This book is specially curated for managers, decisions makers and data users. It explains, from the ground level, how Python can be used for data analysis and visualization through its powerful libraries—NumPy, Pandas, Matplotlib, Seaborn and yfinance. These libraries provide ready-made functions that help us analyse data and create meaningful visualizations without requiring prior knowledge of programming.
Learning by Doing. The examples in this book use practical datasets resembling real-world situations from different domains. Each function is explained along with its code and the corresponding output, so that you can run the code, observe the results, and learn through hands-on practice. The functions, tools, and techniques explained here are not limited to the datasets used in the book; they can be applied to other datasets and real-world situations.