Python Data Science Handbook
Essential Tools for Working with Data
Publisher: O'Reilly Media
Final Release Date: November 2016
Pages: 548

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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oreillyPython Data Science Handbook
 
4.9

(based on 9 reviews)

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100%

of respondents would recommend this to a friend.

Pros

  • Easy to understand (6)
  • Helpful examples (6)
  • Well-written (6)
  • Accurate (5)
  • Concise (5)

Cons

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  • Novice (5)
  • Intermediate (4)
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Reviewed by 9 customers

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5.0

Perfect Guideline for Beginners

By Tim

from Seattle, WA

Comments about oreilly Python Data Science Handbook:

I watched several training videos before picked this book up. The content of this book is the "common emphasis" of these videos. Before you read it, please spend some time to learn Python first, this book needs you have solid Python knowledge/skills. Good luck!

 
5.0

Enabled junior data analyst to get up and running fast

By DW

from New York, NY

About Me Leader

Verified Buyer

Pros

  • Concise
  • Easy to understand

Cons

    Best Uses

    • Novice
    • Student

    Comments about oreilly Python Data Science Handbook:

    I got this book for a junior data analyst (just out of grad school). She read the first half or so of each chapter, and was able to build the basic skills needed to hit the ground running with the Python data stack.

     
    5.0

    Very nice book!

    By Ahmad Sultan

    from Germany

    About Me Developer

    Verified Buyer

    Pros

    • Easy to understand
    • Helpful examples
    • Well-written

    Cons

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      • Intermediate
      • Novice
      • Student

      Comments about oreilly Python Data Science Handbook:

      It met all my expectations, Thank you!

       
      5.0

      A good intro to the essentials

      By partsiartsi

      from Finland

      About Me Developer, Sys Admin

      Pros

      • Accurate
      • Concise
      • Helpful examples

      Cons

        Best Uses

        • Intermediate
        • Novice
        • Student

        Comments about oreilly Python Data Science Handbook:

        Numpy/Matplotlib/Pandas are great tools, and I have learnt to use them from intros in various books and the official documentation. This is the best practical and combined intro on all of these libraries I have read to date, and I still use it to check some syntax and examples. Highly recomended if you know python and try to use python for data-analysis, know numpy but not pandas, or have background in R or Matlab and want an intro to the python alternative.

        (1 of 1 customers found this review helpful)

         
        5.0

        A succinct introduction to data science using PyData Stack

        By GeeDay

        from Portland, Oregon

        About Me Budding Data Scientist

        Verified Reviewer

        Pros

        • Accurate
        • Concise
        • Easy to understand
        • Helpful examples
        • Well-written

        Cons

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          • Novice
          • Student

          Comments about oreilly Python Data Science Handbook:

          Book provides a quick overview of data science and the relevant python libraries needed for data science and machine learning. Still waiting for the book to be updated with the chapter on statistics.. can't wait!

          (4 of 4 customers found this review helpful)

           
          5.0

          Excellent Tutorial And Reference

          By ktroxie

          from Cambridge, MA

          About Me Data Scientist, Developer

          Verified Reviewer

          Pros

          • Accurate
          • Helpful examples
          • Well-written

          Cons

            Best Uses

              Comments about oreilly Python Data Science Handbook:

              This book focuses on the key tools you'll use in your day-to-day as a data scientist: Ipython, Numpy, Matplotlib/Seaborn, Pandas, Scikit-Learn. It uses a lot of code examples and motivating examples to take you from a rank beginner to someone who can fluently use the tools in their day-to-day work.

              The book is filled with small and insightful examples illustrating specific points, for example, what broadcasting is in numpy and how it works. The author has a knack for identifying the minimal example that illustrates a point.

              There are a few in-depth sections, in the machine learning section, where specific techniques like linear regression are discussed in detail. Besides using a real-world dataset, it is also a really interesting example of the thought process a skilled data scientist goes through.

              I've found myself referring back to the book constantly over the past few months, for both refresher on topics ("time series in pandas) to specific questions ("how do i show a confusion matrix for my results"). I wholeheartedly recommend this book.

              (2 of 4 customers found this review helpful)

               
              5.0

              If you landed here, don't hesitate to buy

              By future data scientist

              from San Jose, Costa Rica

              Pros

              • Concise
              • Easy to understand
              • Well-written

              Cons

                Best Uses

                • Intermediate
                • Novice
                • Student

                Comments about oreilly Python Data Science Handbook:

                Jake van der Plas (or VanderPlas in a non-dutch enviroment). this is the guy you want to learn from! The book is an awesome introduction to Data Science with Python. The guy also has a few YouTube videos in which he discusses similar topics. All in all, this is the book you're looking for! I just wish there was an update to the book, it's been almost 6 months since it was last updated.. Once released, this will be gold.

                (1 of 1 customers found this review helpful)

                 
                5.0

                I can't wait

                By Sblack4

                from Washington DC

                About Me Student

                Verified Buyer

                Pros

                • Accurate
                • Concise
                • Easy to understand
                • Helpful examples
                • Well-written

                Cons

                • Not comprehensive enough

                Best Uses

                • Student

                Comments about oreilly Python Data Science Handbook:

                I love it! I'm new to Python so the general review helped as well as taught me a few new tricks. There are examples in the book I just wish there were exercises to challenge my understanding:)

                (10 of 10 customers found this review helpful)

                 
                4.0

                Great so far

                By Chris

                from Blue Mountains, Australia

                About Me Educator

                Verified Buyer

                Pros

                • Accurate
                • Easy to understand
                • Helpful examples
                • Suggested Resources Well
                • Well-written

                Cons

                  Best Uses

                  • Intermediate

                  Comments about oreilly Python Data Science Handbook:

                  I'm gradually increasing the amount of data analysis I do with Python rather than R and this text is developing into an excellent introduction on the essential , and cool, tools that makes Python the great gluestick it is. I'm not new to Python and think the Chapter 1 overview of the language is succinct and pertinent. I learnt some new things about iPython in Chapter 2 but have learnt a lot from the chapter on Pandas. I found the examples relevant and useful.

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