On 08/02/2011 01:07 PM, Dennis Murphy wrote: > In addition to the other responses (all of which I liked), a couple of > other alternatives to consider are 2D density plots (see ?kde2d in the > MASS package, for example) or geom_tile() in the ggplot2 package, > which you can think of as a 3D histogram projected to 2D with color > corresponding to (relative) frequency, as suggested by Paul Hiemstra. > geom_tile() is a discretized, gridded version of a hexbin plot, but I
When using geom_tile you need to bin the data yourself. I much prefer using stat_bin2d which does all the work for you. cheers, Paul > would start with the hexbin myself. I echo KOH's comment: make sure > you remove the outliers first, especially that one in the upper left > corner :) > > After looking at your plot, here's my question: why would you plot > kills/minute vs. minutes played? Doesn't the first variable render the > second one moot? Wouldn't kills vs. minutes played be a more relevant > (scatter)plot? If you have information on the skill level of the > players, you could incorporate that information into the plot as well. > There are several nice ways to go if this is the case. > > If kills/minute is the more appropriate measure, a univariate density > plot would make sense, or a histogram. > > HTH, > Dennis > > On Mon, Aug 1, 2011 at 10:26 PM, DimmestLemming <nicoadams...@gmail.com> > wrote: >> I'm working with a lot of data right now, but I'm new to R, and not very good >> with it, hence my request for help. What type of graph could I use to >> straighten out things like... >> >> http://r.789695.n4.nabble.com/file/n3711389/Untitled.png >> >> ...this? >> >> I want to see general frequencies. Should I use something like a 3D >> histogram, or is there an easier way like, say, shading? I'm sure these are >> both possible, but I don't know which is easiest or how to implement either >> of them. >> >> Thanks! >> >> -- >> View this message in context: >> http://r.789695.n4.nabble.com/Clean-up-a-scatterplot-with-too-much-data-tp3711389p3711389.html >> Sent from the R help mailing list archive at Nabble.com. >> >> ______________________________________________ >> 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. >> > ______________________________________________ > 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. -- Paul Hiemstra, Ph.D. Global Climate Division Royal Netherlands Meteorological Institute (KNMI) Wilhelminalaan 10 | 3732 GK | De Bilt | Kamer B 3.39 P.O. Box 201 | 3730 AE | De Bilt tel: +31 30 2206 494 http://intamap.geo.uu.nl/~paul http://nl.linkedin.com/pub/paul-hiemstra/20/30b/770 ______________________________________________ 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.
