Tips on using Pandas
Read Python for Data Analysis
Python for Data Analysis is very good as both a tutorial and reference. It also covers using iPython.
For many things it seems initially that Python alone will suffice. It probably will. However, using Pandas gives you a lot of well implemented functionality for free and is a good choice for open ended projects.
Functional not OOP
Try to write functional (functions accepting functions as arguments) code rather than complex objects. For flexible, interactive analysis this is usually the way to go.
Don't just use Pandas
Use Continuum.io's Anaconda distribution of Python
Some Python libraries are tricky to compile, this does it for you: Anaconda. The basic version is fine for most uses, but even the more advanced one is free for Academic users. This allows you to use things like Numba (roughly a Python JIT) which seems to be impossible to compile on Mac.