Thanks for your help.
As far as your question below is concerned, the data frame arose as a
result of some data cleaning on an original data frame, which was
changed into a table, modified, and changed back to a data frame:
ttcrmean<- as.table(by(ngbe[,'Log10'],
list(Time=ngbe$Time,Temp=ngbe$Temp,Conc=ngbe$Conc,Repl=ngbe$Replicate),
mean))
for (k in 1:3) { #fix-up time zeroes
for (l in 1:5) { #replicates
t0val<- ttcrmean[1,3,k,l]
for (j in 1:4) { #temps
ttcrmean[1,j,k,l]<- t0val
} #j
} #l
} #i
df<- na.omit(as.data.frame(ttcrmean))
colnames(df)[5]<- 'Log10'
At 12:51 AM 6/5/2011, Joshua Wiley wrote:
Hi Robert,
<snip>
I would also look into *why* those numeric columns are being stored as
factors in the first place. If you are reading the data in with
read.table() or one of its wrapper functions (like read.csv), then it
would be better to preempt the storage as a factor altogether rather
than converting back to numeric. For example, perhaps something is
being used to indicate missing data that R does not recognize (e.g.,
SAS uses "."). Specifying na.strings = ".", would fix this. See
?read.table for some of the options available.
<snip>
================================================================
Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: r...@lcfltd.com
Least Cost Formulations, Ltd. URL: http://lcfltd.com/
824 Timberlake Drive Tel: 757-467-0954
Virginia Beach, VA 23464-3239 Fax: 757-467-2947
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