[R] How to perform a grouped shapiro wilk test on dataframe

[arun]

Hi,
Try this:
dat1<- read.csv("sample.csv",sep="\t",stringsAsFactors=FALSE)
 with(dat1,tapply(COUNTS,list(ACTIVITY),function(x) if (length(unique(x))==1) NA else shapiro.test(x)))
#$activity1
#[1] NA

#$activity2

#    Shapiro-Wilk normality test

#data:  x
#W = 0.4588, p-value = 8.025e-11
#

#$activity3
#
    Shapiro-Wilk normality test
#
#data:  x
#W = 0.7283, p-value = 3.76e-07
library(plyr) 
ddply(dat1,.(ACTIVITY), summarise, Pval=if(length(unique(COUNTS))==1) NA else shapiro.test(COUNTS)$p.value)
#   ACTIVITY         Pval
#1 activity1           NA
#2 activity2 8.025059e-11
#3 activity3 3.760396e-07

A.K.



----- Original Message -----
From: ramoss <ramine.mossadegh at finra.org>
To: r-help at r-project.org
Cc: 
Sent: Friday, April 5, 2013 10:50 AM
Subject: [R] How to perform a grouped shapiro wilk test on dataframe

Hello,

I was wandering if it is possible to perform on a dataframe called 'all' a
shapiro wilk normality test for COUNTS by variable Group

ACTIVITY?  Could it be done using plyer?  I saw an eg that applies to an
array but not to a dataframe:

lapply(split(dataset1$Height,dataset1$Group),shapiro.test)

Any thoughts would be much appreciated.

My dataframe is in shape:

dat       ACTIVIT  COUNTS
1/1/13   XXXX      43
..
..
1/31/13 XXXX    60
1/1/13   YYYY     40
..
..
1/31/13 YYYY  10
etc  going for 3 months.



--
View this message in context: http://r.789695.n4.nabble.com/How-to-perform-a-grouped-shapiro-wilk-test-on-dataframe-tp4663438.html
Sent from the R help mailing list archive at Nabble.com.

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.