CODEWITHSUNDEEP
r
Mark
Mark

Reputation: 10984

Calculating the mean of values in tables using formulae [R]

I know commands like xtabs and table allow a user to do cross-tabulation

For example the following command generates a pivot table that shows the number of cars that have the same number of gears and cylinders.

> xtabs(~cyl+gear, data = mtcars)
   gear
cyl  3  4  5
  4  1  8  2
  6  2  4  1
  8 12  0  2
>

We can extend the formula so it could show the sum of the horse power for the cars in each bin

> xtabs(hp~cyl+gear, data = mtcars)
   gear
cyl    3    4    5
  4   97  608  204
  6  215  466  175
  8 2330    0  599
>

I am now wondering, is it possible to calculate the mean of horse powers for cars in each bin? for example something like this xtabs(mean(hp)~cyl+gear, data = mtcars)

Upvotes: 7

Views: 5891

Answers (4)

Mark
Mark

Reputation: 10984

Another way of calculating it is by using the aggregate() function. Although the output is not in the form of a table. (via twitter)

> aggregate(hp~cyl+gear,data=mtcars,mean)
  cyl gear       hp
1   4    3  97.0000
2   6    3 107.5000
3   8    3 194.1667
4   4    4  76.0000
5   6    4 116.5000
6   4    5 102.0000
7   6    5 175.0000
8   8    5 299.5000
>

Upvotes: 0

Ramnath
Ramnath

Reputation: 55695

You can do it in one line using cast from the reshape library

cast(mtcars, cyl ~ gear, value = 'hp', fun = mean)

Upvotes: 10

grautur
grautur

Reputation: 30495

(Moving my comment to a response, so I can better edit it.)

I'm not sure how to do it with xtabs (which I've never used before), but here are a couple of ways of doing it using the reshape and plyr packages.

> x = melt(mtcars, id = c("cyl", "gear"), measure = c("hp"))
> cast(x, cyl ~ gear, mean)

> x = ddply(mtcars, .(cyl, gear), summarise, hp = mean(hp))
> cast(x, cyl ~ gear)

Upvotes: 3

Mark
Mark

Reputation: 10984

One interesting response that I received from r-help is as following:

> attach(mtcars)
> tapply(hp,list(cyl,gear),mean)
         3     4     5
4  97.0000  76.0 102.0
6 107.5000 116.5 175.0
8 194.1667    NA 299.5
>

Upvotes: 7

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