Question

问题：我有一个包含100个问题的调查。这些可能具有5种类型的响应，我将这些响应分组并统计到单独的表中（在列表中）。每个表具有不同数量的列，具有不同的变量名。

样品数据：

tbl1 <-   tribble(~"stakeholder", ~"Question", ~"1-Little", ~"2",   ~"3",   ~"4-Much",  ~"Do not know/ Not applicable", ~"no_response",
        "SH_1", "QUESTION 2",   2,  1,  4,  8, 1,   1,
        "SH_2", "QUESTION 2",   2,  1,  4,  8, 1,   1,
        "SH_3", "QUESTION 2",   2,  1,  4,  8, 1,   1,
        "SH_4", "QUESTION 2",   2,  1,  4,  8, 1,   1,
)

tbl2 <- tribble(~"stakeholder", ~"Question", ~"1-Little",   ~"2",   ~"3",   ~"4-Much", ~"5-MuchMuch",   ~"Do not know/ Not applicable", ~"no_response",
                "SH_1", "QUESTION 2",   2,  1,  4,  8, 1,   1,2,
                "SH_2", "QUESTION 2",   2,  1,  4,  8, 1,   1,2,
                "SH_3", "QUESTION 2",   2,  1,  4,  8, 1,   1,2,
                "SH_4", "QUESTION 2",   2,  1,  4,  8, 1,   1,2
)

问题：如何基于总和创建比例计数？ 我需要根据每个问题的回答总数创建比例表。

我基于分组变量，通过字符响应在样本表中创建以上计数。我注意到，我将通过6种不同的方式对图形和表格进行分组和再现（总共需要近600种！）：

    tally_function <- function(tbl) {
  tbl %>% 
  gather(key = Question, value = Response,
         12:length(.)) %>% 
  group_by(stakeholder, Question, Response) %>% 
  tally %>% 
  spread(Response, n, fill = 0) %>% 
  select(stakeholder, Question, everything(), no_response = `<NA>`) %>% 
    arrange(Question)

}

我以前使用的函数调用各个列名来产生总和，但这在这里不起作用，因为每个表中的列名都不同：

Prop_Function_Group1 <- function(tbl){
  tbl %>% 
    summarise(`Number of Responses (Count)` = sum(`1-Little` + `2`+`Do not know/ Not applicable`+
                                            `3`+`4-Much` + no_response, na.rm = TRUE),
              `1-Little`= sum(`1-Little`/`Number of Responses (Count)`, na.rm = TRUE) * 100,
              `2` = sum(`2` / `Number of Responses (Count)`, na.rm = TRUE) * 100,
              `Do not know/ Not applicable` = sum(`Do not know/ Not applicable` / `Number of Responses (Count)`, na.rm = TRUE)* 100,
              `3` = sum(`3` / `Number of Responses (Count)`, na.rm = TRUE) * 100,
              `4-Much` = sum(`4-Much` / `Number of Responses (Count)`, na.rm = TRUE) * 100,
              `no_response` = sum(no_response / `Number of Responses (Count)`, na.rm = TRUE) * 100
    ) %>% 
    mutate_if(is.numeric, round, digits = 2) %>% 
    arrange(desc(`Number of Responses (Count)`))
}

当前，我有这个，但是相信我将需要基于names（tbl）的某种ifelse / case_when（）循环，但是在编程上确实是新手，并且不确定从哪里开始。 summary函数中的col名称必须与它们正在汇总的输入表的名称相同。

    prop_function <- function(tbl){
  tbl %>% 
  summarise(`Number of Responses` = sum(3:length(.), na.rm = TRUE))
}

我不需要一个完整的解决方案，任何小的想法和贡献都会有所帮助。如果这是重复的问题类型，请按照正确的方向进行指导。

此后，我还将它们输入purr :: map（）+ ggplot（）中，因此，请注意解决方案是否对tidyverse友好。

干杯。

Answer 1

这是一个继续使用dplyr / tidyverse并镜像来自Prop_Function_Group1(tbl1)的输出格式/结构的解决方案。但是，该功能应该可以应用于您描述的其他表格形式。

library(tidyverse)

prop_function <- function(tbl){
tbl_counts <- tbl %>% 
  summarise_if(is.double, ~sum(.x))

tbl_counts %>% 
  mutate_all(~100 * .x / sum(tbl_counts)) %>%
  mutate(`Number of Responses (Count)` = sum(tbl_counts)) %>% 
  mutate_all(round, digits = 2) %>% 
  select(length(.), everything()) # move last col to first
}

list(tbl1, tbl2) %>% 
  map(prop_function)
#> [[1]]
#> # A tibble: 1 x 7
#>   `Number of Resp~ `1-Little`   `2`   `3` `4-Much` `Do not know/ N~
#>              <dbl>      <dbl> <dbl> <dbl>    <dbl>            <dbl>
#> 1               68       11.8  5.88  23.5     47.1             5.88
#> # ... with 1 more variable: no_response <dbl>
#> 
#> [[2]]
#> # A tibble: 1 x 8
#>   `Number of Resp~ `1-Little`   `2`   `3` `4-Much` `5-MuchMuch`
#>              <dbl>      <dbl> <dbl> <dbl>    <dbl>        <dbl>
#> 1               76       10.5  5.26  21.0     42.1         5.26
#> # ... with 2 more variables: `Do not know/ Not applicable` <dbl>,
#> #   no_response <dbl>

^{由reprex package（v0.2.1）于2019-01-10创建}

Answer 2

上面@ bryan-shalloway给出的答案使我步入正轨-此处所做的主要更改是，此版本通过在mutate（）中嵌套map（）操作来维护分组变量名称：

  proportion_function <- function(tbl){


  tbl_counts <- tbl %>%
    gather(key = Question, value = Response,
           12:length(.)) %>% 
    group_by(Region, Question, Response) %>% 
    tally %>% 
    spread(Response, n, fill = 0) %>% 
    select(Region, Question, everything(), no_response = `<NA>`) %>%
    arrange(Question)

  tbl_counts %>% 
    nest() %>% 
    mutate(data = map(data, ~ .x %>% select_if(is.numeric) 
                      %>% mutate(count = sum(rowSums(.))))) %>%
    mutate(data = map(data, ~ .x %>% select_if(is.numeric) 
                      %>% mutate_all(funs((. / count) * 100 )))) %>%
    mutate(data = map(data, ~ .x %>% select_if(is.numeric)
                      %>% mutate_all(round, digits = 2))) %>%
    unnest()
}

从具有不同变量名称的计数表中创建比例函数

2 个答案: