如何避免使用pivot_wider将重复项转置到列表中？

Question

我在前 3 列上有重复项，我想在

pivot_wider

转置后保留它们，但不是列表格式。
怎么办？

初始数据与重复项：

dat0 <-
structure(list(id = c("P1", "P1", "P1", "P1", "P1", "P1", "P1", 
"P1", "P1", "P1", "P2", "P2", "P2", "P2", "P2", "P2"), analyte = c("A", 
"A", "B", "B", "B", "B", "C", "C", "D", "D", "B", "B", "B", "B", 
"D", "D"), analyzer = c("X", "Y", "X", "Y", "X", "Y", "X", "Y", 
"X", "Y", "X", "Y", "X", "Y", "X", "Y"), result = c(0.7, 0.9, 
1.26, 1.23, 1.24, 1.22, 5.7, 5.3, 4.1, 4.2, 1.22, 1.23, 1.21, 
1.22, 4.4, 4.5)), row.names = c(NA, -16L), class = c("tbl_df", 
"tbl", "data.frame")) 

pivot_wider 运行后会产生什么，并显示以下消息：

dat1 <- dat0 %>% 
  pivot_wider(names_from = analyzer, values_from = result)  

Values from `result` are not uniquely identified; output will contain list-cols.
• Use `values_fn = list` to suppress this warning.
• Use `values_fn = {summary_fun}` to summarise duplicates.
• Use the following dplyr code to identify duplicates.
  {data} |>
  dplyr::summarise(n = dplyr::n(), .by = c(id, analyte, analyzer)) |>
  dplyr::filter(n > 1L) 

所需的输出，具有重复项：

感谢您的帮助

Answer 1

您可以在分组数据中使用

row_number()

来区分重复项，例如，

dat0 %>%
    mutate(grp = row_number(), .by = c(id, analyte, analyzer)) %>%
    pivot_wider(names_from = analyzer, values_from = result) %>%
    select(-grp)

这给出了

# A tibble: 8 × 4
  id    analyte     X     Y
  <chr> <chr>   <dbl> <dbl>
1 P1    A        0.7   0.9
2 P1    B        1.26  1.23
3 P1    B        1.24  1.22
4 P1    C        5.7   5.3
5 P1    D        4.1   4.2
6 P2    B        1.22  1.23
7 P2    B        1.21  1.22