首页 > 解决方案 > 如何使用 expss 创建两个标题表

问题描述

我一直在阅读有关 expss 包的两个标题表herehere,但在线代码对我不起作用。我的想法是创建一个与此图像非常相似的表:

在此处输入图像描述

数据框是:

df <- data.frame(Categoria = c("gender", "gender" , "gender", "gender", "gender", "gender", 
                                 "religion", "religion", "religion", "religion", "religion",
                                 "religion", "religion", "religion", "religion", "religion", 
                                 "religion", "religion"),
                 Opcoes_da_categoria = c("Mulher", "Homem", "Mulher", "Homem", "Mulher", 
                                           "Homem", "Outra religião", "Católico", "Agnóstico ou ateu",
                                           "Evangélico", "Outra religião", "Católico", 
                                           "Agnóstico ou ateu", "Evangélico", "Outra religião",
                                           "Católico", "Agnóstico ou ateu", "Evangélico"),
                 Resposta = c("A Favor", "A Favor", "Contra",  "Contra",  "Não sei", "Não sei",
                              "A Favor", "A Favor", "A Favor", "A Favor", "Contra", "Contra",
                              "Contra", "Contra", "Não sei", "Não sei", "Não sei", "Não sei"),
                 value_perc = c(65, 50, 33, 43, 2, 7, 67, 64, 56, 28, 31, 34, 35, 66, 2, 2, 10, 5))

我创建两个标题表的代码如下,但由于以下问题,它无法正常工作:

library(expss)

my_table <- df %>%
  tab_cells(Resposta) %>%
  tab_weight(value_perc) %>% 
  tab_cols(Opcoes_da_categoria, Categoria) %>%
  tab_stat_cpct(total_label = NULL) %>%
  tab_pivot()

library(gridExtra)

png("my_table.png", height = 50*nrow(my_table), width = 200*ncol(my_table))
grid.table(my_table)
dev.off()
  

在此处输入图像描述

标签: rdataframeexpss

解决方案


我不知道expss,但最近使用了 flextable,发现它很好。远离这方面的专家,我设法制作了一张漂亮的桌子,它接近你想要的。从您的 DF 开始,必须进行一些更改,以使 DF 具有您的表格所需的格式。通过提取名称的部分 before 重命名 col-names _。构建了描述 col 和 header-names 依赖关系的DF类型。(可以在上面的链接中找到)。然后是flextable部分,它首先构建flextable然后应用typology和其他格式化命令。

由此产生的结果,显示了所附图片。


library(tidyverse)
library(flextable)
#> 
#> Attache Paket: 'flextable'
#> The following object is masked from 'package:purrr':
#> 
#>     compose
df <- data.frame(
  Categoria = c(
    "gender", "gender", "gender", "gender", "gender", "gender",
    "religion", "religion", "religion", "religion", "religion",
    "religion", "religion", "religion", "religion", "religion",
    "religion", "religion"
  ),
  Opcoes_da_categoria = c(
    "Mulher", "Homem", "Mulher", "Homem", "Mulher",
    "Homem", "Outra religião", "Católico", "Agnóstico ou ateu",
    "Evangélico", "Outra religião", "Católico",
    "Agnóstico ou ateu", "Evangélico", "Outra religião",
    "Católico", "Agnóstico ou ateu", "Evangélico"
  ),
  Resposta = c(
    "A Favor", "A Favor", "Contra", "Contra", "Não sei", "Não sei",
    "A Favor", "A Favor", "A Favor", "A Favor", "Contra", "Contra",
    "Contra", "Contra", "Não sei", "Não sei", "Não sei", "Não sei"
  ),
  value_perc = c(65, 50, 33, 43, 2, 7, 67, 64, 56, 28, 31, 34, 35, 66, 2, 2, 10, 5)
)


# adjust your df to match cols and names with tidyvers
dfa <- df %>%
  pivot_wider(names_from =c('Opcoes_da_categoria', 'Categoria'), values_from = 'value_perc')
nam <- str_extract(colnames(dfa),'^[^_]+')
colnames(dfa) <- nam

typology <- data.frame(
  col_keys = c( "Resposta",
                "Mulher", "Homem",
                "Outra religião", "Católico",
                "Agnóstico ou ateu", "Evangélico"),
  what = c("", "Genero", "Genero", "Religio",
           "Religio", "Religio", 'Religio'),
  measure = c( "Resposta", 
               "Mulher", "Homem",
               "Outra religião", "Católico",
               "Agnóstico ou ateu", "Evangélico"),
  stringsAsFactors = FALSE )

library(officer) # needed for making border
dftab <- flextable::flextable(dfa)

border_v = fp_border(color="gray")
dftab <- dftab %>% 
  set_header_df(mapping = typology, key = "col_keys" ) %>% 
  merge_h(part = "header") %>% 
  merge_v(part = "header") %>% 
  theme_booktabs() %>% 
  vline(border = border_v, j =3, part = 'body') %>% 
  vline(border = border_v, j =3, part = 'header')
print(dftab)
#> a flextable object.
#> col_keys: `Resposta`, `Mulher`, `Homem`, `Outra religião`, `Católico`, `Agnóstico ou ateu`, `Evangélico` 
#> header has 2 row(s) 
#> body has 3 row(s) 
#> original dataset sample: 
#>   Resposta Mulher Homem Outra religião Católico Agnóstico ou ateu Evangélico
#> 1  A Favor     65    50             67       64                56         28
#> 2   Contra     33    43             31       34                35         66
#> 3  Não sei      2     7              2        2                10          5

在此处输入图像描述


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