使用宽格式与长格式的摘要-解网

问：

我有一个格式如下的数据帧。状态有两个级别（PRE、POST）。

SI_mean	TU_mean	ED_mean	MT_mean	DT_mean	SK_mean	ATT_mean	地位
2.6	2.75	2.6	2.8	3.4	2.5	3.8	前
3	3	2.4	2.4	3	3	4	前
2.4	2.75	2.4	2.2	2.6	2.25	2.8	前

我想使用 wilcox.test 比较每列的状态级别值。于是我立刻试了一下，

df |>
  summarise(across(contains("mean"),~wilcox.test(.x~Status)$p.value))

但我受到的欢迎是

Error in `summarise()`:
ℹ In argument: `across(contains("mean"), ~wilcox.test(.x ~ Status)$p.value)`.
ℹ In row 1.
Caused by error in `across()`:
! Can't compute column `SI_mean`.
Caused by error in `wilcox.test.formula()`:
! grouping factor must have exactly 2 levels

所以我改用长格式，它按预期工作，

df |> pivot_longer(contains("mean"),names_to = "Variable",values_to = "Mean") |>
  group_by(Variable) |>
  summarise(
    wilcox_p_value = wilcox.test(Mean~Status)$p.value
    )

但为什么宽幅版面失败了呢？summarise

我只是对我在功能上误解的地方以及我将如何让它在宽格式上工作感兴趣。summarise

数据

df=structure(list(SI_mean = c(2.6, 3, 2.4, 3, 3, 3.2, 2.2, 4, 3.8, 
2.8, 3.6, 2, 3.6, 3.6, 3.8, 3.2, 3, 4, 4, 3, 3.2, 4, 4, 3.2, 
3.2, 3, 3.2, 3.8, 4, 4, 4, 3), TU_mean = c(2.75, 3, 2.75, 3, 
3, 2.75, 3, 3.5, 3.75, 2.5, 3.25, 2, 3.5, 4, 3, 3.25, 3, 4, 4, 
3, 4, 4, 4, 3.25, 3.25, 3, 3, 3.25, 4, 4, 4, 3), ED_mean = c(2.6, 
2.4, 2.4, 3, 2.8, 4, 2, 3.8, 2.6, 2, 2.8, 2, 3, 3.4, 3, 1, 3, 
4, 3.8, 3, 3, 4, 4, 3.2, 4, 2.6, 4, 4, 3.8, 3.6, 4, 3), MT_mean = c(2.8, 
2.4, 2.2, 3, 2.8, 3.4, 2.2, 3.6, 3.4, 3, 2.6, 1.8, 3.4, 3, 4, 
2, 3, 3.4, 3.4, 3, 4, 4, 4, 3.2, 4, 2.8, 4, 4, 3.8, 3.6, 4, 3
), DT_mean = c(3.4, 3, 2.6, 3, 3, 3.8, 2.4, 3.6, 3, 3, 2.8, 2.4, 
3.6, 3.6, 3, 2.2, 3, 4, 4, 4, 3.6, 4, 4, 3.6, 3.8, 2.8, 4, 4, 
4, 3.8, 4, 3), SK_mean = c(2.5, 3, 2.25, 3, 3, 3.5, 2.25, 4, 
3.25, 2.25, 2.5, 2.5, 3.75, 3.75, 4, 1, 2, 4, 3.25, 3, 3.75, 
4, 4, 2.75, 4, 3, 4, 4, 4, 4, 4, 3), ATT_mean = c(3.8, 4, 2.8, 
3, 3, 3.8, 3, 3.6, 3, 4, 4, 3, 3.8, 3.6, 4, 3.8, 4, 4, 4, 4, 
4, 4, 4, 3.6, 3.8, 3, 4, 4, 4, 4, 4, 4), Status = c("PRE", "PRE", 
"PRE", "PRE", "PRE", "PRE", "PRE", "PRE", "PRE", "PRE", "PRE", 
"PRE", "PRE", "PRE", "PRE", "PRE", "PRE", "POST", "POST", "POST", 
"POST", "POST", "POST", "POST", "POST", "POST", "POST", "POST", 
"POST", "POST", "POST", "POST")), class = c("rowwise_df", "tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -32L), groups = structure(list(
    .rows = structure(list(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
        10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
        21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 
        32L), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), row.names = c(NA, -32L), class = c("tbl_df", 
"tbl", "data.frame")))

r tidyr 汇总宽格式数据

suppressPackageStartupMessages(
  library(dplyr)
)

df %>% print(n = 1L)
#> # A tibble: 32 × 8
#> # Rowwise: 
#>   SI_mean TU_mean ED_mean MT_mean DT_mean SK_mean ATT_mean Status
#>     <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>    <dbl> <chr> 
#> 1     2.6    2.75     2.6     2.8     3.4     2.5      3.8 PRE   
#> # ℹ 31 more rows

attributes(df)
#> $names
#> [1] "SI_mean"  "TU_mean"  "ED_mean"  "MT_mean"  "DT_mean"  "SK_mean"  "ATT_mean"
#> [8] "Status"  
#> 
#> $class
#> [1] "rowwise_df" "tbl_df"     "tbl"        "data.frame"
#> 
#> $row.names
#>  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
#> [26] 26 27 28 29 30 31 32
#> 
#> $groups
#> # A tibble: 32 × 1
#>          .rows
#>    <list<int>>
#>  1         [1]
#>  2         [1]
#>  3         [1]
#>  4         [1]
#>  5         [1]
#>  6         [1]
#>  7         [1]
#>  8         [1]
#>  9         [1]
#> 10         [1]
#> # ℹ 22 more rows

df %>%
  ungroup() %>%
  summarise(across(contains("mean"), ~wilcox.test(.x ~ Status)$p.value))
#> Warning: There were 7 warnings in `summarise()`.
#> The first warning was:
#> ℹ In argument: `across(contains("mean"), ~wilcox.test(.x ~ Status)$p.value)`.
#> Caused by warning in `wilcox.test.default()`:
#> ! cannot compute exact p-value with ties
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 6 remaining warnings.
#> # A tibble: 1 × 7
#>   SI_mean TU_mean  ED_mean MT_mean  DT_mean SK_mean ATT_mean
#>     <dbl>   <dbl>    <dbl>   <dbl>    <dbl>   <dbl>    <dbl>
#> 1  0.0147 0.00512 0.000527 0.00114 0.000114 0.00252  0.00613

^{创建于 2023-11-09 使用 reprex v2.0.2}

使用宽格式与长格式的摘要

Using summarise in wide vs long format

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