用另一个变量计算几个二进制变量的比例

Emman 发表于 Dev

艾曼

我有几个二进制变量的数据，我想通过另一个变量计算每个变量的比例。

例

我对人们进行调查并询问他们：
请标记您喜欢以下哪种水果（可以标记多种选择）：
☐香蕉☐苹果☐橙子☐草莓☐桃子

选中此框的每个人都会1输入数据，当留空时，将表示为0。数据如下所示：

library(dplyr)

set.seed(2021)

my_df <-
  matrix(rbinom(n = 100, size = 1, prob = runif(1)), ncol = 5) %>%
  as.data.frame() %>%
  cbind(1:20, ., sample(c("male", "female"), size = 20, replace = T)) %>%
  setNames(c("person_id", "banana", "apple", "orange", "strawberry", "peach", "gender"))

my_df
#>    person_id banana apple orange strawberry peach gender
#> 1          1      1     1      1          0     0 female
#> 2          2      1     0      0          0     1 female
#> 3          3      0     0      1          0     1 female
#> 4          4      1     1      0          1     0 female
#> 5          5      1     1      1          0     0   male
#> 6          6      1     1      1          0     1 female
#> 7          7      0     1      0          1     1   male
#> 8          8      1     1      0          0     0   male
#> 9          9      1     1      1          0     0 female
#> 10        10      0     0      0          0     0   male
#> 11        11      1     1      1          1     1   male
#> 12        12      1     1      0          0     1   male
#> 13        13      1     1      0          1     0   male
#> 14        14      1     1      0          0     0   male
#> 15        15      0     0      0          0     1   male
#> 16        16      0     1      0          0     1   male
#> 17        17      1     0      0          0     1   male
#> 18        18      1     1      1          1     1   male
#> 19        19      0     0      1          1     1 female
#> 20        20      0     0      0          0     0 female

^{由reprex软件包（v0.3.0）创建于2021-02-01}

我想得到每种水果的比例，除以gender。通过此答案，我了解了如何对一个变量进行操作（例如banana）：

my_df %>%
  group_by(gender) %>%
  summarise(n_of_observations = n(), prop = sum(banana == 1)/n())

## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 2 x 3
##   gender n_of_observations  prop
##   <chr>              <int> <dbl>
## 1 female                10   0.6
## 2 male                  10   0.4

但是，如何得到所有水果这样的桌子呢？

所需的输出：

##    fruit      gender  prop
##    <chr>      <chr>  <dbl>
##  1 banana     female   0.6
##  2 banana     male     0.4
##  3 apple      female   0.4
##  4 apple      male     0.3
##  5 orange     female   0.3
##  6 orange     male     0.1
##  7 strawberry female   0.4
##  8 strawberry male     0.4
##  9 peach      female   0.3
## 10 peach      male     0.6

dplyr如果可能，我正在寻找解决方案。非常感谢！

LMc

您可以tidyr先透视数据，然后再对其进行汇总：

library(tidyr)

tidyr::pivot_longer(my_df, banana:peach,
                    names_to = "fruit") %>% 
  dplyr::group_by(gender, fruit) %>% 
  dplyr::summarize(prop = sum(value) / n())

   gender fruit       prop
   <chr>  <chr>      <dbl>
 1 female apple      0.5  
 2 female banana     0.625
 3 female orange     0.625
 4 female peach      0.5  
 5 female strawberry 0.25 
 6 male   apple      0.75 
 7 male   banana     0.667
 8 male   orange     0.25 
 9 male   peach      0.583
10 male   strawberry 0.333

arrange如果要按排序，可以将其传送到fruit。您还可以使用来在summarize函数中添加观测值的数量n = n()。

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