However, the author does explore possible errors throughout the text and helps the reader understand what is causing them so as to aid in future debugging.All the chapters are uniformly formatted and are consistent in their use of terminology.The book is broken up into logical chapters and each chapter is further divided into meaningful and accessible portions. However, it is not an introduction to programming nor an introduction to computer science using Python as the teaching language.The content of the book is accurate given its intended scope, even if it is a little dated in its approach to some material, such as string formatting. The book would benefit from making visualization stand more on its own.The book is well-organized and has a coherent flow through the chapters. Python for Everybody: Exploring Data In Python 3. Other readers will always be interested in your opinion of the books you've read. This book provides an Informatics-oriented introduction to programming.
Few of my students were planning to be professional computer programmers. While Severance has reworked many of the examples in these chapters to better reflect the book's overarching theme of data exploration Downey and Elkner's clear and concise introduction to the Python language is still prevalent and makes the early material easily accessible for new programmers. The book generally strikes a good balance. Finally, there is essentially no treatment of the Python standard library nor any hint that readers should look into it for the amazing wealth of functionality it provides. The book does an excellent job of explaining the Python language, always providing a context in which topics are useful. The book keeps the clarity of the original while including examples skewed towards data applications, particularly text processing. These are good choices because they are widely used, but increasingly XML is falling by the wayside … The chapters based on Downey and Elkner's earlier book are very clear if, again, limited in scope. You'll also see how to handle missing values and prepare to visualize your dataset in a Jupyter notebook. Information is imparted, not just to be comprehensive, but to help the reader be a better programmer.
The discussion of applications is accurate with regards to common practices of web-scraping programs. The author plays it conservatively by discussing XML and JSON for web services and SQLite for databases. The book keeps the clarity of the original while including examples skewed towards data applications, particularly text processing. Overall, this book serves as an introduction to the basics of the Python programming language and its application to data exploration. Whether you've loved the book or not, if you give your honest and detailed thoughts then people will find new books that are right for them. Download books for free. Instead, they planned to be librarians, managers, lawyers, The use of Python 3 ensures that chapters regarding syntax and data structures will remain valid for the foreseeable future. The first nine chapters are terse, but comprehensive introduction to Python.
The later chapters jump in complexity at the expense of clarity in my opinion. The book does not cover data science, plotting, or Python libraries like pandas.
Chapters build upon those that proceeded them as is to be expected in an introductory programming text.The text in the browser by default is on the small side but this can be corrected by zooming in on the page.
This has the effect, however, of making the section headers overly large. The book is also lacking in its coverage of string formatting in Python, discussing only the most basic string formatting features and capabilities of the language while completely eschewing the .format() method and f-strings. But it does not provide a general treatment of visualization tools nor a discussion of how to use them effectively. Free download Python For Everybody Exploring Data Using Python 3 in PDF Written by Charles R. Severance. Chapters two through ten are based heavily on Allen Downey and Jeff Elkner's excellent book, "Think Python: How to Think Like a Computer Scientist." 11 min read. The coverage of the Python language is generally thorough, but misses topics like list comprehensions and lambda expressions. Python for Everybody – Exploring Data Using Python 3. The visualization chapter is the only one that is lacking. Find books One of the three visualization examples is based on the Gmane interface to mailing lists, which is likely not very relevant for students and Gmane's continued existence is in doubt.
The chapter on visualization is unfortunately dependent on the database chapter. I did not find any subsection to be overly long and overall each chapter is short enough to be assigned as a single reading. Python for Everybody | Exploring Data Using Python 3 | download | B–OK. It is more geared toward acquiring data (web, databases and SQL).I found no issues with the content, but there are a few typographical errors from LaTex in the text. They are obvious and don't impact the understanding. The author plays it conservatively by discussing XML and JSON for web services and SQLite for databases. The use of Python 3 ensures that chapters regarding syntax and data structures will remain valid for the foreseeable future.
The latter I suspect is due at least in part to the text's age.