Pivot tables (also called contingency tables and cross tabulation tables) are a powerful means of data visualization and data summarization. When dealing with large data sets with multiple variables, or multiple datasets manually manipulating the pivot tables in WYSIWYG (what you see is what you get) spreadsheets can quickly become troublesome and error prone. In these instances it becomes preferred or even necessary to use a YAFIYGI (you ask for it you got it) model to automate all or part of the data summarization process.
There are already existing Python pivot table modules available. The ones I have found don't support multidimensional data, require Windows and Excel, or are incomplete and abandoned. They also are usually tailored towards an information technology audience as opposed to a scientific/research audience. On the other extreme are projects like PyTables. PyTables is an impressive undertaking but many datasets just aren't complex enough to justify the effort required to get data into PyTables. The pyvttbl module presented here offers a solution for datasets of "Goldilocks" complexity; too much for spreadsheets, but too little for coding custom solutions or configuring PyTables.

Obectives:

Examine your existence.
Build tools for this examination, developing physical computing and programming skills in the process.
Develop a final project that attends to the rest of you.