Any way to apply TWO functions with tapply()?

I need to compute the mean and the standard deviation of a data set and would
like to have the results in one table/data frame. I call tapply() two times
and do then merge the resulting tables to have them all in one table. Is
there any way to tell tapply() to use the functions mean and sd within one
function call? Something like tapply(data$response, list(data$targets,
data$conditions), c(mean, sd)).

Thanks in advance.
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f <- function(x) data.frame(mean = mean(x), sd = sd(x))
do.call(rbind, tapply(CO2$uptake, CO2$Type, f))

I need to compute the mean and the standard deviation of a data set and would
like to have the results in one table/data frame. I call tapply() two times
and do then merge the resulting tables to have them all in one table. Is
there any way to tell tapply() to use the functions mean and sd within one
function call? Something like tapply(data$response, list(data$targets,
data$conditions), c(mean, sd)).

Thanks in advance.
--
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That was a superb answer to a question that has already appeared in various
forms on r-help at least 4 times that I can remember just this week. I think
your text could be appended without much editing into the FAQ. ?It could
then have its own hyperlink, and you wouldn't need to type it again the next
umpteen times that it will re-appear.

--
David.


On May 7, 2010, at 8:50 AM, Gabor Grothendieck wrote:

tapply does handle functions with vector outputs, e.g. using the built
in CO2 data set the following data frame is returned:

f <- function(x) data.frame(mean = mean(x), sd = sd(x))
do.call(rbind, tapply(CO2$uptake, CO2$Type, f))

? ? ? ? ? mean ? sd
Quebec ? ? ?33.5 9.67
Mississippi 20.9 7.82

Note that if you replace data.frame with c in f then you get a matrix
out instead of a data.frame.

There is also somewhat similar functionality in summaryBy (doBy
package), summary.formula (Hmisc package), ddply (plyr package), remix
(remix package), melt and cast (reshape package) and sqldf (sqldf
package).

Of these summaryBy in the doBy package is particularly easy to specify
and produces a data frame:

library(doBy)
summaryBy(uptake ~ Type, data = CO2, FUN = c(mean, sd))

remix and summary.formula in Hmisc have particularly attractive output
but do not produce data frames. ?Hmisc even has a plot method. ?The
specification to remix is also simple here and, in fact, is identical
to the summaryBy line above except it uses lower case fun. ?sqldf uses
SQL for the specification which may be an advantage if you know SQL
better than R.

On Fri, May 7, 2010 at 5:39 AM, Phil Wieland <phwiel at gmx.de> wrote:

I need to compute the mean and the standard deviation of a data set and
would
like to have the results in one table/data frame. I call tapply() two
times
and do then merge the resulting tables to have them all in one table. Is
there any way to tell tapply() to use the functions mean and sd within
one
function call? Something like tapply(data$response, list(data$targets,
data$conditions), c(mean, sd)).

Thanks in advance.
--
View this message in context:
http://r.789695.n4.nabble.com/Any-way-to-apply-TWO-functions-with-tapply-tp2133924p2133924.html
Sent from the R help mailing list archive at Nabble.com.

David Winsemius, MD
West Hartford, CT

tapply does handle functions with vector outputs, e.g. using the built
in CO2 data set the following data frame is returned:

f <- function(x) data.frame(mean = mean(x), sd = sd(x))
do.call(rbind, tapply(CO2$uptake, CO2$Type, f))

? ? ? ? ? ?mean ? sd
Quebec ? ? ?33.5 9.67
Mississippi 20.9 7.82

Note that if you replace data.frame with c in f then you get a matrix
out instead of a data.frame.

There is also somewhat similar functionality in summaryBy (doBy
package), summary.formula (Hmisc package), ddply (plyr package), remix
(remix package), melt and cast (reshape package) and sqldf (sqldf
package).

Of these summaryBy in the doBy package is particularly easy to specify
and produces a data frame:

library(doBy)
summaryBy(uptake ~ Type, data = CO2, FUN = c(mean, sd))

remix and summary.formula in Hmisc have particularly attractive output
but do not produce data frames. ?Hmisc even has a plot method. ?The
specification to remix is also simple here and, in fact, is identical
to the summaryBy line above except it uses lower case fun. ?sqldf uses
SQL for the specification which may be an advantage if you know SQL
better than R.

On Fri, May 7, 2010 at 5:39 AM, Phil Wieland <phwiel at gmx.de> wrote:

I need to compute the mean and the standard deviation of a data set and would
like to have the results in one table/data frame. I call tapply() two times
and do then merge the resulting tables to have them all in one table. Is
there any way to tell tapply() to use the functions mean and sd within one
function call? Something like tapply(data$response, list(data$targets,
data$conditions), c(mean, sd)).

Thanks in advance.
--
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Sent from the R help mailing list archive at Nabble.com.

As pointed out to me offline, data.table should be added to the list
of relevant packages as well. ?Its primary advantage is for large data
sets as it is very fast. ?Its interface does take some getting used to
but its most recent version on CRAN does have several vignettes which
should ease learning.