دانلود کتاب پایتون برای اکسل – یک محیط مدرن برای اتوماسیون و تحلیل داده‌ها

This book is organized into six parts. The first two parts teach you the fundamentals of Python and pandas, so you’ll need a bit of patience until we start using Python and Excel together in Part III. This is intentional: if you want the fast track, there are plenty of resources that jump straight into Python in Excel or pandas. However, as soon as you need to adapt or debug the code from these tutorials, it’s easy to get stuck. By building a solid foundation in Parts I and II, you’ll understand the concepts and tools you’ll rely on in later chapters. This approach takes a bit longer upfront, but it will save you time and frustration in the long run. Part I, “Introduction to Python”: Chapter 1 looks into the reasons why Python is such a good companion for Excel. Chapter 2 introduces the tools we’ll be using in this book: the uv package manager, the Terminal, Visual Studio Code, and Jupyter notebooks. Chapter 3 will teach you enough Python to be able to follow the rest of this book. Part II, “Introduction to pandas”: Chapter 4 gives you a very short introduction to NumPy, which is the backbone of many scientific packages, including pandas. pandas, the topic of Chapter 5, is one of the most popular Python libraries for data analysis. Its core data structure, the DataFrame, is similar to a spreadsheet and can serve as a programmatic alternative to an Excel workbook. Part III, “Python in Excel”: Chapter 6 covers the basics of Python in Excel, the official Microsoft solution. Python in Excel is centered around the concept of a twodimensional Jupyter notebook that unlocks better analytics and visualization by giving you access to the broader pandas ecosystem. Chapter 7 teaches you how to use pandas with time series. For this