This is a very classic Python data analysis book. There is a progressive relationship between each chapter. It is suitable for reading after getting started with Python (such as "Python Programming, From Introduction to Practice"). This book is specifically for the field of data analysis. I read it carefully and typed the code again. I had no clue at first and made slow progress, but it gradually became clearer. Learning programming requires more practice, which is difficult for people without foundation, because there is no way to start. My experience is that when your foundation is not solid, you should read more, memorize more, summarize more, and build your own thinking framework.
This book is written by Wes McKinney, the founder of the pandas project, and introduces in detail the specific details and basic points of using Python to operate, process, clean and organize data. The second edition is fully revised and updated for Python 3.6, covering new versions of pandas, NumPy, IPython and Jupyter, and adding a large number of practical cases, which can help you efficiently solve a series of data analysis problems.
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