带有重复项的pivot_wider

Question

I have the following df

df <- structure(list(ID = c(1, 1, 1, 1, 1, 2, 2, 2, 2), value = c("p", 
"p", "p1", "p2", "p3", "a", "b", "c", "d"), i1 = c(1, 1, 1, 1, 
1, 1, 1, 1, 1)), row.names = c(NA, -9L), class = c("tbl_df", 
"tbl", "data.frame"))

 ID value i1 <dbl> <chr> <dbl> 1 1 p 1 2 1 p 1 3 1 p1 1 4 1 p2 1 5 1 p3 1 6 2 a 1 7 2 b 1 8 2 c 1 9 2 d 1

When I tried to pivot, I got an error saying there are duplicates.

df %>% pivot_wider(names_from = value, values_from = i1, values_fill = list(i1 = 0))

 Warning message: Values in `i1` are not uniquely identified; output will contain list-cols. * Use `values_fn = list(i1 = list)` to suppress this warning. * Use `values_fn = list(i1 = length)` to identify where the duplicates arise * Use `values_fn = list(i1 = summary_fun)` to summarise duplicates

I would like to identify what values are repeating for each unique ID so I could filter. Or maybe I could remove duplicates during the pivot_wider() step. The source code has name_repair which I set to "unique". Did not work!

The ideal output is:

 p p1 p2 p3 abcd 1 1 1 1 1 0 0 0 0 2 0 0 0 0 1 1 1 1

Answer 1

I think in OP's attempt what they were trying to do was to remove duplicates and then pivot the data which can be done with distinct and pivot_wider .

library(dplyr)
library(tidyr)

df %>%
 distinct() %>%
 pivot_wider(names_from = value, values_from = i1, values_fill = list(i1 = 0))

# A tibble: 2 x 9
#     ID     p    p1    p2    p3     a     b     c     d
#  <dbl> <int> <int> <int> <int> <int> <int> <int> <int>
#1     1     1     1     1     1     0     0     0     0
#2     2     0     0     0     0     1     1     1     1

---

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We can also use count and pivot_wider

df %>% 
  count(ID, value) %>%
  mutate(n = +(n > 0)) %>%
  pivot_wider(names_from = value, values_from = n, values_fill = list(n = 0))