Having trouble with spread/pivot wider from long with varying data types [duplicate]

Question

tst <- data.frame(ID = c(123, 123, 123, 124, 124, 124), 
              Identifier = c("S2", "S2", "S5", "S3", "S2", "S2"),
              Speed = c(15,24,11,34,13,15),
              Box_loc = c(801,802,803,801,802,803),
              Ord = c(86,87,90,81,82,84))

I have been attempting to flip the above data from long to wide format, however whenever i try to research it myself, the data does not look similar enough for me to be able to translate it properly. And it seems like it should be a simple solution, but maybe I am missing some critical details.

ID	Identifier(801)	Speed(801)	Ord(801)	Identifier(802)	Speed(802)	Ord(802)	Identifier(803)	Speed(803)	Ord(803)
123	S2	15	86	S2	24	87	S5	11	90
124	S3	34	81	S2	13	82	S2	15	84

I want to get my data to look like this table. The actual data has more than just 2 ID's (if that matters), and the numbers in the headers are the Box_loc. So in other words, for each Box_loc, there are IDs from 123-250 which each need their own row with these columns. My actual file has 10 columns or so, but the syntax should be about the same.

Answer 1

You could use the following solution:

library(tidyr)

tst %>%
  pivot_wider(names_from = Box_loc, 
              values_from = !c(ID, Box_loc), 
              names_glue = "{.value}({Box_loc})")

# A tibble: 2 x 10
     ID `Identifier(801)` `Identifier(802)` `Identifier(803)` `Speed(801)` `Speed(802)`
  <dbl> <chr>             <chr>             <chr>                    <dbl>        <dbl>
1   123 S2                S2                S5                          15           24
2   124 S3                S2                S2                          34           13
# ... with 4 more variables: Speed(803) <dbl>, Ord(801) <dbl>, Ord(802) <dbl>, Ord(803) <dbl>