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[NF0]≡ Download Free Python for Everybody Exploring Data in Python 3 Charles Severance Aimee Andrion Elliott Hauser Sue Blumenberg eBook

Python for Everybody Exploring Data in Python 3 Charles Severance Aimee Andrion Elliott Hauser Sue Blumenberg eBook



Download As PDF : Python for Everybody Exploring Data in Python 3 Charles Severance Aimee Andrion Elliott Hauser Sue Blumenberg eBook

Download PDF Python for Everybody Exploring Data in Python 3 Charles Severance Aimee Andrion Elliott Hauser Sue Blumenberg eBook

Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.



Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.



This book uses the Python 3 language. The earlier Python 2 version of this book is titled "Python for Informatics Exploring Information".


Python for Everybody Exploring Data in Python 3 Charles Severance Aimee Andrion Elliott Hauser Sue Blumenberg eBook

This book is not intended for professional programmers, and that's a very good thing for the rest of us. His primary motivation is to help readers understand how large amounts of data and information can be readily analyzed using Python. Another good point - he tells us that Python vocabulary is a rather small set of 'reserved words' with special meaning to Python. Unlike English, there is no ambiguity about what these words mean in Python.

Severance then describes how to start a conversation with Python - after first installing the Python software on your computer. Much/most of that information is offline, accessible through a link he provides. Continuing, >>> is Python's way of asking 'What do you want me to do next?' and the need for parentheses surround the description of what you want your computer to do. Python, like other programming languages, is very picky about syntax.

Then on to labeling/describing data to be used. Etc.

Overall, this book is a good overview for someone seriously interested in becoming a python programmer, not so good for someone just wanting to get a sense of what Python can do and how it would go about accomplishing such.

Product details

  • File Size 3879 KB
  • Print Length 244 pages
  • Simultaneous Device Usage Unlimited
  • Publication Date July 10, 2016
  • Sold by  Digital Services LLC
  • Language English
  • ASIN B01IA5VIFM

Read Python for Everybody Exploring Data in Python 3 Charles Severance Aimee Andrion Elliott Hauser Sue Blumenberg eBook

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Python for Everybody Exploring Data in Python 3 Charles Severance Aimee Andrion Elliott Hauser Sue Blumenberg eBook Reviews


I have used several books and most are about the same. They get you to a certain point and then you don’t know how to get to the next level. This one takes you through the whole process from start to finish of completing a project that you can use. Pair this book with the Professor’s videos on and you will have a great learning experience!
Amazing! I'm shocked and grateful that people put this material out. Such a high quality product (the book plus the podcast). I can't believe these lessons are next to free! Great way to learn Python. Very accessible and efficient with learning time.
There is no answer key for the exercises in this book. There is also no answer key if auditing the course at coursera. The only way to get the answers or grading is through the fully-paid version at coursera. There are deliberate trick questions that the text does not address, almost forcing a student to buy the paid version. For example, chapter 2 exercises require certain input() and float() expressions that the text does not address. Spent about two hours finally getting it, but only with internet searches. I paid $10 for the printed book instead of the free e-book, and one would think the $10 book would at least provide an answer key. In summary, this is a deliberate attempt to confuse a student and nearly force him or her to upgrade to the paid version in order to get the correct answers to the exercises.
I purchased this book because it was required for online Python courses taught by the author. I have not found a better beginner Python book out there. Plus, now that I am a professional Python programmer, I find myself constantly referring to this book to clarify certain points and reinforce understanding of basic principles. (I may be a professional, but I'm still a rookie.) I've purchased a few fat, expensive Python programming books with animals on the cover, but these tend to collect dust. In short, I have a new-found appreciation for this book and how much work went in to writing it. Thanks, Professor Severance!
Good intro to Python. Great companion and resource for the Coursera Python courses. The author and instructor is a master, making it easy to learn basic programming principles and Python.
The simplest and clearest explanations out of nearly a dozen introductory python texts I have collected. Artfully crafted instructional progression with by far the most relevant and amusing analogies and example cases. It is interesting to note that this is basically the third formal edition of a constantly improving open-source resource that was initially restructured and reworked by a very gifted teacher to teach data analysis and data mining; if you have tried to work through Think Python you should be able to recognize the refinement resulting from the writer's having used previous editions of this text to teach tens of thousands of students. I keep going back to this book as a reference as well. It really does contain the concisest explanations, and I am recognizing more and more that the code blocks and larger processing methods he describes are paragons of industry approaches. Starting here will make your life so much simpler and your learning immediately so much more productive you won't get lost in all the technical asides and theoretical maelstroms so many datascience Python texts seem to love to spin into and through. (I have also found the text to be a very helpful foundation for integrating all the open source videos and resources the author put together while teaching his classes through Coursera [and the University of Michigan]).
- A data analyst from a non-datascience background learning Python for the first time.
Excellent! The book is definitively for beginners who have no idea or know nothing about Python before. The author mixes basic concepts, without going deeply enough in some subjects. In addition, author provides teaching materials online pythonlearn.com. You can design your own learning path while having fun to navigate through the online course.

I have learnt many programming languages and read many books how to program. This is my favorite one because it is the easiest to read. The coding examples are easy to understand for the beginner. I am highly recommending this book for all non-programmers who want to learn the programming concept and to understand how program code works.
This book is not intended for professional programmers, and that's a very good thing for the rest of us. His primary motivation is to help readers understand how large amounts of data and information can be readily analyzed using Python. Another good point - he tells us that Python vocabulary is a rather small set of 'reserved words' with special meaning to Python. Unlike English, there is no ambiguity about what these words mean in Python.

Severance then describes how to start a conversation with Python - after first installing the Python software on your computer. Much/most of that information is offline, accessible through a link he provides. Continuing, >>> is Python's way of asking 'What do you want me to do next?' and the need for parentheses surround the description of what you want your computer to do. Python, like other programming languages, is very picky about syntax.

Then on to labeling/describing data to be used. Etc.

Overall, this book is a good overview for someone seriously interested in becoming a python programmer, not so good for someone just wanting to get a sense of what Python can do and how it would go about accomplishing such.
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