在嵌套列表上映射并提取特定列表元素

Question

我有一些数据看起来像：

   price unleveragedData
   <dbl> <list>         
1 450000 <list [5]>     
2 400000 <list [5]>     
3 400000 <list [5]>     
4 397000 <list [5]>     
5 750000 <list [5]>     
6 550000 <list [5]>

我正在尝试将列表的元素

5

放入新列中-即

   price unleveragedData element5
   <dbl> <list>         
1 450000 <list [5]>         -----
2 400000 <list [5]>         -----
3 400000 <list [5]>     
4 397000 <list [5]>     
5 750000 <list [5]>     
6 550000 <list [5]>         -----

使用以下内容：

df$unleveragedData %>% 
  map(., ~ pluck(., c(5)))

我可以得到我想要的输出：

[[1]]
[1] 260551.4

[[2]]
[1] 330786.9

[[3]]
[1] 330786.9

[[4]]
[1] 287739.3

[[5]]
[1] 566416

[[6]]
[1] 271879.7

但是，在

mutate

函数中我无法让它工作。

df %>% 
  mutate(
    element5 = map(unleveragedData, ~ map_dbl(., pluck(., c(5))))
  )

资料：

df = structure(list(price = c(450000, 400000, 400000, 397000, 750000, 
550000), unleveragedData = list(list(-0.0547083151944441, c(-450000, 
15533.28, 16475.2128, 17473.760928, 18532.32229728, 280205.849576444
), "450000-0.08", structure(list(` ` = c("Revenue", "Vacancy", 
"Gross Revenue", "Operating Expenses", "Net Operating Income"
), Year1 = c(16560, 828, 15732, 199, 15533), Year2 = c(17554, 
878, 16676, 201, 16475), Year3 = c(18607, 930, 17676, 203, 17474
), Year4 = c(19723, 986, 18737, 205, 18532), Year5 = c(20907, 
1045, 19861, 207, 19654), Year6 = c(22161, 1108, 21053, 209, 
20844), purchasePriceCapRate = c("450000-0.08", "450000-0.08", 
"450000-0.08", "450000-0.08", "450000-0.08")), row.names = c(NA, 
-5L), class = "data.frame"), 260551.350870592), list(0.0224165566243759, 
    c(-400000, 19720.512, 20916.35712, 22184.0790912, 23527.991786112, 
    355739.600331834), "400000-0.08", structure(list(` ` = c("Revenue", 
    "Vacancy", "Gross Revenue", "Operating Expenses", "Net Operating Income"
    ), Year1 = c(21024, 1051, 19973, 252, 19721), Year2 = c(22285, 
    1114, 21171, 255, 20916), Year3 = c(23623, 1181, 22441, 257, 
    22184), Year4 = c(25040, 1252, 23788, 260, 23528), Year5 = c(26542, 
    1327, 25215, 263, 24953), Year6 = c(28135, 1407, 26728, 265, 
    26463), purchasePriceCapRate = c("400000-0.08", "400000-0.08", 
    "400000-0.08", "400000-0.08", "400000-0.08")), row.names = c(NA, 
    -5L), class = "data.frame"), 330786.932409621), list(0.0224165566243759, 
    c(-400000, 19720.512, 20916.35712, 22184.0790912, 23527.991786112, 
    355739.600331834), "400000-0.08", structure(list(` ` = c("Revenue", 
    "Vacancy", "Gross Revenue", "Operating Expenses", "Net Operating Income"
    ), Year1 = c(21024, 1051, 19973, 252, 19721), Year2 = c(22285, 
    1114, 21171, 255, 20916), Year3 = c(23623, 1181, 22441, 257, 
    22184), Year4 = c(25040, 1252, 23788, 260, 23528), Year5 = c(26542, 
    1327, 25215, 263, 24953), Year6 = c(28135, 1407, 26728, 265, 
    26463), purchasePriceCapRate = c("400000-0.08", "400000-0.08", 
    "400000-0.08", "400000-0.08", "400000-0.08")), row.names = c(NA, 
    -5L), class = "data.frame"), 330786.932409621), list(-0.00700507916565851, 
    c(-397000, 17154.144, 18194.36544, 19297.1098944, 20466.129841344, 
    309444.720836595), "397000-0.08", structure(list(` ` = c("Revenue", 
    "Vacancy", "Gross Revenue", "Operating Expenses", "Net Operating Income"
    ), Year1 = c(18288, 914, 17374, 219, 17154), Year2 = c(19385, 
    969, 18416, 222, 18194), Year3 = c(20548, 1027, 19521, 224, 
    19297), Year4 = c(21781, 1089, 20692, 226, 20466), Year5 = c(23088, 
    1154, 21934, 228, 21705), Year6 = c(24473, 1224, 23250, 231, 
    23019), purchasePriceCapRate = c("397000-0.08", "397000-0.08", 
    "397000-0.08", "397000-0.08", "397000-0.08")), row.names = c(NA, 
    -5L), class = "data.frame"), 287739.317917958), list(0.00205549716813258, 
    c(-750000, 33768, 35815.68, 37986.4368, 40287.657168, 609143.15125314
    ), "750000-0.08", structure(list(` ` = c("Revenue", "Vacancy", 
    "Gross Revenue", "Operating Expenses", "Net Operating Income"
    ), Year1 = c(36000, 1800, 34200, 432, 33768), Year2 = c(38160, 
    1908, 36252, 436, 35816), Year3 = c(40450, 2022, 38427, 441, 
    37986), Year4 = c(42877, 2144, 40733, 445, 40288), Year5 = c(45449, 
    2272, 43177, 450, 42727), Year6 = c(48176, 2409, 45767, 454, 
    45313), purchasePriceCapRate = c("750000-0.08", "750000-0.08", 
    "750000-0.08", "750000-0.08", "750000-0.08")), row.names = c(NA, 
    -5L), class = "data.frame"), 566415.98015346), list(-0.0866171399087425, 
    c(-550000, 16208.64, 17191.5264, 18233.489664, 19338.07544064, 
    292388.712601507), "550000-0.08", structure(list(` ` = c("Revenue", 
    "Vacancy", "Gross Revenue", "Operating Expenses", "Net Operating Income"
    ), Year1 = c(17280, 864, 16416, 207, 16209), Year2 = c(18317, 
    916, 17401, 209, 17192), Year3 = c(19416, 971, 18445, 212, 
    18233), Year4 = c(20581, 1029, 19552, 214, 19338), Year5 = c(21816, 
    1091, 20725, 216, 20509), Year6 = c(23125, 1156, 21968, 218, 
    21750), purchasePriceCapRate = c("550000-0.08", "550000-0.08", 
    "550000-0.08", "550000-0.08", "550000-0.08")), row.names = c(NA, 
    -5L), class = "data.frame"), 271879.670473661))), class = c("rowwise_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -6L), groups = structure(list(
    .rows = structure(list(1L, 2L, 3L, 4L, 5L, 6L), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), row.names = c(NA, -6L), class = c("tbl_df", 
"tbl", "data.frame")))