使用dplyr在R中获取数据帧后的完全连接

我有一个如下所示的数据帧：

+--------+---------------+----+
| period |     label     | n  |
+--------+---------------+----+
|      4 | Engaged       |  2 |
|      4 | Remarkable    |  1 |
|      5 | Engaged       |  1 |
|      5 | Inconsistent  |  2 |
|      5 | Remarkable    |  5 |
|      6 | Engaged       |  1 |
|      6 | Inconsistent  |  1 |
|      6 | Remarkable    |  5 |
|      7 | Engaged       |  2 |
|      7 | Remarkable    |  3 |
|      7 | Transactional |  2 |
+--------+---------------+----+

+--------+---------------+----+
| period |     label     | n  |
+--------+---------------+----+
|      4 | Inconsistent  |  0 |
|      4 | Transactional |  0 |
|      4 | Engaged       |  2 |
|      4 | Remarkable    |  1 |
|      5 | Inconsistent  |  2 |
|      5 | Transactional |  0 |
|      5 | Engaged       |  1 |
|      5 | Remarkable    |  5 |
|      6 | Inconsistent  |  1 |
|      6 | Transactional |  0 |
|      6 | Engaged       |  1 |
|      6 | Remarkable    |  5 |
|      7 | Inconsistent  |  0 |
|      7 | Transactional |  2 |
|      7 | Engaged       |  2 |
|      7 | Remarkable    |  3 |
+--------+---------------+----+

我需要让每个时期都有不一致、事务性、参与性和卓越性的标签选项。如果每个周期中未使用每个标签，则应为该周期插入该标签，其值n等于0

我考虑将数据帧从长到宽旋转，然后用0填充缺少的值，但有时在任何时段都可能看不到每个值。我还考虑过按时段对数据帧进行分组，然后对所有标签进行完全连接，但在连接数据帧时似乎忽略了组

我需要得到一个如下所示的数据帧：

+--------+---------------+----+
| period |     label     | n  |
+--------+---------------+----+
|      4 | Engaged       |  2 |
|      4 | Remarkable    |  1 |
|      5 | Engaged       |  1 |
|      5 | Inconsistent  |  2 |
|      5 | Remarkable    |  5 |
|      6 | Engaged       |  1 |
|      6 | Inconsistent  |  1 |
|      6 | Remarkable    |  5 |
|      7 | Engaged       |  2 |
|      7 | Remarkable    |  3 |
|      7 | Transactional |  2 |
+--------+---------------+----+

+--------+---------------+----+
| period |     label     | n  |
+--------+---------------+----+
|      4 | Inconsistent  |  0 |
|      4 | Transactional |  0 |
|      4 | Engaged       |  2 |
|      4 | Remarkable    |  1 |
|      5 | Inconsistent  |  2 |
|      5 | Transactional |  0 |
|      5 | Engaged       |  1 |
|      5 | Remarkable    |  5 |
|      6 | Inconsistent  |  1 |
|      6 | Transactional |  0 |
|      6 | Engaged       |  1 |
|      6 | Remarkable    |  5 |
|      7 | Inconsistent  |  0 |
|      7 | Transactional |  2 |
|      7 | Engaged       |  2 |
|      7 | Remarkable    |  3 |
+--------+---------------+----+

以下是我正在处理的示例数据：

df <- as.data.frame(
  list(
    period = c(4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L,
                  7L, 7L, 7L),
    label = c(
      "Engaged",
      "Remarkable",
      "Engaged",
      "Inconsistent",
      "Remarkable",
      "Engaged",
      "Inconsistent",
      "Remarkable",
      "Engaged",
      "Remarkable",
      "Transactional"
    ),
    n = c(2L, 1L, 1L,
          2L, 5L, 1L, 1L, 5L, 2L, 3L, 1L)
  )
)

options <- as.data.frame(
  list(
    label = c(
      "Inconsistent",
      "Transactional",
      "Engaged",
      "Remarkable"
    ),
    n = c(0L, 0L, 0L, 0L)
  )
)

---

我们可以按“期间”分组，然后根据“选项”数据集中的“标签”值完成“标签”

library(dplyr)
library(tidyr)
df %>% 
     group_by(period) %>%
     complete(label = options$label, fill = list(n = 0))

---

我们可以按“期间”分组，然后根据“选项”数据集中的“标签”值完成“标签”

library(dplyr)
library(tidyr)
df %>% 
     group_by(period) %>%
     complete(label = options$label, fill = list(n = 0))