On Tue, 26 Feb 2008, Andre Nathan wrote: > I know about stem, but the data set has 1 million points, so it's not > very useful here. I want to avoid binning just to have an idea about the > shape of the distribution, before deciding how I'll bin it.
Ideas: 1) use a much smaller sample of the data (1000 should suffice) 2) use a density plot (see ?density), perhaps on a sub-sample (although as that will bin the data on a fine grid, this does not matter much). > > Andre > > On Tue, 2008-02-26 at 16:20 -0600, roger koenker wrote: >> take a look at >> >> ?stem >> >> There is still a place for handtools in the age of integrated >> circuits. Of course, avoiding binning isn't really desirable. >> >> url: www.econ.uiuc.edu/~roger Roger Koenker >> email [EMAIL PROTECTED] Department of Economics >> vox: 217-333-4558 University of Illinois >> fax: 217-244-6678 Champaign, IL 61820 >> >> >> On Feb 26, 2008, at 4:10 PM, Andre Nathan wrote: >> >>> Hello >>> >>> I need to plot a histogram, but insted of using bars, I'd like to plot >>> the data points. I've been doing it like this so far: >>> >>> h <- hist(x, plot = F) >>> plot(y = x$counts / sum(x$counts), >>> x = x$breaks[2:length(x$breaks)], >>> type = "p", log = "xy") >>> >>> Sometimes I want to have a look at the "raw" data (avoiding any kind >>> of >>> binning). When x only contains integers, it's easy to just use bins of >>> size 1 when generating h with "breaks = seq(0, max(x))". >>> >>> Is there any way to do something similar when x consists of fractional >>> data? What I'm doing is setting a small bin length (for example, >>> "breaks >>> = seq(0, 1, by = 1e-6)", but there's still a chance that points will >>> be >>> grouped in a single bin. >>> >>> Is there a better way to do this kind of "raw histogram" plotting? >>> >>> Thanks, >>> Andre >>> >>> ______________________________________________ >>> 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. > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ 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.
