The materials for this chapter can be found on GitHub at https://github.com/stefmolin/Hands-On-Data-Analysis-with-Pandas/tree/master/ch_04. There are four notebooks that we will work through, each numbered according to when they will be used. The text will prompt when to switch. We will begin with the 1-querying_and_merging.ipynb notebook to learn about querying and merging dataframes. Next, we will move on to the 2-dataframe_operations.ipynb notebook to discuss data enrichment through operations such as binning, window functions, and pipes. For this section, we will use the function in the window_calc.py Python file.
The understanding_window_calculations.ipynb notebook contains some interactive visualizations for understanding window functions. This may require some additional setup, but the instructions are in the notebook.
Then, we will discuss aggregations...
