Transposing in dplyr

Question

I have the following data.frame

df = structure(list(HEADER = c(\"HOME_TRPM\", \"AWAY_TRPM\", \"HOME_TEAM\",\"AWAY_TEAM\"),
                     price = c(\"0.863         


        

Answer 1

They must have updated tidyr since this was originally posted because I think it does what you were originally asking for now:

> library(dplyr)
> library(tidyr)
Warning message:
package ‘tidyr’ was built under R version 3.4.4 
> df
         HEADER              price
    1 HOME_TRPM  0.863104076023855
    2 AWAY_TRPM -0.845186446996287
    3 HOME_TEAM                CHA
    4 AWAY_TEAM                NOP

    > tidyr::spread(df, HEADER, price)
      AWAY_TEAM          AWAY_TRPM HOME_TEAM         HOME_TRPM
    1       NOP -0.845186446996287       CHA 0.863104076023855

If you have a bigger data frame you can always gather and then spread:

> mdf <- data.frame(Things = c("Cookies","Cake","Knives","Kittens", "Politics"), Darkness = sample(1:5), Despair = sample(1:5), Defeat = sample(1:5))> mdf 
    Things Darkness Despair Defeat
1  Cookies        3       4      1
2     Cake        2       2      5
3   Knives        1       3      2
4  Kittens        5       5      3
5 Politics        4       1      4
> mdf %>% tidyr::gather(Idea, Warning_Level, Darkness:Defeat)
     Things     Idea Warning_Level
1   Cookies Darkness             3
2      Cake Darkness             2
3    Knives Darkness             1
4   Kittens Darkness             5
5  Politics Darkness             4
6   Cookies  Despair             4
7      Cake  Despair             2
8    Knives  Despair             3
9   Kittens  Despair             5
10 Politics  Despair             1
11  Cookies   Defeat             1
12     Cake   Defeat             5
13   Knives   Defeat             2
14  Kittens   Defeat             3
15 Politics   Defeat             4
> mdf %>% tidyr::gather(Idea, Warning_Level, Darkness:Defeat) %>% tidyr::spread(Things, Warning_Level)
      Idea Cake Cookies Kittens Knives Politics
1 Darkness    2       3       5      1        4
2   Defeat    5       1       3      2        4
3  Despair    2       4       5      3        1