Реструктурируйте фрейм данных в R

Question

Это исходные данные. Кадр

temp <- structure(list(Initial = c(
  32.5, 30.4, 36.5, 4.2, 24.3
), Amount = c(
  374.24, 79.05, 1.02, 0.79, 0.71
), Load  = c(
  11.512, 2.605, 0.027, 0.021, 0.019
), Extra = c(
  36.9, 32.5, 12.2, 12.2, 12.2
), Perc = c(
  114L, 107L, 33L, 33L, 33L
)), row.names = c(
  1L, 2L, 3L, 4L, 5L
), class = "data.frame")

Это то, что я хочу создать. Я бы предпочел тидиверс

data <- structure(list(Rs = c(
  "Initial", "Initial", "Initial", "Initial",
  "Initial", "Initial", "Initial", "Initial", "Initial", "Initial",
  "Initial", "Initial", "Initial", "Initial", "Initial", "Initial",
  "Initial", "Initial", "Initial", "Initial", "Amount", "Amount",
  "Amount", "Amount", "Amount", "Amount", "Amount", "Amount", "Amount",
  "Amount", "Amount", "Amount", "Amount", "Amount", "Amount", "Load",
  "Load", "Load", "Load", "Load", "Load", "Load", "Load", "Load",
  "Load", "Extra", "Extra", "Extra", "Extra", "Extra"
), Rvalue = c(
  32.5,
  30.4, 36.5, 4.2, 24.3, 32.5, 30.4, 36.5, 4.2, 24.3, 32.5, 30.4,
  36.5, 4.2, 24.3, 32.5, 30.4, 36.5, 4.2, 24.3, 374.24, 79.05,
  1.02, 0.79, 0.71, 374.24, 79.05, 1.02, 0.79, 0.71, 374.24, 79.05,
  1.02, 0.79, 0.71, 11.512, 2.605, 0.027, 0.021, 0.019, 11.512,
  2.605, 0.027, 0.021, 0.019, 36.9, 32.5, 12.2, 12.2, 12.2
), Cs = c(
  "Amount",
  "Amount", "Amount", "Amount", "Amount", "Load", "Load", "Load",
  "Load", "Load", "Extra", "Extra", "Extra", "Extra", "Extra",
  "Perc", "Perc", "Perc", "Perc", "Perc", "Load", "Load", "Load",
  "Load", "Load", "Extra", "Extra", "Extra", "Extra", "Extra",
  "Perc", "Perc", "Perc", "Perc", "Perc", "Extra", "Extra", "Extra",
  "Extra", "Extra", "Perc", "Perc", "Perc", "Perc", "Perc", "Perc",
  "Perc", "Perc", "Perc", "Perc"
), Cvalue = c(
  374.24, 79.05, 1.02,
  0.79, 0.71, 11.512, 2.605, 0.027, 0.021, 0.019, 36.9, 32.5, 12.2,
  12.2, 12.2, 114, 107, 33, 33, 33, 11.512, 2.605, 0.027, 0.021,
  0.019, 36.9, 32.5, 12.2, 12.2, 12.2, 114, 107, 33, 33, 33, 36.9,
  32.5, 12.2, 12.2, 12.2, 114, 107, 33, 33, 33, 114, 107, 33, 33,
  33
)), class = "data.frame", row.names = c(NA, -50L))

Answer 1

Мы можем выполнить цикл, используя names(temp), select требуемые столбцы, затем gather, наконец, связывает все кадры данных вместе

library(tidyverse)
#head(names(temp),-1)
map_dfr(names(temp)[-length(temp)], ~select(temp,.x:ncol(temp)) %>% 
                      gather(key = Cs,value = Cvalue,-.x) %>% mutate(Rs=.x) %>% 
                      select(Rs,Rvalue=.x,everything())) 

Answer 2

Объяснение того, что делает pmap:

pmap(list(x, y, z), fun) совпадает с Map(fun, x, y, z).Затем pmap_dfr делает то же самое, но дополнительно rbind объединяет все элементы результирующего списка в один фрейм данных.

library(tidyverse)

pairs <- expand.grid(names(temp), names(temp), stringsAsFactors = F) %>% 
            filter(Var1 > Var2)

pmap_dfr(pairs, ~{
  tibble(Rs = .y, Rvalue = temp[[.y]], 
         Cs = .x, Cvalue = temp[[.x]])
})

edit: На самом деле, неясно, как вы решаете, какойRs, Cs пары, которые вы включаете, а какие нет.Какой бы ни была логика, начиная с expand.grid и фильтрации, вероятно, вы попадете туда.