dplyr突变case_when产生NA

Question

我在mutate()中使用了case_when()，并获得了预期的输出，但我也收到了有关生成NA的警告。不过，我不知道为什么。据我所知，RHS无论如何都应该是同一类型的。我已经将我的所有RHS条件包装在一个as.double()调用中，以确保它们属于同一类型，但这没有什么区别。这些警告意味着我的默认条件是创建NAs的原因。

依赖关系

我使用library(mc2d)来获取下面使用的rpert()函数。

源数据

> 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

我的代码

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))
  )

警告

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

？奇怪

和其他人一样，我不能重现错误。但是(我不知道函数)我得不到869414.4的答案

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