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I have checked and I found several questions related to this questions multiple functions in a single tapply or aggregate statement R Grouping functions: sapply vs. lapply vs. apply. vs. tapply vs. by vs. aggregate

Actually I want to know what is the best way to use multiple functions in one of the above mentioned algorithms.

I try to give an example 

# make a simple matrix 
df <- matrix(data=rnorm(10), 10, 5)

# make a function which calculate several properties 
several <- function(x) {
      c(min = min(x), mean = mean(x), max = max(x), median =median(x), sum=sum(x))
   }

# use one of the apply family 
apply(df,2, several)

how would you do that ? is there any other way to make it easier or more practical ?

Community
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  • Your `df` is `matrix` so, `apply` works okay. If you need to work with `lapply`, convert the dataset to `data.frame` Other option would be to use `summarise_each` from `dplyr` – akrun Mar 03 '15 at 10:05
  • @akrun you can make an example if you want to ! –  Mar 03 '15 at 10:27

1 Answers1

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each in package plyr does the trick for you too:

library(plyr)
df <- matrix(data=rnorm(50), 10, 5)
aaply(df, 2, each(min, mean, max, median, sum))

If you want another input/output format, you can play with the different functions from dplyr.

thothal
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