In this chapter, we saw that there are various ways to rearrange data in pandas. We can group data using the pandas.groupby operator and the associated methods on groupby objects. We can merge and join Series and DataFrame objects using the concat, append, merge, and join functions. Lastly, we can reshape and create pivot tables using the stack/unstack and pivot/pivot_table functions. This is very useful functionality to present data for visualization or prepare data for input into other programs or algorithms.

In the next chapter, we will examine some useful tasks in data analysis for which we can apply pandas, such as processing time series data and how to handle missing values in our data.

To have more information on these topics on pandas, please take a look at the official documentation at http://pandas.pydata.org/pandas-docs/stable/.