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 saw how a great deal 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.

Having picked up the fundamentals, it's time to proceed to data analysis with the commonly used functions in Chapter 4, Statistics and Linear Algebra. This includes the usage of staple statistical and numerical functions.

The reader is encouraged to read the books mentioned in the references section for exploring Pandas in further detail and depth.