Reshaping Data in R

R provides a variety of methods for reshaping data prior to analysis.

Transpose

Use the t() function to transpose a matrix or a data frame. In the later case, rownames become variable (column) names.

# example using built-in dataset
mtcars
t(mtcars)

The Reshape Package

Hadley Wickham has created a comprehensive package called reshape to massage data. Both an introduction and article are available. There is even a video!

Basically, you "melt" data so that each row is a unique id-variable combination. Then you "cast" the melted data into any shape you would like. Here is a very simple example.

mydata


id	time	x1	x2
1	1	5	6
1	2	3	5
2	1	6	1
2	2	2	4

# example of melt function
library(reshape)
mdata <- melt(mydata, id=c("id","time"))

newdata


id	time	variable	value
1	1	x1	5
1	2	x1	3
2	1	x1	6
2	2	x1	2
1	1	x2	6
1	2	x2	5
2	1	x2	1
2	2	x2	4

# cast the melted data
# cast(data, formula, function)
subjmeans <- cast(mdata, id~variable, mean)
timemeans <- cast(mdata, time~variable, mean)

subjmeans


id	x1	x2
1	4	5.5
2	4	2.5

timemeans


time	x1	x2
1	5.5	3.5
2	2.5	4.5

There is much more that you can do with the melt( ) and cast( ) functions. See the documentation for more details.

Going Further

To practice massaging data, try this course in cleaning data in R.