Reputation: 10483
I have an R data frame like this with one factor variable, and two or more value variables.
> factorvar <- c('a', 'b', 'c')
> valvar1 <- c(1, 1, 1)
> valvar2 <- c(2, 2, 2)
> df <- data.frame(factorvar, valvar1, valvar2)
> df
factorvar valvar1 valvar2
1 a 1 2
2 b 1 2
3 c 1 2
I want to widen it such that the final data frame looks something like the following:
> dfnew
valvar1.a valvar1.b valvar1.c valvar2.a valvar2.b valvar2.c
1 1 1 1 2 2 2
dplyr/tidyr with spread only allow me to do it for one column (value).
Upvotes: 2
Views: 637
Reputation: 887251
Try dcast
from the devel version of data.table
i.e. v1.9.5
. This can take multiple value columns, so you may not need to change the format to long
. It can be installed from here
library(data.table)
dcast(setDT(df)[,ind:=1:.N, by = factorvar], ind~factorvar,
value.var=c('valvar1', 'valvar2'))
# ind a_valvar1 b_valvar1 c_valvar1 a_valvar2 b_valvar2 c_valvar2
#1: 1 1 1 1 2 2 2
Or a more compact option by @Arun
dcast(setDT(df), . ~ factorvar, value.var=c("valvar1", "valvar2"))
Upvotes: 1
Reputation: 9913
This solution uses the dplyr
and tidyr
libraries:
library(dplyr)
library(tidyr)
df %>%
gather(valvar, value, -factorvar) %>%
unite(key, factorvar, valvar) %>%
mutate(dummy = 1) %>%
spread(key, value) %>%
select(-dummy)
Which returns:
a_valvar1 a_valvar2 b_valvar1 b_valvar2 c_valvar1 c_valvar2
1 1 2 1 2 1 2
Upvotes: 3