pandas provides a comprehensive set of data structures for working with and manipulating data and performing various statistical and financial analyses. The two primary data structures in pandas are Series and DataFrame. In this chapter, we will examine the Series object and how it extends a NumPy ndarray to provide operations such as indexed data retrieval, axis labeling, and automatic alignment. Then, we will move on to examine how DataFrame extends the capabilities of Series to use columnar/tabular data, which can be of more than one data type.

The intention of this chapter is to be not only a refresher for those with basic familiarity with pandas, but also a means by which someone who is not initiated with pandas can gain enough familiarity with the two data structures and have a good foundation as we move into more finance-related subjects in later chapters. We will not cover all the details of using Series and DataFrame but will focus...