Interpolating missing values (NaN) in Pandas data frames

Missing data is a fact of life. Fortunately, Pandas provides us with several techniques to handle it, including two ways to interpolate values — provide plausible alternatives to NaN in our data sets. In this video, I show you two of these techniques, including the powerful "interpolate" method for data frames.

The Jupyter notebook for this video, and all of my videos, are at https://github.com/reuven/youTube-notebooks.

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