Python for Everybody: Exploring Data in Python 3

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.

This book has helped me with an on-line class.

This book is a textbook case (hah!) of truth in advertising. It’s directed at people who are interested in using Python as a tool primarily for data analysis, rather than people who are interested in learning Python for more general programming purposes. Is it effective? Yes and no. The early parts of the book are quite instructive, covering the basics of Python’s built-in types and syntax, and building to greater complexity. At some point, though, the bottom suddenly falls out. The difficulty ramps up tremendously, and the book largely devolves into massive code dumps, or links to massive code dumps, with most of the discussion focused on how to make use of the programs rather than how to develop similar programs for your own purposes. I have a feeling that in a classroom setting, with supplemental materials and a good teacher, this is likely less of an issue.All in all, it’s a fine book, and well-targeted. I really appreciated the section on regular expressions, which is a topic most introductory programming texts don’t even mention, and the database interactions are another oft-neglected area that had some good, basic information. I think it would benefit from a bit more dissection of the later programs, but for the price I can’t really complain. 3.5 stars, rounded up to 4.

I'm only 9 pages in but I love this book. I have a degree in Industrial Engineering and certification in 8-12 Math Education. I have a passion for the human machine interface and making the complicated simple. I'm blown away by this book. This would be exactly how I would write a book on programming if I knew enough about programming. So thankful for this author and that this book was on our syllabus for my python class.

Dr. Chuck is great. It is the most comprehensive (mile wide inch deep) cover of python 3. Read the chapter before watching the lesson. Also, all the test questions are available online. When you hit a road block get the solution and reverse engineer it, great way to learn. I write them over and over again in jupyter, piece by piece until I know and UNDERSTAND it front to back.

This is an excellent book. It is well thought out and easy to read. There are lots of genuinely useful links and some complete and useful data-handling examples. My sole objection is the title, implying this book is for "Everybody". I felt that this book would be a great text for a second-year course in any major involving data handling. It would not be ideal for an introduction to computer science class, nor for most computer science majors. It would be too focused on data handling for the former, and too easy for the latter. Anyway, this is nit picking. It's really a very good book.

I am just starting with Python but know a couple other programming languages that are used in statistics. This is a great intro for people with little to no programming background! A little basic for those who already know some object oriented languages, but you can move quickly through the chapters and push yourself to do more. Builds confidence with easy to follow examples and the author does a good job of keeping you engaged-not boring at all! Highly recommend as a stepping stone to begin your Python journey.

I'm using this book in tandem with the coursera.org course on the same called python for everybody and this is invaluable to the course. This book teaches python coding and not - as many many other beginner coding courses teach - how to solve math questions. By the time I got to chapter 10 I was comfortable reading and understanding just about every line of code I came across at the beginner to slightly more advanced data structures level. I can't say I liked the book on kindle though as I used kindle on my phone and it was a bit of a pita to use. I ended up downloading the free pdf and found that did me better than the way it's formatted for kindle. Good luck on your coding journey.