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在另一篇文章中，我概述了一种将总体百分比添加到gt( )包中的表的方法（如何自动将总体百分比添加到 gt() 包中的 row_summary？）我确定的解决方案涉及对row_summary( )函数的单独调用对于添加的每个整体行百分比。但是，如果将这个相当笨重的解决方案应用于整体组百分比，则即使是这种相当笨重的解决方案也不起作用，如下面的工作示例所示。解决方案？

# Create baseline data
set.seed(1)
df <- tibble(some_letter = sample(letters, size = 10, replace = FALSE),
             some_group = sample(c("A", "B"), size = 10, replace = TRUE),
             num1 = sample(100:200, size = 10, replace = FALSE),
             num2 = sample(100:200, size = 10, replace = FALSE),
             n = num1 + num2) %>% 
  mutate(across(starts_with("num"), ~(.x)/(n), .names = "pct_{col}"))

> df
# A tibble: 10 x 7
   some_letter some_group  num1  num2     n pct_num1 pct_num2
   <chr>       <chr>      <int> <int> <int>    <dbl>    <dbl>
 1 g           A            194   148   342    0.567    0.433
 2 j           A            121   159   280    0.432    0.568
 3 n           B            164   200   364    0.451    0.549
 4 u           A            112   118   230    0.487    0.513
 5 e           B            125   180   305    0.410    0.590
 6 s           A            137   164   301    0.455    0.545
 7 w           B            101   175   276    0.366    0.634
 8 m           B            135   110   245    0.551    0.449
 9 l           A            180   167   347    0.519    0.481
10 b           B            131   137   268    0.489    0.511

# Target: the weighted group percentages to be added to the table in gt( )
df %>% group_by(some_group) %>%
  summarise_at(vars(num1, num2, n), funs(sum)) %>%
  mutate(across(starts_with("num"), ~(.x)/(n), .names = "pct_{col}"))

# A tibble: 2 x 6
  some_group  num1  num2     n pct_num1 pct_num2
  <chr>      <int> <int> <int>    <dbl>    <dbl>
1 A            744   756  1500    0.496    0.504
2 B            656   802  1458    0.450    0.550


# Create table in gt( ), attempting to use the summary_rows( ) function to pass 
# group-specific percentages for pct_num1, the result of which is that the last
# passed value is recycled across all groups...

gt(df, groupname_col = "some_group", rowname_col="some_letter") %>%
  summary_rows(groups = TRUE, columns = vars(num1, num2, n), fns = list( TOTAL = "sum" ) ) %>%
  summary_rows(groups = TRUE,
               columns = vars(pct_num1),
               fns = list(TOTAL = ~ c(0.493,0.454) )
  )

gt( ) 的输出

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1 回答 1

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正如我在您的另一个问题中回答的那样“如何自动将总体百分比添加到 gt() 包中的行摘要中？” , 包gt允许您逐个单元格地控制摘要行中显示的所有信息。缺点是表格的代码变得非常冗长。

为了空间，我使用了一个比你的例子更短的例子，但解决方案可以应用于你的问题

library(dplyr)
library(gt)

df2_ex <-  tribble(
  ~some_letter, ~some_group, ~num1, ~num2,
  "c"         ,         "A",     1,     2,
  "d"         ,         "A",     3,     4,
  "x"         ,         "B",     5,     6,  
  "y"         ,         "B",     7,     8
  ) %>%
  rowwise() %>% 
  mutate(pct_num1 = num1 / sum(c_across(starts_with("num"))), 
    pct_num2 = num2 / sum(c_across(starts_with("num"))))

df2_ex 
#> # A tibble: 4 x 6
#> # Rowwise: 
#>   some_letter some_group  num1  num2 pct_num1 pct_num2
#>   <chr>       <chr>      <dbl> <dbl>    <dbl>    <dbl>
#> 1 c           A              1     2    0.333    0.667
#> 2 d           A              3     4    0.429    0.571
#> 3 x           B              5     6    0.455    0.545
#> 4 y           B              7     8    0.467    0.533

基于 some_group 列的分组表的摘要行将读取

df2_ex_grouped <- df2_ex %>% 
  group_by(some_group) %>%
  summarise_at(vars(num1, num2), sum) %>%
  rowwise() %>%
  mutate(pct_num1 = num1 / sum(c_across(starts_with("num"))), 
    pct_num2 = num2 / sum(c_across(starts_with("num"))))

df2_ex_grouped
#> # A tibble: 2 x 5
#> # Rowwise: 
#>   some_group  num1  num2 pct_num1 pct_num2
#>   <chr>      <dbl> <dbl>    <dbl>    <dbl>
#> 1 A              4     6    0.4      0.6  
#> 2 B             12    14    0.462    0.538

最后，为了完整起见，我使用相同的方法包含了一个宏大的摘要

df2_ex_total <- df2_ex %>%
  ungroup() %>%
  summarise_at(vars(num1, num2), sum) %>%
  rowwise() %>%
  mutate(pct_num1 = num1 / sum(c_across(starts_with("num"))), 
    pct_num2 = num2 / sum(c_across(starts_with("num"))))
df2_ex_total
#> # A tibble: 1 x 4
#> # Rowwise: 
#>    num1  num2 pct_num1 pct_num2
#>   <dbl> <dbl>    <dbl>    <dbl>
#> 1    16    20    0.444    0.556

获取所需表格的代码如下所示。请注意，我使用了两种方法来识别应该出现在摘要行右侧单元格中的值：

  1. 使用 base R 从df2_ex_grouped
  2. 使用pull()

选择你喜欢的那个。

您的代码中缺少的部分是指定 some_groups 列的哪个值您正在应用该summary_rows函数而不是使用groups = TRUE. 希望这个答案能解决你的问题。

df2_ex %>%
  gt(groupname_col = "some_group", rowname_col="some_letter") %>%
  summary_rows(groups = TRUE, columns = vars(num1, num2), fns = list(TOTAL = "sum"),
    formatter = fmt_number, decimals = 0) %>%
  summary_rows(groups = TRUE, columns = vars(num1, num2), fns = list(TOTAL = "sum"),
    formatter = fmt_number, decimals = 0) %>%
  summary_rows(groups = "A", columns = vars(pct_num1), 
    fns = list(TOTAL = ~ df2_ex_grouped$pct_num1[1]),
    formatter = fmt_number, decimals = 4) %>%
  summary_rows(groups = "A", columns = vars(pct_num2), 
    fns = list(TOTAL = ~ df2_ex_grouped$pct_num2[1]),
    formatter = fmt_number, decimals = 4) %>%
  summary_rows(groups = "B", columns = vars(pct_num1), 
    fns = list(TOTAL = ~ df2_ex_grouped$pct_num1[2]),
    formatter = fmt_number, decimals = 4) %>%
  summary_rows(groups = "B", columns = vars(pct_num2), 
    fns = list(TOTAL = ~ (
        df2_ex_grouped %>% 
          filter(some_group == "B") %>%
          select(pct_num2) %>%
          pull())),
    formatter = fmt_number, decimals = 4) %>%
  grand_summary_rows(columns = vars(num1, num2), fns = list(`grand TOTAL` = "sum"),
    formatter = fmt_number, decimals = 0) %>%
  grand_summary_rows(columns = vars(pct_num1), 
    fns = list(
      `grand TOTAL` = ~ (df2_ex_total$pct_num1)),
    formatter = fmt_number, decimals = 3) %>%
  grand_summary_rows(columns = vars(pct_num2), 
    fns = list(
      `grand TOTAL` = ~ (df2_ex_total$pct_num2)),
    formatter = fmt_number, decimals = 3)

由reprex 包（v0.3.0）于 2020 年 11 月 14 日创建

于 2020-11-14T22:47:42.747 回答