r - 如何根据 2 列的条件改变 R dplyr 中的新变量？

Question

我有一个看起来像这样的数据集:

Recipient  ID
(chr)       (chr)  
Smith       C
Wells       S
Wells       S
Jones       S
Jones       N
Wu          C
Wu          N
Wu          S

我想改变一个新变量，它是“唯一”或“多个”，基于收件人是否出现一次(唯一)，收件人出现不止一次但每次出现都具有相同的 ID(唯一)，收件人出现不止一次并且有 1 个或多个 ID(多个)。我试过使用:

df %>%
 group_by(Recipient, ID) %>%
 mutuate(Freq = case_when(
                str_count(Recipient) == 1 & str_count(ID) == 1 ~ "Unique",
                str_count(Recipient) > 2 & str_count(ID) == 1 ~ "Unique",
                str_count(Recipient) > 2 & str_count(ID) > 1 ~ "Multiple"))

当我这样做时，所有的值都是多个:

Recipient  ID     Freq
(chr)      (chr)  (chr)
Smith       C     Multiple (should be Unique)
Wells       S     Multiple (should be Unique)
Wells       S     Multiple (should be Unique)
Jones       S     Multiple
Jones       N     Multiple
Wu          C     Multiple
Wu          N     Multiple
Wu          S     Multiple

试了很多次，还是破解不了。任何人都可以帮助解决这个问题，或者推荐一种更简单的编码方法吗？谢谢!

Answer 1

n_distinct() 的可能解决方案:

library(dplyr)

df %>%
  group_by(Recipient) %>%
  mutate(Freq = ifelse(n_distinct(ID) == 1, "unique", "multiple")) %>%
  ungroup()

# A tibble: 8 x 3
  Recipient ID    Freq
  <chr>     <chr> <chr>
1 Smith     C     unique
2 Wells     S     unique
3 Wells     S     unique
4 Jones     S     multiple
5 Jones     N     multiple
6 Wu        C     multiple
7 Wu        N     multiple
8 Wu        S     multiple

---

数据

df <- structure(list(Recipient = c("Smith", "Wells", "Wells", "Jones", 
"Jones", "Wu", "Wu", "Wu"), ID = c("C", "S", "S", "S", "N", "C",
"N", "S")), class = "data.frame", row.names = c(NA, -8L))