faceting distr in terms of percents (nominal values)

[adam.l...@pnc.com]

Hi,

A couple of weeks ago Dennis answered my question as to how to bin (and facet) an interval variable so that its distribution is in terms of the percent of total.

It involved multiplying the density by the binwidth. However, this solution  not surprisingly does not work when the x axis is a nominal variable and binning is not required.

Does anyone know a solution to this problem?

Below is an example in which I would like the y axis to be the % of total instead of the frequency. Thanks for your help.

ggplot(diamonds,aes(cut))+geom_histogram()+facet_grid(clarity~color)


Adam Loveland

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[Dennis Murphy]

Hi Adam:

It appears that y = ..count../sum(..count..) works in this case. Compare

ggplot(diamonds, aes(x = cut, y = ..count..)) +
geom_histogram() +
facet_grid(clarity ~ color)

ggplot(diamonds, aes(x = cut, y = ..count../sum(count))) +
geom_histogram() +
facet_grid(clarity ~ color)

These look the same to me except for the y-axis scaling. This would
suggest that, when faceting is involved, the current behavior is
** y = ..count../sum(count) works for bar charts (i.e., when the
x-variable is a factor)
** y = k * ..density.. works for histograms (where the bins are of
fixed width k)

The above lines of code work the same when geom_histogram() is
replaced by geom_bar(). I would suggest raising an issue about this
because the 'rules' shouldn't depend on whether or not one is
faceting.

Technically, if you have a binwidth of 1 in a histogram, where x is
numeric, then a density histogram should be identical to a relative
frequency histogram. In ggplot2,

..density.. = ..count../(N * binwidth),

where N is the sample size ( = sum(..count..) ), and by default,
binwidth = (x_max - x_min)/30. Therefore, when you set the binwidth in
geom_histogram(), multiplying both sides of the above equation by
binwidth will give you the relative frequency. Moreover, when the
binwidth is 1, a density histogram is a relative frequency histogram.

This is easy to see by example:

g <- qplot(rnorm(100), geom = "histogram", binwidth = 1.5)
g2 <- ggplot_build(g)
g2$data

Pay attention to the count and density columns, and note that the
binwidths are 1.5.

In the case where x is a factor, the binwidth trick doesn't work as
pointed out in your example, but the relative frequency definition
does. Why this works for factor but not numeric x in the presence of
faceting I don't know; perhaps you should raise this as an issue to
the developers:

https://github.com/hadley/ggplot2/issues



Dennis

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[adam.l...@pnc.com]

Thanks Dennis very much for the clarification! I don't feel bad asking the question, given the inconsistency you've pointed out.

I will raise the issue with the developers.





Adam Loveland

From:	Dennis Murphy <djm...@gmail.com>
To:	adam.l...@pnc.com
Cc:	ggplot2 <ggp...@googlegroups.com>
Date:	05/18/2013 12:55 AM
Subject:	Re: faceting distr in terms of percents (nominal values)
Sent by:	ggp...@googlegroups.com

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