Introduction

Python and its analytical libraries, such as pandas and Matplotlib, make it very easy to perform both simple and complex statistical calculations on many types of datasets. This chapter introduces the first steps for any statistical analysis: defining and understanding the problem, loading and preparing the dataset, and after that, understanding the variables individually and exploring some relationships between them.

This chapter consists of three sections: in the first section, we introduce the dataset we will be using in this chapter along with a hypothetical (yet very realistic) business problem. Then we load the dataset and perform many of the common tasks of data preparation, including changing variable types and filtering for useful observations. With the dataset ready, the second section presents a brief conceptual introduction to the main metrics of descriptive statistics, then this knowledge is immediately applied to the dataset we are working with. As part...