To summarize, we have discussed how to handle missing data values and manipulate dates and time series in pandas. We also took a brief detour to investigate the plotting functionality in pandas using matplotlib. Handling missing data plays a very important part in the preparation of clean data for analysis and prediction, and the ability to plot and visualize data is an indispensable part of every good data analyst's toolbox.

In the next chapter, we will do some elementary data analysis on a real-world dataset where we will analyze and answer basic questions about the data. For further references about these topics in pandas, please take a look at the official documentation at http://pandas.pydata.org/pandas-docs/stable/index.html.