Aggregate data in R

Question

I'm looking for a dead simple example on how to use aggregate and calculate means in R.

Say, I have the following data frame:

And I want to calculate the mean values for some ranges with the following result:

RANGE         MEAN
100-200       90
300-400       107.5

How would I go about doing this, cast() or aggregate()?

Your question is unclear. What variable do you want to aggregate on (What do you mean by "some ranges")? — danas.zuokas, Jun 29 '12 at 12:02
Oh, forgot to change the heading for the second table - fixed now. — Johnny, Jun 29 '12 at 12:06

A5C1D2H2I1M1N2O1R2T1 · Accepted Answer · 2015-02-13T04:34:16.093

14

Assuming your data frame is named "x":

aggregate(x$B, list(cut(x$A, breaks=c(0, 200, 400))), mean)
#     Group.1     x
# 1   (0,200]  90.0
# 2 (200,400] 107.5

With "data.table", you can do the following:

library(data.table)
as.data.table(x)[, .(RANGE = mean(B)), by = .(MEAN = cut(A, c(0, 200, 400)))]
#         MEAN RANGE
# 1:   (0,200]  90.0
# 2: (200,400] 107.5

edited Feb 13 '15 at 04:34

answered Jun 29 '12 at 12:10

A5C1D2H2I1M1N2O1R2T1

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For nicer looking output: `aggregate(list(mean = df$B), list(range = cut(df$A, breaks=c(0, 200, 400))), mean)` – A5C1D2H2I1M1N2O1R2T1 Jul 24 '12 at 16:32

jrouquie · Answer 2 · 2012-06-29T12:20:20.677

3

Here is a basic example of aggregate usage.

> foo = data.frame(A=c(100,200,300,400),B=c(85,95,110,105))
> aggregate(foo$B,by=list(foo$A<250),FUN=mean)
  Group.1     B
1   FALSE 107.5
2    TRUE  90.0
>

edited Jun 29 '12 at 12:20

answered Jun 29 '12 at 12:07

jrouquie

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score 2 · Answer 3 · answered Jun 29 '12 at 12:11

2

Or the same with cut and tapply

 foo <- data.frame(A=c(100,200,300,400),B=c(85,95,110,105))
 tapply(foo$B, cut(foo$A, breaks=seq(0, 400, 200)), mean)
  (0,200] (200,400] 
     90.0     107.5

answered Jun 29 '12 at 12:11

johannes

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Aggregate data in R

3 Answers3

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