I have a data.frame with the columns: Month, Store and Demand.
Month Store Demand
Jan A 100
Feb A 150
Mar A 120
Jan B 200
Feb B 230
Mar B 320
I need to pivot it around to make a new data.frame or array with columns for each month, store e.g.:
Store Jan Feb Mar
A 100 150 120
B 200 230 320
Any help is very much appreciated. I have just started with R.
> df <- read.table(textConnection("Month Store Demand
+ Jan A 100
+ Feb A 150
+ Mar A 120
+ Jan B 200
+ Feb B 230
+ Mar B 320"), header=TRUE)
So in all likelihood your Month column is a factor with levels sorted alphabetically (EDIT:)
> df$Month <- factor(df$Month, levels= month.abb[1:3])
# Just changing levels was not correct way to handle the problem.
# Need to use within a factor(...) call.
> xtabs(Demand ~ Store+Month, df)
Month
Store Jan Feb Mar
A 100 150 120
B 200 230 320
A slightly less obvious method (since the 'I' function returns its argument):
> with(df, tapply(Demand, list(Store, Month) , I) )
Jan Feb Mar
A 100 150 120
B 200 230 320
Welcome to R.
There are usually many ways to get to the same end using R. Another approach would be to use Hadley's reshape package.
# create the data as explained by @Dwin
df <- read.table(textConnection("Month Store Demand
Jan A 100
Feb A 150
Mar A 120
Jan B 200
Feb B 230
Mar B 320"),
header=TRUE)
# load the reshape package from Hadley -- he has created GREAT packages
library(reshape)
# reshape the data from long to wide
cast(df, Store ~ Month)
And for reference, you should check out this great tutorial. http://www.jstatsoft.org/v21/i12/paper
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