# Packages also contain data: ----------------
library(reshape)
data(package="reshape")
?french_fries
head(friench_fries)
str(french_fries)
?tips
head(tips)
str(tips)
# Melting data -------------------------------
# When melting need to indicate which variables are
# identifier and which variables are measured variables
ffm <- melt(french_fries, id=1:5, measure=5:9)
# A variable can only be id or measured, so we only need
# to specify one of the two
ffm <- melt(french_fries, measure=5:9)
ffm <- melt(french_fries, id=1:5)
# Can also use variable names instead of column indices
ffm <- melt(french_fries, id = c("time", "treatment", "subject", "rep"))
# Casting data ---------------------------------------
# Once we have data in molten form, we can cast the data into
# different shapes by specifying which variables should go in the rows
# and which in the columns (just like pivot tables in excel)
cast(ffm, treatment ~ variable, mean)
cast(ffm, subject ~ variable, mean)
cast(ffm, subject + treatment ~ variable, mean)
# Useful for determining where missing values are:
cast(ffm, subject ~ time, length)
cast(ffm, treatment ~ rep, length)
cast(ffm, subject + treatment ~ time, length)
# Find out more on the reshape website: http://had.co.nz/reshape