RinAction - R Data Manipulation - Reshaping Data

gistfile1.r

#####################################################
# -------- Aggregation and Restructuring -----------#
#####################################################

############
#Transpose
############
cars <- mtcars[1:5, 1:4]
t(cars)

####################################
# Aggregating data (group by)
####################################
options(digits=3)
attach(mtcars)
agg <- aggregate(mtcars, by=list(cyl, gear), FUN=mean, na.rm=TRUE)
agg # note that the by variables must be in a list (even if there's only one)

############
# Reshape
############
install.packages("reshape")
library(reshape)

id <- c(1,1,2,2)
time <-c(1,2,1,2)
x1 <- c(5,3,6,2)
x2 <- c(6,5,1,4)
mydata <- data.frame(id, time, x1, x2, stringsAsFactors =FALSE)

# Melting
md <- melt(mydata, id=(c("id","time")))

#Casting
cast(md, id~variable, mean)
cast(md, time~variable, mean)
cast(md, id~time, mean)

cast(md, id+time~variable)
cast(md, id+variable~time)
cast(md, id~variable+time)

# Using Cast() to Transpose Rows to Columns

head(data)
# Package User Installed
# 1              abind    1         1
# 2 AcceptanceSampling    1         0
# 3             ACCLMA    1         0
# 4           accuracy    1         1
# 5            acepack    1         0
# 6        aCGH.Spline    1         0

data.transpose <- cast(data, User ~ Package, value = 'Installed')

head(data[,1:10])
# Rpkg_1 Rpkg_2 Rpkg_3 Rpkg_4 Rpkg_5 Rpkg_6 Rpkg_7 Rpkg_8 Rpkg_9 Rpkg_10
# RUser_1      1      1      0      0      1      0      0      1      0       1
# RUser_2      3      1      1      0      1      1      1      0      1       1
# RUser_3      4      0      1      1      1      1      0      0      1       0
# RUser_4      5      1      1      1      0      1      0      1      1       1
# RUser_5      6      1      1      1      0      1      0      1      1       1
# RUser_6      7      1      1      1      0      1      1      1      1       1