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Python Data Science Handbook: Essential Tools for Working with Data Paperback – 6 December 2016

by Jake Vanderplas (Author)
4.5 out of 5 stars 806 ratings
Edition: 1st
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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

About the Author

Jake VanderPlas is a long-time user and developer of the Python scientific stack. He finished his PhD in Astronomy at the University of Washington in 2012, and 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.
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  1. ISBN-10
    1491912057
  2. ISBN-13
    978-1491912058
  3. Edition
    1st
  4. Publisher
    O'Reilly Media, Inc, USA
  5. Publication date
    6 December 2016
  6. Language
    English
  7. Dimensions
    17.78 x 3.18 x 25.4 cm
  8. Print length
    548 pages
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Python Data Science Handbook: Essential Tools for Working with Data
Python Data Science Handbook: Essential Tools for Working with Data
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From the Publisher

Data Science for Business
Data Science from Scratch
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Python Data Science Handbook
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Price $49.59 $71.05 $66.17 $101.38 $57.73 $108.95
What You Need to Know about Data Mining and Data-Analytic Thinking First Principles with Python Straight Talk from the Frontline Visualize, Model, Transform, Tidy, and Import Data Facing the Future with Time-Tested Tools Tools and Techniques for Developers
Pages 414 330 408 250 212 500

Product description

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, Inc, USA
  • Publication date ‏ : ‎ 6 December 2016
  • Edition ‏ : ‎ 1st
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 548 pages
  • ISBN-10 ‏ : ‎ 1491912057
  • ISBN-13 ‏ : ‎ 978-1491912058
  • Item weight ‏ : ‎ 862 g
  • Dimensions ‏ : ‎ 17.78 x 3.18 x 25.4 cm
  • Customer Reviews:
    4.5 out of 5 stars 806 ratings

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Jake VanderPlas

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Top reviews from Australia

  • Glen Hardingham
    4.0 out of 5 stars Awesome
    Reviewed in Australia on 17 September 2018
    Format: PaperbackVerified Purchase
    Has a lot of information to absorb. Read the whole thing to become a star in Python!!
    One person found this helpful
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  • Paul Kinsvater
    5.0 out of 5 stars Perfekt für Statistiker mit wenig Computer Science-Background
    Reviewed in Germany on 4 March 2017
    Format: PaperbackVerified Purchase
    Ich erkläre zunächst meinen eigenen Background und darauf aufbauend, was ich an anderen Python-Büchern/Tutorials vermisst habe:

    Ich bin promovierter Statistiker mit langjähriger Erfahrung in R und arbeite seit etwas mehr als 2 Jahren mit Linux. Shell-Skills (bash) sind zwar vorhanden, aber definitiv noch ausbaufähig. Ich stehe am Anfang einer Data Science-Karriere in der Industrie. Da Data Science nach meinem Verständnis aus Computer Science + Statistik + epsilon besteht und da ich einen starken Mathematik/Statistik-Background habe, möchte ich meine Programmier-Skills verbessern. Dazu gehört das Erlernen weiterer Programmiersprachen wie Python und C++.

    Mein Ziel: Lerne Datenanalyse in Python. Insbesondere NumPy, SciPy, Pandas und Matplotlib.

    Dies ist nicht mein erstes Python-Buch. Was mir an anderen Büchern/Onlinetutorien aufgefallen ist, dass diese oft auf Computer Scientists (Informatiker) zugeschnitten sind. Es war regelmäßig frustrierend, wenn kleine Details nicht erklärt wurden, die für Informatiker selbstverständlich sind.

    Das Buch "Python Data Science Handbook" ist anders. Es erklärt vieles, was für einen Nicht-Informatiker nicht selbstverständlich ist. Insbesondere ist das erste Kapitel wertvoll für einen Statistiker wie mich. Es erklärt detailliert, wie man mit ipython in einer Shell arbeitet.

    Fazit: Für Informatiker, die tiefes Verständnis für Python aufbauen wollen, sind andere Bücher empfehlenswert. Wenn man dagegen Grundkenntnisse in Python mitbringt und hauptsächlich an der Datenanalyse in Python interessiert ist, kann ich dieses Buch herzlichst empfehlen.
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  • Guillermo Martinez Dibene
    5.0 out of 5 stars Very useful
    Reviewed in Canada on 23 November 2020
    Format: PaperbackVerified 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.
    Report
  • Amazon Customer
    2.0 out of 5 stars disappointed
    Reviewed in France on 24 October 2017
    Format: PaperbackVerified Purchase
    I really hoped that this would be better. There are a few errors that take a while to work out. Some of the key concepts are completely skipped over. Constantly find myself losing interest in the topics, which could flow a lot better. I had hoped for something like Hadleys book R for Data science, but this is far from it. Wouldn't bother buying.
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  • Ashish
    5.0 out of 5 stars Very useful for data science
    Reviewed in India on 5 December 2021
    Verified Purchase
    This book has put thorough light on the libraries like NumPy, Pandas and Metplotlib. Very useful for data science students but this book is not for general Python or for those who want to learn Python from the beginning.
    Report
  • Ana Isabel Bezerra Cavalcanti
    5.0 out of 5 stars Importante, principalmente para pesquisas futuras.
    Reviewed in Brazil on 15 October 2020
    Format: PaperbackVerified Purchase
    Atendeu às minhas expectativas atuais e será útil em trabalhos futuros.
    Report