != 0 && Sepal.Width > Petal.Length) {
"Output1"
} else {
if(Total == 0 && Petal.Length > Petal.Length){
"Output2"
} else {
"Output3"}}
)
class(iris.size$Size)
[1] "character"
> iris.size %>% arrange(Size)
# A tibble: 150 x 7
Sepal.Length Sepal.Width Petal.Length Petal.Width
<dbl> <dbl> <dbl> <dbl>
1 5.1 3.5 1.4 0.2
2 4.9 3.0 1.4 0.2
3 4.7 3.2 1.3 0.2
4 4.6 3.1 1.5 0.2
5 5.0 3.6 1.4 0.2
6 5.4 3.9 1.7 0.4
7 4.6 3.4 1.4 0.3
8 5.0 3.4 1.5 0.2
9 4.4 2.9 1.4 0.2
10 4.9 3.1 1.5 0.1
# ... with 140 more rows, and 3 more variables:
# Species <fctr>, Total <dbl>, Size <chr>
>

Answer 3

The error message is caused by the fact that iris.size["Size"] is an object of type data.frame(). This can be confirmed by the str() function:
> str(iris.size["Size"])
'data.frame': 150 obs. of 1 variable:
$ Size: chr [1:150, 1] "Output1" "Output1" "Output1" "Output1" ...
..- attr(*, "dimnames")=List of 2
.. ..$ : NULL
.. ..$ : chr "Sepal.Width"
>
Casting the object with as.vector() resolves the problem because the data frame contains 1 column.