Before diving into this book, it’s helpful to have an intermediate understanding of either R or Python (or both), including intermediate-level proficiency in data manipulation and analysis using libraries such as pandas, NumPy, and the tidyverse. Familiarity with Excel basics, such as navigating spreadsheets and performing simple data manipulations, is also assumed. Additionally, a basic understanding of statistical concepts and data visualization techniques will be beneficial for following along with the examples and exercises presented throughout the book.

An installation guide for the relevant packages and tools will be provided in each chapter.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

Disclaimer

The authors acknowledge the use of cutting-edge AI, such as ChatGPT, with the sole aim of enhancing the language and clarity within the book, thereby ensuring a smooth reading experience for readers. It's important to note that the content itself has been crafted by the authors and edited by a professional publishing team.