r - 在 dplyr 中汇总并为没有值的类别插入 0

Question

假设您有这样的数据:

set.seed(2021)

age <- floor(runif(35, min = 20, max = 25))

dat <- data.frame(age)

dat %>%
  mutate(education = sample(c("Low", "Mid-level", "High"), 
                           size = nrow(dat), prob = c(0.55, 0.2, 0.25), replace = TRUE)) %>%
  group_by(age, education) %>%
  summarise(n = n())

结果:

     age education     n
   <dbl> <chr>     <int>
 1    20 High          1
 2    20 Low           2
 3    21 Low           3
 4    21 Mid-level     2
 5    22 High          2
 6    22 Low           4
 7    23 Low           4
 8    23 Mid-level     2
 9    24 High          1
10    24 Low          10
11    24 Mid-level     4

例如，如您所见，20 岁时没有“中级”教育的计数，因此该类别已从数据框中排除。是否可以将该值显示为 0？

例如

# A tibble: 11 x 3
# Groups:   age [5]
     age education     n
   <dbl> <chr>     <int>
 1    20 High          1
 2    20 Low           2
 3    20 Mid-level     0

Answer 1

除了 group_by 和 summarise，您可以使用 count 和 .drop = FALSE 作为参数。您需要先制作教育列因素，因此您可以尝试在最后添加:

  count(age, as.factor(education), .drop = FALSE) 

编辑:按顺序排列因素以获得更清晰的结果

dat %>%
  mutate(education = sample(
    c("Low", "Mid-level", "High"),
    size = nrow(dat),
    prob = c(0.55, 0.2, 0.25),
    replace = TRUE
  )) %>%
# convert to factor with levels in specified order
  mutate(education = factor(education, levels = c("Low", "Mid-level", "High"))) %>%
  count(age, education, .drop = FALSE) 

结果:

   age education  n
1   20       Low  2
2   20 Mid-level  0
3   20      High  1
4   21       Low  3
5   21 Mid-level  2
6   21      High  0
7   22       Low  4
8   22 Mid-level  0
9   22      High  2
10  23       Low  4
11  23 Mid-level  2
12  23      High  0
13  24       Low 10
14  24 Mid-level  4
15  24      High  1