This book gives you the perfect foray into data analysis. We discuss data analysis in Python in a way that will benefit you irrespective of your expertise level in Python. At the beginner level, you will appreciate the simple but elaborate approach we use to introduce you to basic Python concepts necessary for data analysis. With this knowledge, you can establish your foundation in data analysis, and build on that over time as you become accustomed to more complex subjects.

For intermediate and expert users, you can also benefit from this book by using it as a reminder of some of the key points that define data science. When you dwell in a field for a long time, it is easy to take some things for granted. This happens to many programmers and developers. This book reminds you of the basic building principles that have helped you become one of the best data analysts in your field.

Python libraries are some of the most important features in Python programming. The libraries help you perform tasks that would have otherwise been impossible to perform, or cumbersome. We discuss the major Python libraries you will use all the time, and highlight the main ones relevant to data analysis so you can get the distinction.

Take note that data science is not an isolated subject. Most of the disciplines that involve Python programming depend on data, so you can expect to use the knowledge learned in this book in other fields, too. For example, when you advance into machine learning, your ability to perform exceptional data analysis will be required to help you build and train relevant machine learning models. Therefore, this book will not just get you ready for data analysis, it will prepare you for various fields in Python programming, including artificial intelligence, deep learning, and machine learning.

Besides discussing the main Python libraries, we investigate the major data analysis libraries like Pandas and Matplotlib in-depth. These libraries will form the foundation of most of the data analysis work you perform over the years. Data analysis in Python will help you become an all-rounded developer. The good thing about learning Python is that you can use the knowledge gained to further your career in other programming languages like R. It is important to learn Python for data analysis from a conceptual and fundamental framework so that you set the right tone on which you can build your career further and advance into the future.

Unlike other books, I don't claim that this book will make you a master of data science after a single read. That's not realistic, in fact, it's even a bit absurd. What I claim is that you will definitely learn about the basics. The rest is practice. The more you practice the better you code.