Chapter 3. The Pandas Primer

The Pandas is named after panel data (an econometric term) and Python data analysis, and is a popular open source Python library. We shall learn about basic Pandas functionalities, data structures, and operations in this chapter.

The official Pandas documentation insists on naming the project pandas in all lowercase letters. The other convention the Pandas project insists on is the import pandas as pd import statement.

We will follow these conventions in this text.

In this chapter, we will install and explore Pandas. Then, we will acquaint ourselves with the two central Pandas data structures--DataFrame and Series. After that, you will learn how to perform SQL-like operations on the data contained in these data structures. Pandas has statistical utilities, including time-series routines, some of which will be demonstrated. The topics we will look at are as follows:

• Installing and exploring Pandas
• The Panda DataFrames
• The Panda Series
• Querying data in Pandas
• Statistics with Pandas DataFrames
• Data aggregation with Pandas DataFrames
• Concatenating and appending DataFrames
• Joining DataFrames
• Handling missing values
• Dealing with dates
• Pivot tables