在c(…)中使用pmap第2部分

Question

最近我一直在探索使用pmap函数及其变体的各种应用，我特别感兴趣的是使用c(...)将所有参数传递到。下面的数据集属于我们今天早些时候与多位非常有知识的用户讨论的另一个问题。我们应该根据days列中的值沿着它们各自的行重复weight列中的值，以获得以下输出：

df <- tribble(
  ~Name,    ~School,   ~Weight, ~Days,
  "Antoine", "Bach",     0.03,   5,
  "Antoine", "Ken",      0.02,   7,
  "Barbara", "Franklin", 0.04,   3
)

输出：

df %>%
  mutate(map2_dfr(Weight, Days, ~ set_names(rep(.x, .y), 1:.y))) %>%
  select(-c(Weight, Days))

# A tibble: 3 x 9
  Name    School     `1`   `2`   `3`   `4`   `5`   `6`   `7`
  <chr>   <chr>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Antoine Bach      0.03  0.03  0.03  0.03  0.03 NA    NA   
2 Antoine Ken       0.02  0.02  0.02  0.02  0.02  0.02  0.02
3 Barbara Franklin  0.04  0.04  0.04 NA    NA    NA    NA 

# This is not my code and it works:

pmap_dfr(df, function(Weight, Days, ...) c(..., setNames(rep(Weight, Days), 1:Days)))

# And I can also rewrite it in the following way which also works:

df %>%
  mutate(data = pmap(list(Weight, Days), ~ setNames(rep(.x, .y), 1:.y))) %>%
  unnest_wider(data)

df %>% 
  mutate(pmap_dfr(., ~ c(..., setNames(rep(Weight, Days), 1:Days))))


df %>% 
  pmap_dfr(., ~ c(..., setNames(rep(Weight, Days), 1:Days)))

非常感谢您的提前和非常抱歉的冗长的描述。

Answer 1

问题似乎是将自定义匿名/lambda函数(函数（Weight,Days,...)-其中参数的名称与列名相同）与默认lambda函数(~-其中参数为.x,.y（如果只有两个元素或如果超过两个元素）-..1,..2,..3等）混合在一起。在行动的代码中

library(dplyr)
library(purrr)
df %>% 
   mutate(pmap_dfr(., ~ c(..., setNames(rep(Weight, Days), 1:Days))))

“weight”和“days”返回原始数据集中的完整列值，而不是从行返回。如果我们希望仍然使用上述命令，则需要将每一行中捕获的数据转换为tibble并将与一起使用

df %>%
     pmap_dfr(., ~ with(as_tibble(list(...)), 
             setNames(rep(Weight, Days), seq_len(Days))))
# A tibble: 3 x 7
#     `1`   `2`   `3`   `4`   `5`   `6`   `7`
#   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#1  0.03  0.03  0.03  0.03  0.03 NA    NA   
#2  0.02  0.02  0.02  0.02  0.02  0.02  0.02
#3  0.04  0.04  0.04 NA    NA    NA    NA   

如果我们想要其他列,

df %>%
     pmap_dfr(., ~ c(list(...)[-(3:4)], with(as_tibble(list(...)), 
             setNames(rep(Weight, Days), seq_len(Days)))))
# A tibble: 3 x 9
#  Name    School     `1`   `2`   `3`   `4`   `5`   `6`   `7`
#  <chr>   <chr>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#1 Antoine Bach      0.03  0.03  0.03  0.03  0.03 NA    NA   
#2 Antoine Ken       0.02  0.02  0.02  0.02  0.02  0.02  0.02
#3 Barbara Franklin  0.04  0.04  0.04 NA    NA    NA    NA   

或使用行式

library(tidyr)
df %>% 
    rowwise %>% 
    mutate(out = list(setNames(rep(Weight, Days), seq_len(Days)))) %>%
    ungroup %>%
    unnest_wider(c(out))  %>%
    select(-Weight, -Days)
# A tibble: 3 x 9
#  Name    School     `1`   `2`   `3`   `4`   `5`   `6`   `7`
#  <chr>   <chr>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#1 Antoine Bach      0.03  0.03  0.03  0.03  0.03 NA    NA   
#2 Antoine Ken       0.02  0.02  0.02  0.02  0.02  0.02  0.02
#3 Barbara Franklin  0.04  0.04  0.04 NA    NA    NA    NA