Produce SAS Proc Freq Output in R

I have never been a huge fan or advocate of SAS, and actually recommend using other SAS alternatives, but I am somewhat addicted to the SAS Proc Freq procedure and its output tables.  Its a nice way to not only visualize the data but also to get some useful summary statistics.  I have been using the R table command for a while and in most cases combined with margin.table or prop.table it suffices to summarize the data.  Recently, I have been in need of summary statistics for the tables as well.  This can be accomplished easy enough using the R chisq.test or fisher.test commands, but still doesn't quite provide the fluid integration of data visualization and summary statistics that the SAS Proc Freq output provides.  Today I came across the R package CrossTable.  This procedure, part of the gmodels library, provides formatted output very similar to that of Proc Freq.  So much so, it even uses the same ascii characters to delineate cell boundaries.  There is a bit of playing around with options and such to get the exact statistics and percentages and such you would like, but overall a very nice (a not to mention free) alternative to SAS's Proc Freq output.  Below is an example table I created.

Statistical Package Alternatives to SAS

Lets face it, SAS (aka Statistical Analysis Software) is an archaic program that is difficult to learn, cumbersome to code, and slow to implement calculations.   While graphics are improving, graphs are still hard to customize and lag far behind those of other programs.  In addition, yearly licensing fees were more than enough to scare me away, especially since there are a lot of open source statistical programing packages that are just as good, if not better than SAS.

So what are these alternatives to SAS?  Here is my attempt to make a list of valid alternatives to SAS.  Some may be more powerful or better tailored to specific niches than others, but all are capable of carrying out basic statistical tests.  The list is alphabetical with major SAS contenders highlighted in bold.

Epi Info - simple CDC tool for clinicians
Excel - basic, but there are some useful plugins
gretl - open source with econometrics focus
KXEN - seems more geared towards industry
Mathematica - used it doing physics research, seemed powerful at the time, but a long time ago
MATLAB - again, maybe more for engineers and such, but has statistical functionality
Minitab - quite accessible to those with little computer knowledge
Octav - open source, similar to MATLAB
OpenEpi - online, JAVA based statistical applets
Python - more of a programming language, but has statistical packages you can load
R - open source, thousands of libraries and active community of users
S-Plus - similar to R, S based dialect, could not find a link to this
Sage- unified interface of open source packages
SPSS - point and click, with some scripting options, crashes a lot
Stata - command line or point and click, powerful but not bloated
STATISTICA - markets themselves as a user friendly SAS alternative

That's about as exhaustive of a list as I can come up with.  If I missed something important please comment and let me know about it.  Hopefully I have been able to convince you there are plenty of excellent alternative statistical programming packages to SAS that are worth your time looking into.  In my opinion, R and Stata are the two clear front runners, particularly R since it is free and open source.  Happy hunting for a SAS replacement!