I was excited to be able to talk at two recent data-centric conferences in New York. They touch on some related subjects, with the PyData talk being a lot more technical and having to do with low-level architecture in pandas and engineering work I've been doing this year at DataPad.
Before anyone yells at me, I'm going to revisit the PostgreSQL benchmarks in my PyData talk at some point as the performance would be a lot better with the data stored in fully-normalized form (a single fact table with all primitive data types and auxiliary tables for all of the categorical / string data. Laborious but the way a DBA would set it up rather than having a single table with VARCHAR columns).
Practical Medium Data Analytics with Python (10 Things I Hate About pandas, PyData NYC 2013) from Wes McKinney