dplyr 变异 case_when 产生 NA

Question

I'm using case_when() in a mutate() and I'm getting the expected output, but I'm also getting warnings about producing NA. I can't figure out why, though. From what I can tell, the RHS should be of the same type no matter what. I've wrapped all my RHS conditions in a as.double() call to make sure they are of the same type, but it doesn't make a difference. The warnings imply that my default condition is what is creating the NAs.

dependencies

I'm using library(mc2d) to get the rpert() function used below.

source data

> simulationTable %>% select(count, Productivity_Low__c, Productivity_ML__c, Productivity_High__c)
# A tibble: 20 x 4
# Rowwise: 
   count Productivity_Low__c Productivity_ML__c Productivity_High__c
   <int>               <dbl>              <dbl>                <dbl>
 1     2                   0                  0                    0
 2     2                   0                  0                    0
 3     0                   0                  0                    0
 4     2                   0                  0                    0
 5     6                   0                  0                    0
 6     1                   0                  0                    0
 7     0                   0                  0                    0
 8     0                   0                  0                    0
 9     0                   0                  0                    0
10     0                   0                  0                    0
11     0                   0                  0                    0
12     0                   0                  0                    0
13     0                   0                  0                    0
14     0                   0                  0                    0
15     1                   0                  0                    0
16     0               10000              75000               500000
17     0               10000              75000               500000
18     1               10000              75000               500000
19     0               10000              75000               500000
20     0               10000              75000               500000

my code

simulationTable <- simulationTable %>%
  mutate(
    productivity = case_when(count>0 & Productivity_High__c>0 ~ as.double(sum(rpert(count, Productivity_Low__c, Productivity_ML__c, Productivity_High__c))),
                             TRUE ~ as.double(0))
  )

the warnings

Problem with `mutate()` input `productivity`.
ℹ NAs produced
ℹ Input `productivity` is `case_when(...)`.
ℹ The error occurred in row 1.NAs producedProblem with `mutate()` input `productivity`.
ℹ NAs produced
ℹ Input `productivity` is `case_when(...)`.
ℹ The error occurred in row 2.NAs producedProblem with `mutate()` input `productivity`.
ℹ NAs produced
ℹ Input `productivity` is `case_when(...)`.
ℹ The error occurred in row 4.NAs producedProblem with `mutate()` input `productivity`.
ℹ NAs produced
ℹ Input `productivity` is `case_when(...)`.
ℹ The error occurred in row 5.NAs producedProblem with `mutate()` input `productivity`.
ℹ NAs produced
ℹ Input `productivity` is `case_when(...)`.
ℹ The error occurred in row 6.NAs producedProblem with `mutate()` input `productivity`.
ℹ NAs produced
ℹ Input `productivity` is `case_when(...)`.
ℹ The error occurred in row 15.NAs produced

Answer 1

? Odd

As with others I cant reproduce the errors. BUT (I don't know the function) I don't get 869414.4 as an answer from

require(mc2d)
a <- as.integer(1)
b <- as.double(0)
c <- as.double(10000)
d <- as.double(75000)
e <- as.double(500000)
as.double(sum(rpert(a, c, d, e)))
[1] 156468.2