R aggregate dataframe on two variables and apply function

Question

I have a dataframe which I'd like to aggregate over two variables applying the function mean on each meassurement. Here the head of the dataframe:

  Subject Activity         meassureA         meassureB         meassureC       meassureD
1       1  running         0.2820216      -0.037696218       -0.13489730       -0.3282802
2       1  running         0.2558408      -0.064550029       -0.09518634       -0.2292069
3       1  walking         0.2548672       0.003814723       -0.12365809       -0.2751579
4       2  running         0.3433705      -0.014446221       -0.16737697       -0.2299235

Now, I would like to get something like this:

  Subject Activity         meassureA         meassureB         meassureC       meassureD
1       1  running         mean(S1,A1)      mean(S1,A1)       mean(S1,A1)       mean(S1,A1)
2       1  walking         mean(S1,A2)      mean(S1,A2)       mean(S1,A2)       mean(S1,A2)
3       2  running         mean(S2,A1)      mean(S2,A1)       mean(S2,A1)       mean(S2,A1)
4       2  walking         mean(S2,A2)      mean(S2,A2)       mean(S2,A2)       mean(S2,A2)

Where the value of meassure A is the mean of all values of subject 1 (S1) performing activity running (A1).

I was thinking of using aggregate(), but I am not able to apply what I learned so far to my problem. Any help is highly appreciated.

Not sure but maybe aggregate(.~ Subject + Activity, df, mean)? — David Arenburg
– David Arenburg, Commented Apr 26, 2015 at 14:33

Steven Beaupré · Accepted Answer · 2015-04-26 15:01:02Z

1

As mentionned by David in the comments, you could do:

aggregate(. ~ Subject + Activity, df, mean)

Or using data.table:

data.table::setDT(df)[, lapply(.SD, mean), by = .(Subject, Activity)]

Or using dplyr:

library(dplyr)
df %>% group_by(Subject, Activity) %>% summarise_each(funs(mean))

Which gives:

#  Subject Activity meassureA    meassureB  meassureC  meassureD
#1       1  running 0.2689312 -0.051123123 -0.1150418 -0.2787436
#2       1  walking 0.2548672  0.003814723 -0.1236581 -0.2751579
#3       2  running 0.3433705 -0.014446221 -0.1673770 -0.2299235

edited Apr 26, 2015 at 15:01

answered Apr 26, 2015 at 14:58

Steven Beaupré

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1 Comment

David Arenburg Over a year ago

Or data.table::setDT(df)[, lapply(.SD, mean), by = .(Subject, Activity)] if you know what you doing :)

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