在 R 脚本中创建包含每个问题选项总百分比的报告

Question

我有一个包含组和一堆 yes/no 值的数据集（0=否，1=是）。我正在尝试仅使用 R 脚本创建一个包含每组总计和漂亮布局的报告。

这是我目前所知道的。

# test data (real data from API service is larger)
df_visits <- read.table(text = "
PATIENT_ID,RAND,UNIT_GT3,HEMOR_YN
1000,ARM1,1,0
1001,ARM2,0,0
1003,ARM1,1,0
1005,ARM1,1,0
1006,ARM2,1,1
1008,ARM2,0,0
1009,ARM1,1,1
1010,ARM2,1,0
1011,ARM1,1,0
1014,ARM2,0,0
1015,ARM2,1,0
1018,ARM1,1,1
", header = TRUE, sep = ",")

# results per group, using 'ifelse' feels clunky but it works
df_per_group  <- data.frame(
  cbind(
    RAND     = tapply(df_visits$RAND,     list(df_visits$RAND), max, na.rm=TRUE),
    UNIT_GT3_Y = tapply(ifelse(df_visits$UNIT_GT3 == 1, 1, 0), list(df_visits$RAND), sum, na.rm=TRUE),
    UNIT_GT3_N = tapply(ifelse(df_visits$UNIT_GT3 == 0, 1, 0), list(df_visits$RAND), sum, na.rm=TRUE),
    HEMOR_YN_Y = tapply(ifelse(df_visits$HEMOR_YN == 1, 1, 0), list(df_visits$RAND), sum, na.rm=TRUE),
    HEMOR_YN_N = tapply(ifelse(df_visits$HEMOR_YN == 0, 1, 0), list(df_visits$RAND), sum, na.rm=TRUE)
  )
)

# t{base} = Matrix Transpose
df_pivot <- as.data.frame(t(df_per_group))

生成的 df_pivot 数据框如下所示，我可以使用 write.csv():

导出它

# RND          ARM1  ARM2
# ------------+-----+-----+
# UNIT_GT3_Y  |   6 |   3 |
# UNIT_GT3_N  |   0 |   3 |
# HEMOR_YN_Y  |   2 |   1 |
# HEMOR_YN_N  |   4 |   5 |
# ------------+-----+-----+

但是，我希望目标数据集也有每个问题的总百分比，并且有更好的问题标签，所以像这样：

# RND            ARM1         ARM2
# --------------+-------------+------------+
# Units>3 : Yes |   6  (100%) |    3 (50%) |
#           No  |   0    (0%) |    3 (50%) |
# --------------+-------------+------------+
# Hemmorage Yes |   2 (33.3%) |  1 (16.7%) |
#           No  |   4 (66.7%) |  5 (83.3%) |
# --------------+-------------+------------+

有没有办法像这样更改标签并添加每个问题的百分比？
另外，我是 R 脚本的新手，所以是否有更有效的方法来获得所需的结果？

Answer 1

您可以使用 tables 包，它允许您直接从初始数据生成摘要 table :

library(tables)

tables::tabular(((`Units>3` = factor(ifelse(UNIT_GT3==0,'No','Yes'),levels=c('Yes','No'))) +
                 (Hemmorage = factor(ifelse(HEMOR_YN==0,'No','Yes'),levels=c('Yes','No'))))
                ~(RND = factor(RAND))* ((n=1) + Percent(Equal(factor(RAND))))
                ,data = df_visits)

              RND                      
               ARM1         ARM2        
               n    Percent n    Percent
 Units>3   Yes 6    100.00  3    50.00  
           No  0      0.00  3    50.00  
 Hemmorage Yes 2     33.33  1    16.67  
           No  4     66.67  5    83.33

编辑：在评论中关注您的问题：

tables::tabular(((`Units>3` = factor(ifelse(UNIT_GT3==0,'No','Yes'),levels=c('Yes','No'))) +
                   (Hemmorage = factor(ifelse(HEMOR_YN==0,'No','Yes'),levels=c('Yes','No'))))
                ~(Total = 1)+(RND = factor(RAND))* ((Nb=1) + Percent(Equal(factor(RAND))))
                ,data = df_visits)

                     RND                      
                     ARM1         ARM2        
               Total Nb   Percent Nb   Percent
 Units>3   Yes 9     6    100.00  3    50.00  
           No  3     0      0.00  3    50.00  
 Hemmorage Yes 3     2     33.33  1    16.67  
           No  9     4     66.67  5    83.33

Answer 2

您可以使用 tidyverse 和 kableExtra 包来创建漂亮的表格：

library(tidyverse)
library(kableExtra)

raw <- tibble::tibble(RND = c("UNIT_GT3_Y",
                              "UNIT_GT3_N",
                              "HEMOR_YN_Y",
                              "HEMOR_YN_N"),
                      ARM1 = c(6,0,2,4),
                      ARM2 = c(3,3,1,5))

tbl <- raw %>% 
  mutate(State = if_else(str_detect(str_sub(RND,-1), "Y"), "Yes", "No"),
         RND = word(RND, 1,2, sep="_")) %>% 
  group_by(RND) %>% 
  mutate_if(is.numeric, ~ paste0(.x, " [", 
                                 round((.x /sum(.x)) * 100, 1), 
                                 "%]")) %>% 
  ungroup() %>% 
  select(RND, State, everything()) %>% 
  kbl() %>%
  kable_paper(full_width = F) %>%
  column_spec(1, bold = T) %>% 
  collapse_rows(columns = 1, valign = "top")

^{由 reprex package (v0.3.0)}

于 2020-12-07 创建

kableExtra 有很多样式选项

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