Summary
In this chapter, we focused on pandas—a Python data analysis library. This was an introductory tutorial about the basic pandas features and data structures. We realized that a lot of the pandas functionality mimics relational database tables, allowing us to query, aggregate, and manipulate data efficiently. NumPy and pandas work well together and make it possible to perform basic statistical analysis. At this point, you might be tempted to think that pandas is all we need for data analysis. However, there is more to data analysis than meets the eye.
The next chapter, Chapter 5, Retrieving, Processing, and Storing Data, will teach us skills that are essential, though they may not be considered data analysis by some people. We will go with ...
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