

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all--IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.
Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.
With this handbook, you'll learn how to use:
It takes about 10 Hours and 58 minutes on average for a reader to read Python Data Science Handbook: Essential Tools For Working With Data. This is based on the average reading speed of 250 Words per minute.
Python Data Science Handbook: Essential Tools For Working With Data is 548 pages long.
Great book for beginners !
Derived From Web , Jan 10, 2020
Before diving into the programming language, you must know how to program a python program. The. Net framework is extremely small and easily executable. The remaining 15 days are spent with two hours a day spent on the book. It's a great book.
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excellent book but disappointing physical print/copy
Derived From Web , Dec 23, 2019
Amazon's own printed book, "The Age of Enlightenment," is off-brand. The book was printed on black and white paper, rendering many of the illustrations useless. The book is excellent and the contents are excellent, a great course with thorough and useful detail, said Dr. Paul LiCalsi. Amazon's own printed version is cheaper and more flexible, even if the original was never sold.
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Recommended to buy:
No
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Must have book for Machine Learning
Derived From Web , Mar 12, 2018
I love the presentation style and the treatment of the subject in this book, Mary. The book could have been organized better by adding more chapters.
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Recommended to buy:
Yes
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An excellent primer on data science tools
Derived From Web , Feb 4, 2018
I really enjoyed the book, Morgenthau said. I had not really picked up the python programming language prior to reading the book, but I was able to pick it up quickly. Before that I was plotting distributions of real-time statistics and developing a predictive modeling service. This book is a must-have for any aspiring data scientist.
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Great coverage of essential topics
Derived From Web , Aug 5, 2017
The first three are about pandas, the middle one is about matplotlib. Now that I've been applying it at work, however, I've found that the items covered in the first two thirds are really essential. If I had just jumped straight to the sections on scikit-learn, I would have been nearly as productive. The author does an excellent job covering broad terrain with enough detail that you can apply it to your problems, he said. If you have any questions, you can find yourself going back to use this book as a reference.
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Recommended to buy:
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Best book for python data analysis
Derived From Web , Jun 10, 2017
This is an excellent reference book for people working in data analysis. 80% of the effort in machine learning, data analysis or data science is about processing data, not about understanding data. If you're looking for hardcore machine learning, you're out of luck. Highly recommend.
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Recommended to buy:
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This book is well written and easy to follow
Derived From Web , Jun 10, 2017
The book is well written and easy to follow, said Dr. Brian McBride, director of the federal Centers for Disease Control and Prevention. It has saved me from spending hours on the internet to find the books I need.
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Recommended to buy:
Yes
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Excllent Introduction to Python for Data Science
Derived From Web , Jun 9, 2017
This was my first book that covered all the Python for data science. Even though it doesn't go into super great depth in any area, it is definitely a super book. It covers everything from. Net to Web 2.0, including everything from pandas to scikit-learn. Anyone new to Python or data science will find this useful.
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Recommended to buy:
Yes
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Not the panacea for data science challenges, but a pretty good resource nevertheless
Derived From Web , Jun 4, 2017
I am currently taking a Machine Learning course from Udacity and this book has proven to be a great reference guide for several projects and quizzes. Although it does not go into great depth of machine learning, it does give an understanding of essential concepts. For those interested in machine learning I would recommend bying hands-on TensorFlow by Geron and bying the book, "Machine Learning with Scikit-Learn." Just keep that in mind before buying it, said Jennette Tamayo, a New Jersey resident. For those complaining about black and white graphs and diagrams, check the author's GitHub page.
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New from | Used from |
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Paperback (December 20, 2016) | remove | $31.01 |