Description
Using the pandas python library requires a shift in thinking that is not always intuitive to those who use it. This talk will take a deep dive into the underlying data structure of pandas to explain why it performs the way it does under certain circumstances. It will explain why a MultiIndex DataFrame takes up less memory than it's simple counter part, why groupby should never be run on a non-MultiIndexed DataFrame, why the example documentation for the pandas apply function is an example of how not to use it, and how not taking the time to normalize data can affect performance.