Description
The pandas library represents a very efficient and convenient tool for data manipulation, but sometimes hides unexpected pitfalls which can arise in various and sometimes unintelligible ways.
By briefly referring to some aspects of the internals, I will review specific situations in which a change of approach can, for instance, make a difference in terms of performance.
UPDATE (April 12, 2017) - SLIDES: the talk had very few slides; still, you can find those few, together with the notebooks I used live, here.