How to do a simple transpose/pivot in R - r

Question

I simply want to take a dataframe with two columns, one with a grouping variable and the second with values, and transform it so that the grouping variable becomes columns with the appropriate values. A very simple question, but after searching for about an hour, I cannot find a good answer. Here is a toy example:
var <- c("Var1", "Var1", "Var2", "Var2")
value <- c(1, 2, 3, 4)
df <- data.frame(var, value)
df.one <- df[df$var == "Var1", ]
df.two <- df[df$var == "Var2", ]
desired.df <- data.frame(df.one[2], df.two[2])
colnames(desired.df) <- c("Var1", "Var2")
desired.df
With more variables and values, this bit of code could become extremely clunky. Can anyone suggest a better method? Any advice would be greatly appreciated!

Answer 1

Data:
df <- structure(list(var = structure(c(1L, 1L, 2L, 2L),
.Label = c("Var1", "Var2"), class = "factor"),
value = c(1, 2, 3, 4)), .Names = c("var", "value"),
class = "data.frame", row.names = c(NA, -4L))
It looks like it is useful to introduce a new variable that identifies the observation within var (I call this case below); you can remove it after reshaping it if you like.
With reshape2/plyr:
library("plyr")
library("reshape2")
## add 'case' identifier
df <- ddply(df,"var",mutate,case=1:length(var))
## dcast() to reshape; then drop identifier
dcast(df,case~var)[,-1]
With tidyr (same strategy):
library("tidyr")
library("dplyr")
df %>% group_by(var) %>%
mutate(case=seq(n())) %>%
spread(var,value) %>%
select(-case)
This could probably be done with reshape() in base R as well, but I have never been able to figure it out ...

Answer 2

Base R solution:
data.frame(split(df$value,df$var))
# Var1 Var2
#1 1 3
#2 2 4
This solution implies that all 'VarN' subsets have equal length.
More general solution will be:
z <- split(df$value,df$var)
max.length <- max(sapply(z,length))
data.frame(lapply(z,`length<-`,max.length))
which appends NA to shorter lists to make sure that all lists have the same length.