Python has become a dominant computer programming language for analyzing and visualizing scientific data, in part due to its concise, intuitive syntax and free availability without the purchase of an expensive license. The syntax of the language itself is easy to pick up, but learning how to plot, visualize, and analyze scientific data has required more effort in the past, as the relevant resources are spread across the Internet and can at times be confusing to the novice. This book is intended to provide a handy, clearly written tutorial on the most essential features of the language and its most widely used plotting and analysis libraries. Specifically, the author wrote it from the perspective of "What book would I want to have had when I was transitioning to Python from another programming language?" This book will be useful not only as a classroom text but also as a guide and reference for students, educators, and researchers who have some programming experience already and want to start quickly creating plots and analyzing data using Python. The author's assumption is that the reader has some experience programming, though not necessarily with Python. Although the new Python programmer may wish to read the book cover to cover, the book is organized such that the experienced Python programmer who wants to get started in plotting data can readily jump to the appropriate chapter. The last few chapters include topics that are more advanced, such as using regular expressions for matching text patterns, performing spectral analysis of data, and solving systems of linear equations.