[R] Splitting data frame into columns with dplyr

[Thierry Onkelinx]

Dear Michael,

You'll need a combination of dplyr and tidyr

library(dplyr)
library(tidyr)

data.frame(id = rep(1:3, 2), z = rep(c("A", "B")), x = 1:6, y = 7:12) %>%
  arrange(z) %>%
  gather(variable, value, -z, -id) %>%
  mutate(newcol = paste(z, variable, sep = ".")) %>%
  select(-z, -variable) %>%
  spread(newcol, value)


ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

2015-10-01 14:42 GMT+02:00 <Michael.Laviolette op dhhs.state.nh.us>:

>
> I have a data frame with a structure similar to the following. The variable
> z is a grouping variable; x and y are measurement variables.
>
> library(dplyr)
> df <- data.frame(z = rep(c("A", "B")), x = 1:6, y = 7:12) %>%
>   arrange(z)
>
>   z x  y
> 1 A 1  7
> 2 A 3  9
> 3 A 5 11
> 4 B 2  8
> 5 B 4 10
> 6 B 6 12
>
> I need to reshape into one column for each group-measurement combination as
> below. Preferably using dplyr functions, how can I get to this?
>
>   A.x   A.y   B.x   B.y
> 1   1     7     2     8
> 2   3     9     4    10
> 3   5    11     6    12
>
> Thanks,
> M.L.
>
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