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 12 reviews)

Ratings Distribution

  • 5 Stars

     

    (11)

  • 4 Stars

     

    (1)

  • 3 Stars

     

    (0)

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100%

of respondents would recommend this to a friend.

Pros

  • Easy to understand (9)
  • Concise (8)
  • Helpful examples (8)
  • Well-written (8)
  • Accurate (7)

Cons

No Cons

Best Uses

  • Intermediate (7)
  • Student (7)
  • Novice (5)
    • Reviewer Profile:
    • Developer (5)

Reviewed by 12 customers

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5.0

I'll read this book again, may be a couple of times

By PG

from Bangalore

About Me Designer, Developer, Educator

Verified Reviewer

Pros

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

Cons

    Best Uses

    • Intermediate
    • Student

    Comments about oreilly Python Data Science Handbook:

    Over the past three years I referred to Wes McKinney's excellent book Python for Data Analysis for my work. Now on, I'll refer to Python for Data Science Handbook. It is clear and concise and addresses developers with some experience. This is sensible, because an absolute beginner is unlikely to start with data analysis.

    Though I have a hard copy, Jupyter Notebook version of the book freely available at github is great help in learning and teaching.

    The examples are short and easy to understand. However, they make things appear much easier than real life challenges.

    A good coverage on data munging would help because we spend more than 50% of the time in cleansing and modelling the data.

    Minor grammatical errors are found in a few places. The language could have been plainer reducing many unwanted wordiness. I'll be glad to give my detailed observations to the publisher / author.

     
    5.0

    Leapfrog your skills

    By Always learning

    from FL

    About Me Developer

    Verified Reviewer

    Pros

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

    Cons

      Best Uses

      • Intermediate

      Comments about oreilly Python Data Science Handbook:

      Excellent flow of information. Avoids repeating basic language stuff and deeps dive quickly into the essential topics for moving your knowledge from basic to intermediate level. It also provides useful guidance of using help support tools.

       
      5.0

      Excellent !

      By Always_learning

      from FL

      Pros

      • Accurate
      • Concise
      • Easy to understand

      Cons

        Best Uses

        • Intermediate

        Comments about oreilly Python Data Science Handbook:

        Fills the gap between novice to expert.

        (2 of 2 customers found this review helpful)

         
        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

            Best Uses

            • 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

                Best Uses

                • 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.

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