On 2013-04-03 14:59, Sarah Goslee wrote:
Of course it can. Use the mode() in the same way you used the mean() function.
You didn't provide a reproducible example, so I can't provided tested
code, but I would think that you can add
mode=mode(COUNTS) to the ddply() arguments.
?mode will direct you to the help page for _storage_ mode of an object.
That's not likely what the OP had in mind. It seems that what s/he
wants is the "most frequent value". This is (usually) a pretty useless
piece of information, but there are a number of packages that do
provide it.
To the OP:
Install package sos and then do findFn("mode") to see what's available.
E.g. packages, pracma, asbio, dprep, rattle and many others.
Do note that they handle the multimodal situation differently.
Or, write your own, perhaps using table() and which.max().
Peter Ehlers
all1 <- ddply(all,"ACT_NAME", summarise, mean=mean(COUNTS), sd=sd(COUNTS),
q25=quantile(COUNTS,.25),median=quantile(COUNTS,.50),
q75=quantile(COUNTS,.75),
q90=quantile(COUNTS,.90), q95=quantile(COUNTS,.95),
q99=quantile(COUNTS,.99) )
On Wed, Apr 3, 2013 at 5:36 PM, Mossadegh, Ramine N.
<ramine.mossad...@finra.org> wrote:
So you mean it cannot be calculated within plyer?
-----Original Message-----
From: Sarah Goslee [mailto:sarah.gos...@gmail.com]
Sent: Wednesday, April 03, 2013 5:36 PM
To: Mossadegh, Ramine N.; r-help
Subject: Re: [R] Can package plyr also calculate the mode?
If you type
?mode
at an R prompt you will be able to read the help for the mode() function.
On Wed, Apr 3, 2013 at 5:34 PM, Mossadegh, Ramine N.
<ramine.mossad...@finra.org> wrote:
I tried mode=?mode(COUNTS) but that doesn't work.
-----Original Message-----
From: Sarah Goslee [mailto:sarah.gos...@gmail.com]
Sent: Wednesday, April 03, 2013 5:32 PM
To: Mossadegh, Ramine N.
Cc: r-help
Subject: Re: [R] Can package plyr also calculate the mode?
Sure, you can add the mode in, following the format by the other summary
statistics.
?mode
Sarah
On Wed, Apr 3, 2013 at 5:25 PM, ramoss <ramine.mossad...@finra.org> wrote:
I am trying to replicate the SAS proc univariate in R. I got most of
the stats I needed for a by grouping in a data frame using:
all1 <- ddply(all,"ACT_NAME", summarise, mean=mean(COUNTS), sd=sd(COUNTS),
q25=quantile(COUNTS,.25),median=quantile(COUNTS,.50),
q75=quantile(COUNTS,.75),
q90=quantile(COUNTS,.90), q95=quantile(COUNTS,.95),
q99=quantile(COUNTS,.99) )
So I got the mean, median std dev, quantiles etc.
IS there any way I can add the mode to the mixt. Thanks ahead for any
suggestions.
--
Sarah Goslee
http://www.functionaldiversity.org
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