How to convert 1-column tibble into matrix as follows?-CodePudding

I need to face below data procesing related problem. How to reshape data given dataframe into demand output?

given df:

pln <- tibble(code = c("PLN","EUR","USD"),
              value_in_PLN = c(1,4.6,4.3))

Demand output:

pln_matrix <- tibble(code = c("PLN","USD","EUR"),
                     PLN = c(1,4.3,4.6),
                     USD = c(1/4.3, 1, 4.3/4.6),
                     EUR = c(1/4.6, 4.6/4.3,1))

Thnaks in advance for any hint! Additionally, it would be the best way if it is possible to use tidyverse functionality to deal with that.

CodePudding user response：

 a <- pln$value_in_PLN %*% t(1/pln$value_in_PLN)
 colnames(a) <- pln$code
 cbind(pln, a)
  code value_in_PLN PLN       EUR       USD
1  PLN          1.0 1.0 0.2173913 0.2325581
2  EUR          4.6 4.6 1.0000000 1.0697674
3  USD          4.3 4.3 0.9347826 1.0000000

a can also be computed as

  outer(pln$value_in_PLN, pln$value_in_PLN, '/')

    [,1]      [,2]      [,3]
[1,]  1.0 0.2173913 0.2325581
[2,]  4.6 1.0000000 1.0697674
[3,]  4.3 0.9347826 1.0000000

or even:

tcrossprod(pln$value_in_PLN, 1/pln$value_in_PLN)
     [,1]      [,2]      [,3]
[1,]  1.0 0.2173913 0.2325581
[2,]  4.6 1.0000000 1.0697674
[3,]  4.3 0.9347826 1.0000000

CodePudding user response：

library(tidyverse)

pln <- tibble(code = c("PLN","EUR","USD"),
              PLN = c(1,4.6,4.3))

bind_cols(code = pln$code,
          map2_dfc(
            .x = pln$code,
            .y = pln$PLN,
            .f = ~ transmute(pln,!!.x := pln$PLN / .y)
          ))
#> # A tibble: 3 × 4
#>   code    PLN   EUR   USD
#>   <chr> <dbl> <dbl> <dbl>
#> 1 PLN     1   0.217 0.233
#> 2 EUR     4.6 1     1.07 
#> 3 USD     4.3 0.935 1

^{Created on 2022-04-26 by the reprex package (v2.0.1)}