I just published a blog post proclaiming the implementation of the function MosaicPlot that gives visual representation of the contingencies of categorical variables in a list of records. The blog post has examples and explanations:
http://mathematicaforprediction.wordpress.com/2014/03/17/mosaic-plots-for-data-visualization/

If we consider the census income data set known as the "adult data set" that is summarized in this table:



we visualize the co-occurence of (categorical variable) values with mosaic plots like this one:



By comparing the sizes of the rectangles corresponding to values “Bachelors”, “Doctorate”, “Masters”, and “Some-college” on the “sex vs. education” mosaic plot we can see that the fraction of men that have finished college is larger than the fraction of women that have finished college.
We can further subdivide the rectangles according the co-occurrence frequencies with a third categorical variable. We are going to choose that third variable to be “income”, the values of which can be seen as outcomes or consequents of the values of the first two variables of the mosaic plot.



From the mosaic plot "sex vs. education vs. income" we can make the following observations.1. Approximately 75% of the males with doctorate degrees or with a professional school degree earn more than $50000 per year.2. Approximately 60% of the females with a doctorate degree earn more than $50000 per year.3. Approximately 45% of the females with a professional school degree earn more than $50000.4. Across all education type females are (much) less likely to earn more than $50000 per year.