Sync your home directories on ACCRE and the local.Find the function you're looking for in R.R clinic this week: Regression Modeling Strategies.Comparison of plots using Stata, R base, R lattice.JBrowse: a JavaScript Based Genome Browser.What happens when a consumer genetics company goes.If you use SPSS, SAS, MATLAB, or something else, post the code in a comment here and send me a picture or link to the plot and I'll post it here.
#STATA HISTOGRAMS HOW TO#
I'm ordering the ggplot2 book (Amazon, ~$50), so as I figure out how to do more with ggplot2 I'll post more comparisons like this. And it required the 2nd shortest command, only 3 characters longer than the Stata equivalent. The black bars on the light-gray background have a good data-ink ratio. There are no unnecessary lines delimiting the bins, and the binwidth is appropriate. The default plot made by ggplot2 is just hands-down good-looking. It uses density for the vertical axis, which may not mean much to non-statisticians. Stata's default plot looks very similar to lattice, but again uses a very unattractive color scheme. The vertical axis is proportion of total. You lose some information especially on the bottom plot towards the right tail. Also, I'm not sure why the axis labels switch sides every other plot, and the ticks on top of the plot are probably unnecessary. The lattice package in R does a little better perhaps, but the default color scheme is visually less than stellar. By default, the base graphics system gives you counts (frequency) on the vertical axis. (If you can shorten this, please comment). R's base graphics give you a rather spartan plot, with very wide bins. Again I'll concede that all of the above graphing systems give you an incredible amount of control of every aspect of the graph, but I'm only looking for what gives me the best out-of-the-box default plot using the shortest command possible. In my opinion ggplot2 is the clear winner.