The next best thing is the ability to save and restore your entire state (plots, command history, variable and array contents, scripts, notes. and its easy to come back to after you set it aside for a while (use the gui till you remember the commands). The best part is that it is both GUI and command line so you have the best of both worlds. its script language is VERY fast (around half as fast as C) compared to say Matlab. but for line plotting and data analysis I really like it. It's matrix format is clumsy compared to R or Matlab. I love igor and have used it for 12 years now. Or RWeb which lets you build CGI based interfaces to R (complete with graphs), though performance isn't exactly stellar (R has a pretty heavy launch penalty relative to most computational tasks)
#Unh sigmaplot software pdf
Until those arrive there's also Sweave (its in the tools package that ships), which while not really a GUI lets you combine LaTeX and R noweb style to generate some quite nice ps/pdf output (it deals with making sure the appropriate PDF or EPS files are around and whatnot). You can find info about some of this cutting edge stuff over at and I think There's also at least one person working on more interactive forms of documents (read: widgets and data in your paper controlling live graphing surfaces) which could be used to build GUIs as well.
Hopefully the GUI thing will improve over time-there's a project called ObveRsive (or something like that) thats gotten started within the last few months to put, from what I can tell, Stata/DataDesk types of things over R.There's been a great deal of interest in that from time to time.
#Unh sigmaplot software software
A wonderful piece of software that has been indispensible during my Ph. However, it can handle immense data sets, supports mathematical text (meaning you can throw a complicated equation into your graph and have it come out with publication-quailty finish) and can do some colour, three-dimensional plotting. There is no gui, so all fine tuning of the figures has to be done through the command line. R is multi-platform, capable of producing graphs in a number of formats (eps, ps, pdf, png etc), can be run in batch mode (great for simulations) and can produce very pretty graphics. If, on the other hand, he's going to be doing some real stats, then he should definitely investigate R as a solution. If the original poster isn't going to be doing complicated statistical analysis or curve-fitting (I mean, is he just ramming a straight line through his data cloud, or is he into splines and whatnot), then it probably isn't worth his time to learn the syntax.
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