使用dplyr创建具有几个分类/因子变量的汇总比例表 [英] Using dplyr to create summary proportion table with several categorical/factor variables

问题描述

我正在尝试创建一个表，该表通过另一个变量总结了几个分类变量（使用频率和比例）。我想使用dplyr软件包来做到这一点。

这些先前的Stack Overflow讨论部分是我要寻找的内容：

解决方案

使用tidyr / dplyr组合，这是您的操作方法：

 库（tidyr）
库（dplyr）
 
 mtcars％>％
收集（变量，值，齿轮，碳水化合物，cyl）％>％
 group_by（am，variable，value）％>％
 summary（n = n（））％>％
 mutate（freq = n / sum （n））
  

I am trying to create one table that summarizes several categorical variables (using frequencies and proportions) by another variable. I would like to do this using the dplyr package.

These previous Stack Overflow discussions have partially what I am looking for: Relative frequencies / proportions with dplyr and Calculate relative frequency for a certain group.

Using the mtcars dataset, this is what the output would look like if I just wanted to look at the proportion of gear by am category:

    mtcars %>%
    group_by(am, gear) %>%
    summarise (n = n()) %>%
    mutate(freq = n / sum(n))

    #   am gear  n      freq
    # 1  0    3 15 0.7894737
    # 2  0    4  4 0.2105263
    # 3  1    4  8 0.6153846
    # 4  1    5  5 0.3846154

However, I actually want to look at not only the gears by am, but also carb by am and cyl by am, separately, in the same table. If I amend the code to:

    mtcars %>%
    group_by (am, gear, carb, cyl) %>%
    summarise (n = n()) %>%
    mutate(freq = n / sum(n))

I get the frequencies for each combination of am, gear, carb, and cyl. Which is not what I want. Is there any way to do this with dplyr?

EDIT

Also, it would be an added bonus if anyone knew of a way to produce the table I want, but with the categories of am as the columns (as in a classic 2x2 table format). Here is an example of what i'm referring to. It is from one of my previous publications. I want to produce this table in R, so that I can output it directly to a word document using RMarkdown:

解决方案

With tidyr/dplyr combination, here is how you would do it:

library(tidyr)
library(dplyr)

mtcars %>%
  gather(variable, value, gear, carb, cyl) %>%
  group_by(am, variable, value) %>%
  summarise (n = n()) %>%
  mutate(freq = n / sum(n))

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