The first 2 Chapter Python elements of grammar ,IPython and Jupyter Notebooks

When I was there 2011 Years and 2012 When I wrote the first edition of this book in , Available learning Python There are few resources for data analysis . It's a chicken and egg problem in part ： The library we use now , such as pandas、scikit-learn and statsmodels, It was relatively immature at that time .2017 year , Data Science 、 There are many resources for data analysis and machine learning , The original general scientific computing has been extended to computer scientists 、 Physicists and other researchers . Study Python And excellent books to become software engineers .

Because this book focuses on Python Data processing , For some Python The data structure and the characteristics of the library are inevitably insufficient . therefore , This chapter and Chapter 3 This chapter is only enough for you to learn the rest of the book .

Let me see , There is no need to be proficient in data analysis Python. I encourage you to use IPython shell and Jupyter Test example code , And learn different types of 、 Documentation of functions and methods . Although I have tried my best to make the content of this book step by step , But readers will still encounter something that has not been introduced before .

Most of this book focuses on table based analysis and data preparation tools for processing large-scale data sets . In order to use these tools , We must first organize the chaotic data into neat tables （ Or structured ） form . fortunately ,Python Is an ideal language , Can quickly organize data .Python The more skillful you use , The easier it is to prepare new data sets for analysis .

Best in IPython and Jupyter Try the tools used in this book for yourself . When you learn how to start Ipython and Jupyter, I suggest you follow the example code to practice . Like any keyboard driven operating environment , Remember that common commands are also part of the learning curve .

note ： This chapter does not cover Python Some concepts of , Such as classes and object-oriented programming , You may find them in Python Useful in data analysis . To add