The time has come for us to being our journey into the pandas universe. We will start by exploring the main data structures we will encounter when working with pandas. Remember, data structures provide a format for organizing, managing, and storing data. Knowledge of pandas data structures will prove infinitely helpful when it comes to troubleshooting or looking up how to perform certain operations on the data. Keep in mind that these data structures are different for a reason: they were created for specific analysis tasks; we must remember that a given method may only work on a certain data structure, so we need to be able to identify the best structure for the problem we are looking to solve.

Next we will bring our first dataset into Python. We will learn how to create dataframes from other data structures in Python and read in files. Initially, we may wonder why would ever need to create dataframes from other Python data structures; however, if we ever want to test something quickly, create our own data, pull data from an API, or repurpose Python code from another project, then we will find this knowledge indispensable. Finally, we will master ways to inspect, describe, filter and summarize our data.

This section will get us comfortable working with some of the basic, yet powerful, operations we will be performing when conducting our data analyses with pandas.