Handling Missing Data via @OReillyMedia @jakevdp

In most data science tutorials, data is presented as clean and homogeneous. In the real world, getting pristine data is cause for celebration. In the latest instalment of the Python Data Science Handbook (Early Release), Jake VanderPlas looks at how to use built-in Pandas tools for handling missing data in Python.  Great article on Python functionality for something that we all have issues with..