Using R (and dplyr) to create multiple summary tables with factor information

Question

I'm an R beginner and am trying to take tables that look like this

ID Type
X  A
X  A
X  B
Y  C
Y  D
Y  E
Z  F
Z  F

And create summary tables for each ID value so they'll look like this

X  Y  Z  
A  C  F
B  D
   E 

How would I go about doing this with dplyr or something similar? I've tried doing something like a crosstab, but since there are no numberic values I haven't been able to.

Answer 1

Here is one approach using tidyverse:

library(tidyverse)

df %>%
  group_by(ID) %>%
  distinct(ID, Type) %>%
  mutate(rn = row_number()) %>%
  pivot_wider(id_cols = rn, names_from = ID, values_from = Type) %>%
  replace(., is.na(.), " ") %>%
  as.data.frame() %>%
  select(-rn)

Output

  X Y Z
1 A C F
2 B D  
3   E  

Data

df <- data.frame(
  ID = c('X', 'X', 'X', 'Y', 'Y', 'Y', 'Z', 'Z'),
  Type = c('A', 'A', 'B', 'C', 'D', 'E', 'F', 'F'),
  stringsAsFactors = FALSE
)