[R] understanding integer divide (%/%)

ONKELINX, Thierry Thierry.ONKELINX at inbo.be
Wed Jan 3 14:29:14 CET 2007

This is due to the internal representation of 0.1, which is not exactly
0.1 but very close to it. If you want to do an integer divide, you
should only use integers to divide with.




ir. Thierry Onkelinx

Instituut voor natuur- en bosonderzoek / Reseach Institute for Nature
and Forest

Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance

Gaverstraat 4

9500 Geraardsbergen


tel. + 32 54/436 185

Thierry.Onkelinx op inbo.be



Do not put your faith in what statistics say until you have carefully
considered what they do not say.  ~William W. Watt

A statistical analysis, properly conducted, is a delicate dissection of
uncertainties, a surgery of suppositions. ~M.J.Moroney

-----Oorspronkelijk bericht-----
Van: r-help-bounces op stat.math.ethz.ch
[mailto:r-help-bounces op stat.math.ethz.ch] Namens Jeffrey Prisbrey
Verzonden: woensdag 3 januari 2007 14:21
Aan: r-help op stat.math.ethz.ch
Onderwerp: [R] understanding integer divide (%/%)

I am confused about why the following occurs:

> version
platform       i386-pc-mingw32             
arch           i386                        
os             mingw32                     
system         i386, mingw32               
major          2                           
minor          4.0                         
year           2006                        
month          10                          
day            03                          
svn rev        39566                       
language       R                           
version.string R version 2.4.0 (2006-10-03)
> 1 %/% 0.1
[1] 9
> 10 %/% 1
[1] 10

This effect led me into an trap when I tried to
classify a set of proportions based on the first
decimal place by integer dividing by 0.1.  Can someone
explain why this behavior occurs and give me an
insight into how to predict it?

-- Jeff

R-help op stat.math.ethz.ch mailing list
PLEASE do read the posting guide
and provide commented, minimal, self-contained, reproducible code.

More information about the R-help mailing list