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Python Data Science Handbook: Essential Tools for Working with Data 1st Edition

by Jake VanderPlas (Author)
4.6 4.6 out of 5 stars 674 ratings
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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:

  • IPython and Jupyter: provide computational environments for data scientists using Python
  • NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python
  • Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python
  • Matplotlib: includes capabilities for a flexible range of data visualizations in Python
  • Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
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Previous page
  1. ISBN-10
    1491912057
  2. ISBN-13
    978-1491912058
  3. Edition
    1st
  4. Publisher
    O'Reilly Media
  5. Publication date
    January 3, 2017
  6. Language
    English
  7. Dimensions
    7 x 1.25 x 10 inches
  8. Print length
    546 pages
  9. See all details
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  2. Data Science from Scratch: First Principles with Python
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Editorial Reviews

About the Author

Jake VanderPlas is a long-time user and developer of the Python scientific stack. He currently works as an interdisciplinary research director at the University of Washington, conducts his own astronomy research, and spends time advising and consulting with local scientists from a wide range of fields.

Product details

  • Publisher ‏ : ‎ O'Reilly Media; 1st edition (January 3, 2017)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 546 pages
  • ISBN-10 ‏ : ‎ 1491912057
  • ISBN-13 ‏ : ‎ 978-1491912058
  • Item Weight ‏ : ‎ 2.05 pounds
  • Dimensions ‏ : ‎ 7 x 1.25 x 10 inches
  • Customer Reviews:
    4.6 4.6 out of 5 stars 674 ratings

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Customer reviews

4.6 out of 5 stars
4.6 out of 5
674 global ratings
Intermediate book for reading.
5 Stars
Intermediate book for reading.
Not as easy or straightforward as "Python for Data Analysis " but because it uses Jupyter it's easy on the eyes to read. Highly recommend going to Staples or Office Max and getting the book spiral bound.
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Top reviews from the United States

Rodney Savant
5.0 out of 5 stars Intermediate book for reading.
Reviewed in the United States on September 6, 2021
Verified Purchase
Not as easy or straightforward as "Python for Data Analysis " but because it uses Jupyter it's easy on the eyes to read. Highly recommend going to Staples or Office Max and getting the book spiral bound.
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Rodney Savant
5.0 out of 5 stars Intermediate book for reading.
Reviewed in the United States on September 6, 2021
Not as easy or straightforward as "Python for Data Analysis " but because it uses Jupyter it's easy on the eyes to read. Highly recommend going to Staples or Office Max and getting the book spiral bound.
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5 people found this helpful
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L. Wixson
5.0 out of 5 stars Great coverage of essential topics
Reviewed in the United States on August 5, 2017
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When I first received this book, I was surprised that it didn't get to scikit-learn until the last third of the book. The first third is about numpy and pandas, and the middle third 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 were really essential. I wouldn't be nearly as productive if I had just jumped straight to the sections on scikit-learn. The author does an excellent job covering broad terrain with enough detail that you are able to apply it to your problems. You will find yourself going back to use this book as a reference.
27 people found this helpful
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Dmitry
4.0 out of 5 stars Not the panacea for data science challenges, but a pretty good resource nevertheless
Reviewed in the United States on June 4, 2017
Verified Purchase
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 quizes. Although it does not go in depth in regards to machine learning (although almost half of the book is dedicated to it), it does give an understanding of essential concepts. For those interested in machine learning I would recommend bying "Hands-On Machine Learning with Scikit-Learn and TensorFlow" by Geron as well as this book.
There is no one book for data science, and this one is no exception. Just keep that in mind before buying it.
Other than that, I am really happy with my purchase.

P.S. For those complaining about black and white graphs and diagrams - check the author's GitHub.
53 people found this helpful
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Gary W. Garrison
5.0 out of 5 stars Excllent Introduction to Python for Data Science
Reviewed in the United States on June 9, 2017
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I have used R for a few years and this was my first book that covered Python for data science. Even though it does not go into super great depth in any area, it is definitely a super book. It covers everything from Pandas, Matplotlib, and scikit-learn. I would highly recommend it for anyone that is new to Python and/or data science. The book is written with Jupyter Notebooks so it is easy to follow along and try code from the book in your own notebook.
24 people found this helpful
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O. Ishenko
5.0 out of 5 stars Well-written and very helpful
Reviewed in the United States on January 11, 2019
Verified Purchase
I've just finished this book. The author gives a well-written introduction into Machine-Learning with Python Scikit-Learn and illustrates each chapter with well-designed examples that are easy to follow and understand. I am very pleased with this book and can definitely recommend to everyone who is a beginner in the field and wants to quickly get hold on the practical approaches to ML.
One person found this helpful
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Brijesh
5.0 out of 5 stars This is by far the best book out in market to get you started with ...
Reviewed in the United States on January 29, 2017
Verified Purchase
This is by far the best book out in market to get you started with using python for data science. You will need some basic understanding of python and machine learning to understand concepts here, but this book will definitely take you skill to next level.This is no-nonsense book and goes deep into stuff which are relevant and important to do data science in python, every page is rich in information and provides practical use case, optimization tricks and adds new dimensions to your understanding of topic.
13 people found this helpful
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Srikanth Hanumanthappa
5.0 out of 5 stars Great book for beginners !
Reviewed in the United States on January 10, 2020
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well explained the basics of python programming for beginners. examples are small and easily executable. you can finish this book in 15 days with 2 hours each regularly on a day. I strongly recommend this book.
3 people found this helpful
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Eugene
5.0 out of 5 stars Great book!
Reviewed in the United States on April 26, 2019
Verified Purchase
The book is just great - amazing combination of details and brevity. I had programming experience but no experience with Python at all before I started reading this book. Very good fit for my qualification. Recommended for everyone who is going to start a new way into Data Science using Python.
2 people found this helpful
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Guillermo Martinez Dibene
5.0 out of 5 stars Very useful
Reviewed in Canada on November 23, 2020
Verified Purchase
This book contains introductions, tips and overview of the five more common Python packages for data science. It is clear, concise and quite fun to read. Only one down side, which is quite minor: some graphics needs colour. This is not a big deal because you can check the online version which available for free.
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Ana Isabel Bezerra Cavalcanti
5.0 out of 5 stars Importante, principalmente para pesquisas futuras.
Reviewed in Brazil on October 15, 2020
Verified Purchase
Atendeu às minhas expectativas atuais e será útil em trabalhos futuros.
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Antonio García Girón
5.0 out of 5 stars Muy útil
Reviewed in Spain on February 22, 2021
Verified Purchase
Está escrito de forma muy amena y con ejemplos paso a paso. Requiere que se sepa previamente algo de Python, pero es un libro muy útil para aprender a manejar datos a través de librerías, empezando por NumPy y Pandas, Matplotlib para representar datos, y una sección de modelado.
La única pega, por poner una, es que las figuras están en blanco y negro, pero el libro está muy bien.
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Maddy Burger
5.0 out of 5 stars Happy customer
Reviewed in the United Kingdom on April 11, 2021
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Item matches product description
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Carlos Rodriguez Contreras
5.0 out of 5 stars La selección ideal para conocer el ecosistema de Python
Reviewed in Mexico on November 3, 2017
Verified Purchase
Si sólo se pudiera tener un libro que sea una buena referencia de Python, este sería el indicado. Expone de manera sencilla los sistemas más utilizados de Python para la Ciencia de datos como pandas, numpy, y scipy. Lo recomiendo ampliamente.
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