Hi Aren, I was busy thinking about how to make what you wanted, and I missed that you were working with hours from a day. That being the case, you may think about a circular graph. The attached plots show two different ways of working with the same data.
Cheers,
Josh
set.seed(10)
x <- sample(0:23, 10000, TRUE, prob = sin(0:23)+1)
require(ggplot2) # graphing package
## regular barplot
p <- ggplot(as.data.frame(table(x)), aes(x = x, y = Freq)) +
geom_bar()
## using circular coordinates
p2 <- p + coord_polar()
## print them
print(p)
print(p2)
## just if you're interested, the code to
## put the two plots side by side
require(grid)
dev.new(height = 6, width = 12)
grid.newpage()
pushViewport(vpList(
viewport(x = 0, width = .5, just = "left", name = "barplot"),
viewport(x = .5, width = .5, just = "left", name="windrose")))
seekViewport("barplot")
grid.draw(ggplotGrob(p))
seekViewport("windrose")
grid.draw(ggplotGrob(p2))
On Sun, Jan 1, 2012 at 7:59 AM, Aren Cambre <a...@arencambre.com> wrote:
> On Sun, Jan 1, 2012 at 5:29 AM, peter dalgaard <pda...@gmail.com> wrote:
>> Exactly. If what you want is a barplot, make a barplot; histograms are for
>> continuous data. Just remember that you may need to set the levels
>> explicitly in case of empty groups: barplot(table(factor(x,levels=0:23))).
>> (This is irrelevant with 100K data samples, but not with 100 of them).
>>
>> That being said, the fact that hist() tends to create breakpoints which
>> coincide with data points due to discretization is arguably a bit of a
>> design error, but it is age-old and hard to change now. One way out is to
>> use truehist() from MASS, another is to explicitly set the breaks to
>> intermediate values, as in hist(x, breaks=seq(-.5, 23.5, 1))
>
> Thanks, everybody. I'll definitely switch to barplot.
>
> As for continuous, it's all relative. Even the most continuous dataset
> at a scale that looks pretty to humans may have gaps between the
> values when you "zoom in" a lot.
>
> Aren
--
Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, Statistical Consulting Group
University of California, Los Angeles
https://joshuawiley.com/
plots.pdf
Description: Adobe PDF document
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