对多个列表中的多个变量进行统计测试（小标题）答案

【问题标题】：Statistical test on multiple variables on multiple lists (tibble)对多个列表中的多个变量进行统计测试（小标题）
【发布时间】：2021-11-11 14:04:22
【问题描述】：

为了简化我的数据分析，我需要针对不同的变量和不同的数据组处理不同的统计测试（在该示例中为 shapiro 测试）。目的是不要编写 150 次相同的代码。为此，我从我的数据集中创建了一个 tibble，其中每个列表对应于一组数据。

数据集：

dput(head(PdataLaKo,25)) 
structure(list(ctd_file = c("2018-08-02T162038 SBE0251090", "2018-08-02T162038 SBE0251090", 
"2018-08-02T162038 SBE0251090", "2018-08-02T162038 SBE0251090", 
"2018-08-02T162038 SBE0251090", "2018-08-02T162038 SBE0251090", 
"2018-08-02T162038 SBE0251090", "2018-08-02T162038 SBE0251090", 
"2018-08-02T162038 SBE0251090", "2018-08-02T162038 SBE0251090", 
"2018-08-02T175518 SBE0251090", "2018-08-02T175518 SBE0251090", 
"2018-08-02T175518 SBE0251090", "2018-08-02T175518 SBE0251090", 
"2018-08-02T175518 SBE0251090", "2018-08-02T175518 SBE0251090", 
"2018-08-02T175518 SBE0251090", "2018-08-02T175518 SBE0251090", 
"2018-08-02T175518 SBE0251090", "2018-08-02T175518 SBE0251090", 
"2018-08-03T090018 SBE0251090", "2018-08-03T090018 SBE0251090", 
"2018-08-03T090018 SBE0251090", "2018-08-03T090018 SBE0251090", 
"2018-08-03T090018 SBE0251090"), station = c("1", "1", "1", "1", 
"1", "1", "1", "1", "1", "1", "2", "2", "2", "2", "2", "2", "2", 
"2", "2", "2", "3", "3", "3", "3", "3"), month = c(8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L), day = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 
3L, 3L), year = c(2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 
2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 
2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L
), time = c(16.38, 16.38, 16.38, 16.38, 16.38, 16.38, 16.38, 
16.38, 16.38, 16.38, 17.57, 17.57, 17.57, 17.57, 17.57, 17.57, 
17.57, 17.57, 17.57, 17.57, 9.05, 9.05, 9.05, 9.05, 9.05), LAT = c("69.27166667", 
"69.27166667", "69.27166667", "69.27166667", "69.27166667", "69.27166667", 
"69.27166667", "69.27166667", "69.27166667", "69.27166667", "69.25386667", 
"69.25386667", "69.25386667", "69.25386667", "69.25386667", "69.25386667", 
"69.25386667", "69.25386667", "69.25386667", "69.25386667", "69.23883333", 
"69.23883333", "69.23883333", "69.23883333", "69.23883333"), 
    LONG = c("-25.15166667", "-25.15166667", "-25.15166667", 
    "-25.15166667", "-25.15166667", "-25.15166667", "-25.15166667", 
    "-25.15166667", "-25.15166667", "-25.15166667", "-25.0637", 
    "-25.0637", "-25.0637", "-25.0637", "-25.0637", "-25.0637", 
    "-25.0637", "-25.0637", "-25.0637", "-25.0637", "-24.9915", 
    "-24.9915", "-24.9915", "-24.9915", "-24.9915"), bottom_depth = c("226", 
    "226", "226", "226", "226", "226", "226", "226", "226", "226", 
    "229", "229", "229", "229", "229", "229", "229", "229", "229", 
    "229", "255", "255", "255", "255", "255"), timeS = c(223.5, 
    227.236, 228.558, 228.916, 229.336, 229.749, 230.119, 230.49, 
    228.871, 231.587, 242.497, 241.334, 241.591, 241.869, 242.205, 
    242.601, 249.68, 249.758, 250.013, 250.3, 266.6, 267.148, 
    267.57, 267.899, 268.245), pressure = c(0.607, 0.707, 0.808, 
    0.909, 1.01, 1.112, 1.212, 1.313, 1.516, 1.616, 0.503, 0.101, 
    0.202, 0.303, 0.404, 0.505, 0.606, 0.707, 0.808, 0.909, 0.303, 
    0.404, 0.505, 0.606, 0.707), depth = c(0.6, 0.7, 0.8, 0.9, 
    1, 1.1, 1.2, 1.3, 1.5, 1.6, 0.5, 0.1, 0.2, 0.3, 0.4, 0.5, 
    0.6, 0.7, 0.8, 0.9, 0.3, 0.4, 0.5, 0.6, 0.7), salinity = c(30.195, 
    30.1989, 30.199, 30.1737, 30.1894, 30.1824, 30.1546, 30.2275, 
    29.9942, 30.2885, 28.2285, 28.1332, 28.2182, 28.3279, 28.3815, 
    28.4242, 29.0786, 29.1525, 29.2647, 29.3672, 32.484, 32.3028, 
    31.885, 31.3775, 30.978), temperature = c(2.6459, 2.6477, 
    2.6263, 2.5913, 2.6188, 2.608, 2.6106, 2.6746, 2.6973, 2.6837, 
    1.9945, 2.0299, 1.9315, 1.7799, 1.734, 1.7082, 1.9263, 1.928, 
    1.9184, 1.8562, 1.1441, 1.073, 1.052, 1.0518, 1.0603), oxygen = c(352.891, 
    352.339, 352.12, 352.03, 351.884, 351.702, 351.505, 351.296, 
    347.288, 351.001, 345.827, 345.879, 345.866, 345.841, 345.782, 
    345.65, 346.849, 346.78, 346.718, 346.609, 340.888, 340.026, 
    339.348, 338.819, 338.245), oxygen2 = c(102.182, 102.228, 
    102.257, 102.281, 102.313, 102.347, 102.383, 102.427, 101.491, 
    102.644, 97.258, 97.311, 97.301, 97.29, 97.275, 97.253, 98.285, 
    98.293, 98.325, 98.357, 97.857, 97.839, 97.829, 97.812, 97.788
    ), fluorescence = c(0.17892, 0.17232, 0.17139, 0.17278, 0.17479, 
    0.17701, 0.1792, 0.18158, 0.18525, 0.18909, 0.10588, 0.10647, 
    0.10697, 0.10818, 0.10978, 0.11157, 0.1479, 0.14969, 0.15256, 
    0.15607, 0.30833, 0.31088, 0.31321, 0.31532, 0.31758), turbidity = c(0.164, 
    0.164, 0.164, 0.164, 0.163, 0.163, 0.163, 0.163, 0.161, 0.163, 
    0.165, 0.165, 0.165, 0.165, 0.165, 0.164, 0.159, 0.16, 0.16, 
    0.16, 4.742, 4.747, 4.751, 4.753, 4.755), conductivity = c(2.742475, 
    2.743057, 2.74087, 2.73591, 2.740138, 2.738197, 2.736985, 
    2.747572, 2.72913, 2.752912, 2.524555, 2.525942, 2.524426, 
    2.523692, 2.525012, 2.526692, 2.596153, 2.602249, 2.609861, 
    2.613963, 2.806078, 2.786396, 2.752134, 2.712379, 2.682113
    ), pH = c(8.094, 8.098, 8.099, 8.099, 8.099, 8.099, 8.099, 
    8.099, 8.014, 8.099, 8.16, 8.16, 8.16, 8.16, 8.159, 8.159, 
    8.149, 8.148, 8.147, 8.146, 8.121, 8.12, 8.12, 8.119, 8.118
    ), par = c(2627.7, 2627.7, 2627.7, 2627.7, 2627.7, 2627.7, 
    2627.7, 2627.7, 2600, 2627.7, 2627.8, 2627.8, 2627.8, 2627.8, 
    2627.8, 2627.8, 2627.8, 2627.8, 2627.8, 2627.8, 2627.6, NA, 
    2627.6, 2627.6, 2627.6), soundSpeed = c(1454.65, 1454.65, 
    1454.57, 1454.38, 1454.53, 1454.47, 1454.45, 1454.82, 1439.8, 
    1454.96, 1449.08, 1449.22, 1448.88, 1448.36, 1448.23, 1448.18, 
    1449.98, 1450.1, 1450.19, 1450.08, 1450.99, 1450.48, 1449.83, 
    1449.19, 1448.69), svDM = c(1454.55, 1454.55, 1454.48, 1454.29, 
    1454.43, 1454.37, 1454.35, 1454.72, 1439.71, 1454.86, 1448.98, 
    1449.12, 1448.78, 1448.26, 1448.14, 1448.08, 1449.89, 1450.01, 
    1450.1, 1449.98, 1450.91, 1450.4, 1449.76, 1449.12, 1448.61
    ), svWM = c(1454.57, 1454.57, 1454.49, 1454.3, 1454.45, 1454.39, 
    1454.37, 1454.74, 1439.73, 1454.89, 1448.89, 1449.03, 1448.69, 
    1448.18, 1448.05, 1448, 1449.84, 1449.96, 1450.05, 1449.94, 
      1451.01, 1450.49, 1449.83, 1449.16, 1448.62)), row.names = c(NA, 
    25L), class = "data.frame")

#to correspond to the number of observations, the rows are duplicated

    PdataLaKo <- as.data.frame(lapply(PdataLaKo, rep, 250))

为此，我使用了dplyr 包中的函数group_split，它创建了一个对应于每个组（ctd_file）的不同列表的小标题。在我尝试将 shapiro.test 从包 rstatix 应用到具有 sapply 的组的每个选定变量以及具有 lapply 的每个组之后。

PdataLaKo <- PdataLaKo %>%
  group_split(ctd_file)
lnorm <- PdataLaKo[, c(11:24)] %>% 
  map(~ lapply(., sapply(., shapiro.test)))

如果我使用过滤器提取一组并且不创建小标题，则应用于每个变量的sapply 函数有效。因此，问题来自 tibble，而不是应用到所选列。

#non-grouped data
PdataLaKot <- PdataLaKo %>% filter(ctd_file == "2018-08-05T092503 SBE0251090")    
lnorm <- PdataLaKot[, c(11:24)] %>% sapply(shapiro.test)

【问题讨论】：

标签： r dplyr tibble rstatix

【解决方案1】：

library(tidyverse)

shapiro_test_safely <- possibly(.f = shapiro.test, otherwise = NA)

a <- df %>%
  group_nest(ctd_file) %>% 
  mutate(
    data = map(data, ~select(.x, where(is.numeric))[, -c(1:4)]),
    res = map(data, ~map(.x, shapiro_test_safely)),
    res = purrr::set_names(res, nm = ctd_file))

fltr <- map(a$res, ~!is.na(.x))

b <- map2(.x = a$res, .y = fltr,  ~.x[.y])

map_df(b, ~map_df(.x, broom::glance)) %>% 
  mutate(nm = map(b, names) %>% unlist()) %>% 
  mutate(SET = rep(names(b), sapply(b, length))) 

#> # A tibble: 43 x 5
#>    statistic p.value method                      nm           SET               
#>        <dbl>   <dbl> <chr>                       <chr>        <chr>             
#>  1     0.862 0.0807  Shapiro-Wilk normality test timeS        2018-08-02T162038~
#>  2     0.969 0.879   Shapiro-Wilk normality test pressure     2018-08-02T162038~
#>  3     0.969 0.882   Shapiro-Wilk normality test depth        2018-08-02T162038~
#>  4     0.800 0.0144  Shapiro-Wilk normality test salinity     2018-08-02T162038~
#>  5     0.946 0.625   Shapiro-Wilk normality test temperature  2018-08-02T162038~
#>  6     0.711 0.00119 Shapiro-Wilk normality test oxygen       2018-08-02T162038~
#>  7     0.776 0.00738 Shapiro-Wilk normality test oxygen2      2018-08-02T162038~
#>  8     0.939 0.543   Shapiro-Wilk normality test fluorescence 2018-08-02T162038~
#>  9     0.750 0.00356 Shapiro-Wilk normality test turbidity    2018-08-02T162038~
#> 10     0.978 0.954   Shapiro-Wilk normality test conductivity 2018-08-02T162038~
#> # ... with 33 more rows

^{由reprex package (v2.0.1) 于 2021-09-16 创建}

数据

df <-
  structure(
    list(
      ctd_file = c(
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T162038 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-02T175518 SBE0251090",
        "2018-08-03T090018 SBE0251090",
        "2018-08-03T090018 SBE0251090",
        "2018-08-03T090018 SBE0251090",
        "2018-08-03T090018 SBE0251090",
        "2018-08-03T090018 SBE0251090"
      ),
      station = c(
        "1",
        "1",
        "1",
        "1",
        "1",
        "1",
        "1",
        "1",
        "1",
        "1",
        "2",
        "2",
        "2",
        "2",
        "2",
        "2",
        "2",
        "2",
        "2",
        "2",
        "3",
        "3",
        "3",
        "3",
        "3"
      ),
      month = c(
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L,
        8L
      ),
      day = c(
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        2L,
        3L,
        3L,
        3L,
        3L,
        3L
      ),
      year = c(
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L,
        2018L
      ),
      time = c(
        16.38,
        16.38,
        16.38,
        16.38,
        16.38,
        16.38,
        16.38,
        16.38,
        16.38,
        16.38,
        17.57,
        17.57,
        17.57,
        17.57,
        17.57,
        17.57,
        17.57,
        17.57,
        17.57,
        17.57,
        9.05,
        9.05,
        9.05,
        9.05,
        9.05
      ),
      LAT = c(
        "69.27166667",
        "69.27166667",
        "69.27166667",
        "69.27166667",
        "69.27166667",
        "69.27166667",
        "69.27166667",
        "69.27166667",
        "69.27166667",
        "69.27166667",
        "69.25386667",
        "69.25386667",
        "69.25386667",
        "69.25386667",
        "69.25386667",
        "69.25386667",
        "69.25386667",
        "69.25386667",
        "69.25386667",
        "69.25386667",
        "69.23883333",
        "69.23883333",
        "69.23883333",
        "69.23883333",
        "69.23883333"
      ),
      LONG = c(
        "-25.15166667",
        "-25.15166667",
        "-25.15166667",
        "-25.15166667",
        "-25.15166667",
        "-25.15166667",
        "-25.15166667",
        "-25.15166667",
        "-25.15166667",
        "-25.15166667",
        "-25.0637",
        "-25.0637",
        "-25.0637",
        "-25.0637",
        "-25.0637",
        "-25.0637",
        "-25.0637",
        "-25.0637",
        "-25.0637",
        "-25.0637",
        "-24.9915",
        "-24.9915",
        "-24.9915",
        "-24.9915",
        "-24.9915"
      ),
      bottom_depth = c(
        "226",
        "226",
        "226",
        "226",
        "226",
        "226",
        "226",
        "226",
        "226",
        "226",
        "229",
        "229",
        "229",
        "229",
        "229",
        "229",
        "229",
        "229",
        "229",
        "229",
        "255",
        "255",
        "255",
        "255",
        "255"
      ),
      timeS = c(
        223.5,
        227.236,
        228.558,
        228.916,
        229.336,
        229.749,
        230.119,
        230.49,
        228.871,
        231.587,
        242.497,
        241.334,
        241.591,
        241.869,
        242.205,
        242.601,
        249.68,
        249.758,
        250.013,
        250.3,
        266.6,
        267.148,
        267.57,
        267.899,
        268.245
      ),
      pressure = c(
        0.607,
        0.707,
        0.808,
        0.909,
        1.01,
        1.112,
        1.212,
        1.313,
        1.516,
        1.616,
        0.503,
        0.101,
        0.202,
        0.303,
        0.404,
        0.505,
        0.606,
        0.707,
        0.808,
        0.909,
        0.303,
        0.404,
        0.505,
        0.606,
        0.707
      ),
      depth = c(
        0.6,
        0.7,
        0.8,
        0.9,
        1,
        1.1,
        1.2,
        1.3,
        1.5,
        1.6,
        0.5,
        0.1,
        0.2,
        0.3,
        0.4,
        0.5,
        0.6,
        0.7,
        0.8,
        0.9,
        0.3,
        0.4,
        0.5,
        0.6,
        0.7
      ),
      salinity = c(
        30.195,
        30.1989,
        30.199,
        30.1737,
        30.1894,
        30.1824,
        30.1546,
        30.2275,
        29.9942,
        30.2885,
        28.2285,
        28.1332,
        28.2182,
        28.3279,
        28.3815,
        28.4242,
        29.0786,
        29.1525,
        29.2647,
        29.3672,
        32.484,
        32.3028,
        31.885,
        31.3775,
        30.978
      ),
      temperature = c(
        2.6459,
        2.6477,
        2.6263,
        2.5913,
        2.6188,
        2.608,
        2.6106,
        2.6746,
        2.6973,
        2.6837,
        1.9945,
        2.0299,
        1.9315,
        1.7799,
        1.734,
        1.7082,
        1.9263,
        1.928,
        1.9184,
        1.8562,
        1.1441,
        1.073,
        1.052,
        1.0518,
        1.0603
      ),
      oxygen = c(
        352.891,
        352.339,
        352.12,
        352.03,
        351.884,
        351.702,
        351.505,
        351.296,
        347.288,
        351.001,
        345.827,
        345.879,
        345.866,
        345.841,
        345.782,
        345.65,
        346.849,
        346.78,
        346.718,
        346.609,
        340.888,
        340.026,
        339.348,
        338.819,
        338.245
      ),
      oxygen2 = c(
        102.182,
        102.228,
        102.257,
        102.281,
        102.313,
        102.347,
        102.383,
        102.427,
        101.491,
        102.644,
        97.258,
        97.311,
        97.301,
        97.29,
        97.275,
        97.253,
        98.285,
        98.293,
        98.325,
        98.357,
        97.857,
        97.839,
        97.829,
        97.812,
        97.788
      ),
      fluorescence = c(
        0.17892,
        0.17232,
        0.17139,
        0.17278,
        0.17479,
        0.17701,
        0.1792,
        0.18158,
        0.18525,
        0.18909,
        0.10588,
        0.10647,
        0.10697,
        0.10818,
        0.10978,
        0.11157,
        0.1479,
        0.14969,
        0.15256,
        0.15607,
        0.30833,
        0.31088,
        0.31321,
        0.31532,
        0.31758
      ),
      turbidity = c(
        0.164,
        0.164,
        0.164,
        0.164,
        0.163,
        0.163,
        0.163,
        0.163,
        0.161,
        0.163,
        0.165,
        0.165,
        0.165,
        0.165,
        0.165,
        0.164,
        0.159,
        0.16,
        0.16,
        0.16,
        4.742,
        4.747,
        4.751,
        4.753,
        4.755
      ),
      conductivity = c(
        2.742475,
        2.743057,
        2.74087,
        2.73591,
        2.740138,
        2.738197,
        2.736985,
        2.747572,
        2.72913,
        2.752912,
        2.524555,
        2.525942,
        2.524426,
        2.523692,
        2.525012,
        2.526692,
        2.596153,
        2.602249,
        2.609861,
        2.613963,
        2.806078,
        2.786396,
        2.752134,
        2.712379,
        2.682113
      ),
      pH = c(
        8.094,
        8.098,
        8.099,
        8.099,
        8.099,
        8.099,
        8.099,
        8.099,
        8.014,
        8.099,
        8.16,
        8.16,
        8.16,
        8.16,
        8.159,
        8.159,
        8.149,
        8.148,
        8.147,
        8.146,
        8.121,
        8.12,
        8.12,
        8.119,
        8.118
      ),
      par = c(
        2627.7,
        2627.7,
        2627.7,
        2627.7,
        2627.7,
        2627.7,
        2627.7,
        2627.7,
        2600,
        2627.7,
        2627.8,
        2627.8,
        2627.8,
        2627.8,
        2627.8,
        2627.8,
        2627.8,
        2627.8,
        2627.8,
        2627.8,
        2627.6,
        NA,
        2627.6,
        2627.6,
        2627.6
      ),
      soundSpeed = c(
        1454.65,
        1454.65,
        1454.57,
        1454.38,
        1454.53,
        1454.47,
        1454.45,
        1454.82,
        1439.8,
        1454.96,
        1449.08,
        1449.22,
        1448.88,
        1448.36,
        1448.23,
        1448.18,
        1449.98,
        1450.1,
        1450.19,
        1450.08,
        1450.99,
        1450.48,
        1449.83,
        1449.19,
        1448.69
      ),
      svDM = c(
        1454.55,
        1454.55,
        1454.48,
        1454.29,
        1454.43,
        1454.37,
        1454.35,
        1454.72,
        1439.71,
        1454.86,
        1448.98,
        1449.12,
        1448.78,
        1448.26,
        1448.14,
        1448.08,
        1449.89,
        1450.01,
        1450.1,
        1449.98,
        1450.91,
        1450.4,
        1449.76,
        1449.12,
        1448.61
      ),
      svWM = c(
        1454.57,
        1454.57,
        1454.49,
        1454.3,
        1454.45,
        1454.39,
        1454.37,
        1454.74,
        1439.73,
        1454.89,
        1448.89,
        1449.03,
        1448.69,
        1448.18,
        1448.05,
        1448,
        1449.84,
        1449.96,
        1450.05,
        1449.94,
        1451.01,
        1450.49,
        1449.83,
        1449.16,
        1448.62
      )
    ),
    row.names = c(NA,
                  25L),
    class = "data.frame"
  )

【讨论】：

非常有趣的答案，效果很好。此外，对您的代码的另一个兴趣是它会自动避免非数字变量。
太棒了！如果您认为此答案对您有帮助，您可以通过单击此答案左侧的勾号来接受它:)

【解决方案2】：

通常你可以这样做：

library(dplyr)
library(rstatix)

PdataLaKo %>% 
  group_by(ctd_file) %>% 
  summarize(across(pressure:svWM, ~ list(shapiro_test(.))),
            .groups = "drop")

但是，在您的代码中，您使用的是shaprio.test，它来自R，而不是rstatix 库中的shapiro_test。

此外，在您提供的示例中，此代码会出错，因为某些组的某些列的数据没有任何变化。排除这些列，输出将如下所示：


lnorm <- PdataLaKo %>% 
  group_by(ctd_file) %>% 
  summarize(across(pressure:pH, ~ list(shapiro_test(.))), # range only up to pH
            .groups = "drop")

lnorm
# A tibble: 3 x 11
  ctd_file   pressure  depth  salinity temperature oxygen oxygen2 fluorescence
  <chr>      <list>    <list> <list>   <list>      <list> <list>  <list>      
1 2018-08-0~ <tibble ~ <tibb~ <tibble~ <tibble [1~ <tibb~ <tibbl~ <tibble [1 ~
2 2018-08-0~ <tibble ~ <tibb~ <tibble~ <tibble [1~ <tibb~ <tibbl~ <tibble [1 ~
3 2018-08-0~ <tibble ~ <tibb~ <tibble~ <tibble [1~ <tibb~ <tibbl~ <tibble [1 ~
# ... with 3 more variables: turbidity <list>, conductivity <list>, pH <list>

请注意，输出是一堆列表列，每个列表都包含测试结果的小标题。然后，您可以通过多种方式访问特定的组和列（下面使用行索引和列名）：

lnorm[1, "pressure", drop = T][[1]]
# A tibble: 1 x 3
  variable statistic  p.value
  <chr>        <dbl>    <dbl>
1 pressure     0.934 5.66e-32

【讨论】：

感谢@LMc 提供我的数据集，我还必须过滤一个空的 ctd_file，并且我的几个组包含很多观察。然后我添加了这段代码。 PdataLaKo <- PdataLaKo %>% filter(ctd_file != "") %>% group_by(ctd_file) %>% filter(row_number() %in% 1:4999) 但我真的很喜欢你代码的简洁性。