In the "An Introduction to reshape2" package Sean C. Anderson presents the following example.
He uses the airquality data and renames the column names
names(airquality) <- tolower(names(airquality))
The data look like
# ozone solar.r wind temp month day
# 1 41 190 7.4 67 5 1
# 2 36 118 8.0 72 5 2
# 3 12 149 12.6 74 5 3
# 4 18 313 11.5 62 5 4
# 5 NA NA 14.3 56 5 5
# 6 28 NA 14.9 66 5 6
Then he melts them by
aql <- melt(airquality, id.vars = c("month", "day"))
to get
# month day variable value
# 1 5 1 ozone 41
# 2 5 2 ozone 36
# 3 5 3 ozone 12
# 4 5 4 ozone 18
# 5 5 5 ozone NA
# 6 5 6 ozone 28
Finally he gets the original one (different column order) by
aqw <- dcast(aql, month + day ~ variable)
My Quesiton
Assume now that we do not have ID variables (i.e. month and day) and have melted the data as follows
aql <- melt(airquality)
which look like
# variable value
# 1 ozone 41
# 2 ozone 36
# 3 ozone 12
# 4 ozone 18
# 5 ozone NA
# 6 ozone 28
My question is how can I get the original ones? The original ones would correspond to
# ozone solar.r wind temp
# 1 41 190 7.4 67
# 2 36 118 8.0 72
# 3 12 149 12.6 74
# 4 18 313 11.5 62
# 5 NA NA 14.3 56
# 6 28 NA 14.9 66
Another option is
unstack
As the question is about
dcast
, we can create a sequence column and then usedcast
If you are using
data.table
, the devel version ofdata.table
ie.v1.9.5
also hasdcast
function. Instructions to install the devel version arehere
One option using
split
,Here, the data is split by the
variable
column, then the second column of each group is combined back into a data frame (the[[
function with the argument2
is passed tosapply
)