tidyr join an ID table with main table across multiple columns - r

Question

This seems like a very basic operation, but my searches are not finding a simple solution.
As an example of what I am trying to do, consider the following two data frames from a database.
First an ID table that assigns an index to a color name:
ColorID <- tibble(ID = c(1:4), Name = c("Red", "Green", "Blue", "Black"))
ColorID
# A tibble: 4 x 2
ID Name
<int> <chr>
1 1 Red
2 2 Green
3 3 Blue
4 4 Black
Next some table that points to these color indexes (instead of storing text strings):
Widgets <- tibble(Front = c(1,3,4,2,1,1), Back = c(4,4,3,3,1,2),
Top = c(4,3,2,1,2,3), Bottom = c(1,2,3,4,3,2))
Widgets
# A tibble: 6 x 4
Front Back Top Bottom
<dbl> <dbl> <dbl> <dbl>
1 1 4 4 1
2 3 4 3 2
3 4 3 2 3
4 2 3 1 4
5 1 1 2 3
6 1 2 3 2
Now I just want to join the two tables to substitute the index values with the actual color names, so what I want is:
Joined <- tibble(Front = c("Red", "Blue", "Black", "Green", "Red","Red"),
Back = c("Black", "Black", "Blue","Blue", "Red", "Green"),
Top = c("Black","Blue", "Green", "Red", "Green", "Blue"),
Bottom = c("Red", "Green", "Blue", "Black", "Blue","Green"))
Joined
# A tibble: 6 x 4
Front Back Top Bottom
<chr> <chr> <chr> <chr>
1 Red Black Black Red
2 Blue Black Blue Green
3 Black Blue Green Blue
4 Green Blue Red Black
5 Red Red Green Blue
6 Red Green Blue Green
I've tried many iterations with no success, what I thought would work is something like:
J <- Widgets %>% inner_join(ColorID, by = c(. = "ID"))
I can tackle this column by column by using one variable at a time, e.g.
J <- Widgets %>% inner_join(ColorID, by = c("Front" = "ID"))
Which doesn't replace "Front", but instead creates a new "Name" column. Seems like there has to be a simple solution to this though. Thanks.

Answer 1

There is no need for join functions:
library(dplyr)
ColorID <- tibble(ID = c(1:4), Name = c("Red", "Green", "Blue", "Black"))
# reorder so that row number and ID are different
ColorID <- ColorID[c(2, 1, 4, 3), ]
Widgets <- tibble(Front = c(1,3,4,2,1,1), Back = c(4,4,3,3,1,2),
Top = c(4,3,2,1,2,3), Bottom = c(1,2,3,4,3,2))
check_id <- function(col){
ColorID$Name[match(col, ColorID$ID)]
}
Widgets %>%
mutate(across(everything(), check_id))
# A tibble: 6 x 4
Front Back Top Bottom
<chr> <chr> <chr> <chr>
1 Red Black Black Red
2 Blue Black Blue Green
3 Black Blue Green Blue
4 Green Blue Red Black
5 Red Red Green Blue
6 Red Green Blue Green
(Edited) What I'm doing with dplyr and mutate is matching the numbers on Widgets with the number on the ColorID$ID column. This provides me with the row on the ColorID data frame I need for extracting the name.

Answer 2

Does this work:
library(dplyr)
library(tidyr)
Widgets %>% pivot_longer(everything()) %>%
inner_join(ColorID, by = c('value' = 'ID')) %>% select(-value) %>%
pivot_wider(names_from = name, values_from = Name) %>% unnest(everything())
# A tibble: 6 x 4
Front Back Top Bottom
<chr> <chr> <chr> <chr>
1 Red Black Black Red
2 Blue Black Blue Green
3 Black Blue Green Blue
4 Green Blue Red Black
5 Red Red Green Blue
6 Red Green Blue Green