R help - Dec 2012 - Best way to coerce numerical data to a predetermined histogram bin?

Folks:

Say I have a set of histogram breaks:

breaks=c(1:10,15)

# With bin ids:

bin_ids=1:(length(breaks)-1)

# and some data (note that some of it falls outside the breaks:

data=runif(min=1,max=20,n=100)

***

What is the MOST EFFICIENT way to "classify" data into the histogram
bins
(return the bin_ids) and, say, return NA if the value falls outside of the
bins.

By classify, I mean if the data value is greater than one break, and less
than or equal to the next break, it gets assigned that bin's ID (note that
length(breaks) = length(bin_ids)+1)

Also note that, as per this example, the bins are not necessarily equal
widths.

I can, of course, cycle through each element of data, and then move through
breaks, stopping when it finds the correct bin, but I feel like there is
probably a faster (and more elegant) approach to this.  Thoughts?

--j





-- 
Jonathan A. Greenberg, PhD
Assistant Professor
Department of Geography and Geographic Information Science
University of Illinois at Urbana-Champaign
607 South Mathews Avenue, MC 150
Urbana, IL 61801
Phone: 217-300-1924
AIM: jgrn307, MSN: jgrn307@hotmail.com, Gchat: jgrn307, Skype: jgrn3007

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Sent from my phone. Please excuse my brevity.

Jonathan Greenberg <jgrn at illinois.edu> wrote:
>Folks:
>
>Say I have a set of histogram breaks:
>
>breaks=c(1:10,15)
>
># With bin ids:
>
>bin_ids=1:(length(breaks)-1)
>
># and some data (note that some of it falls outside the breaks:
>
>data=runif(min=1,max=20,n=100)
>
>***
>
>What is the MOST EFFICIENT way to "classify" data into the
histogram
>bins
>(return the bin_ids) and, say, return NA if the value falls outside of
>the
>bins.
>
>By classify, I mean if the data value is greater than one break, and
>less
>than or equal to the next break, it gets assigned that bin's ID (note
>that
>length(breaks) = length(bin_ids)+1)
>
>Also note that, as per this example, the bins are not necessarily equal
>widths.
>
>I can, of course, cycle through each element of data, and then move
>through
>breaks, stopping when it finds the correct bin, but I feel like there
>is
>probably a faster (and more elegant) approach to this.  Thoughts?
>
>--j

?findInterval


On Thu, Dec 6, 2012 at 3:00 PM, Jonathan Greenberg
<jgrn@illinois.edu>wrote:
> Folks:
>
> Say I have a set of histogram breaks:
>
> breaks=c(1:10,15)
>
> # With bin ids:
>
> bin_ids=1:(length(breaks)-1)
>
> # and some data (note that some of it falls outside the breaks:
>
> data=runif(min=1,max=20,n=100)
>
> ***
>
> What is the MOST EFFICIENT way to "classify" data into the
histogram bins
> (return the bin_ids) and, say, return NA if the value falls outside of the
> bins.
>
> By classify, I mean if the data value is greater than one break, and less
> than or equal to the next break, it gets assigned that bin's ID (note
that
> length(breaks) = length(bin_ids)+1)
>
> Also note that, as per this example, the bins are not necessarily equal
> widths.
>
> I can, of course, cycle through each element of data, and then move through
> breaks, stopping when it finds the correct bin, but I feel like there is
> probably a faster (and more elegant) approach to this.  Thoughts?
>
> --j
>
>
>
>
>
> --
> Jonathan A. Greenberg, PhD
> Assistant Professor
> Department of Geography and Geographic Information Science
> University of Illinois at Urbana-Champaign
> 607 South Mathews Avenue, MC 150
> Urbana, IL 61801
> Phone: 217-300-1924
> AIM: jgrn307, MSN: jgrn307@hotmail.com, Gchat: jgrn307, Skype: jgrn3007
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@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.
>


-- 
Gregory (Greg) L. Snow Ph.D.
538280@gmail.com

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