This talk will covers ways that help process and analyse visualise data faster in Python. The primary focus is on the technique (should you optimise? what to optimise? how to optimise?) while covering libraries that help with this (line_profiler, Pandas, Numba, etc.)
Working with data in Python requires making a number of choices, ranging from the simple to the complex.
.. and so on. This session will explain how to benchmark code and share insights on the patterns of programming that make your application faster.