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("0.863104076023855", "-0.845186446996287","CHA", "NOP")),                .Names = c("HEADER", "price"), row.names = c(NA, 4L), class = "data.frame")  df #>      HEADER              price #> 1 HOME_TRPM  0.863104076023855 #> 2 AWAY_TRPM -0.845186446996287 #> 3 HOME_TEAM                CHA #> 4 AWAY_TEAM                NOP 

which I want to transpose. How can I do it in dplyr without using t()? I tried

df %>% tidyr::spread(HEADER , price) 

but it doesn't give a flat structure but instead does this:

structure(list(AWAY_TEAM = c(NA, NA, NA, "NOP"),      AWAY_TRPM = c(NA, "-0.845186446996287", NA, NA),       HOME_TEAM = c(NA, NA, "CHA", NA),      HOME_TRPM = c("0.863104076023855", NA, NA, NA)),  .Names = c("AWAY_TEAM", "AWAY_TRPM", "HOME_TEAM", "HOME_TRPM"),  class = "data.frame", row.names = c(NA, 4L)) 

The resulting data.frame should be like this:

structure(list(HOME_TRPM = "0.863104076023855",     AWAY_TRPM = "-0.845186446996287",     HOME_TEAM = "CHA",      AWAY_TEAM = "NOP"),  .Names = c("HOME_TRPM", "AWAY_TRPM", "HOME_TEAM", "AWAY_TEAM"),  row.names = c(NA, -1L), class = "data.frame")) 

Answer 1

I think you want tidyr rather than dplyr:

library(tidyr) library(dplyr) df %>% mutate(group = 1) %>%        spread(HEADER, price)    group AWAY_TEAM          AWAY_TRPM HOME_TEAM         HOME_TRPM 1     1       NOP -0.845186446996287       CHA 0.863104076023855 

Using this, you can specify your groupings - and you can add on select(-group) to remove them later.