SciPy and NumPy
Examples to Jumpstart your Scientific Python Programming
Publisher: O'Reilly Media
Final Release Date: November 2012
Pages: 82

Are you new to SciPy and NumPy? Do you want to learn it quickly and easily through examples and a concise introduction? Then this is the book for you. You’ll cut through the complexity of online documentation and discover how easily you can get up to speed with these Python libraries.

Ideal for data analysts and scientists in any field, this overview shows you how to use NumPy for numerical processing, including array indexing, math operations, and loading and saving data. You’ll learn how SciPy helps you work with advanced mathematical functions such as optimization, interpolation, integration, clustering, statistics, and other tools that take scientific programming to a whole new level.

The new edition is now available, fully revised and updated in June 2013.

  • Learn the capabilities of NumPy arrays, element-by-element operations, and core mathematical operations
  • Solve minimization problems quickly with SciPy’s optimization package
  • Use SciPy functions for interpolation, from simple univariate to complex multivariate cases
  • Apply a variety of SciPy statistical tools such as distributions and functions
  • Learn SciPy’s spatial and cluster analysis classes
  • Save operation time and memory usage with sparse matrices
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oreillySciPy and NumPy
 
2.5

(based on 12 reviews)

Ratings Distribution

  • 5 Stars

     

    (3)

  • 4 Stars

     

    (1)

  • 3 Stars

     

    (1)

  • 2 Stars

     

    (1)

  • 1 Stars

     

    (6)

33%

of respondents would recommend this to a friend.

Pros

  • Easy to understand (6)
  • Helpful examples (5)
  • Concise (3)
  • Well-written (3)

Cons

  • Not comprehensive enough (3)

Best Uses

  • Novice (4)
  • Intermediate (3)
    • Reviewer Profile:
    • Developer (6), Scientist / researcher (3)

Reviewed by 12 customers

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5.0

Exactly what I needed

By QPP

from NL

About Me Phd Student

Verified Reviewer

Pros

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

Cons

    Best Uses

    • Expert
    • Intermediate
    • Novice
    • Student

    Comments about oreilly SciPy and NumPy:

    I am a last year PHD student in a field dominated by IDL so I learned mostly everything in forums and numpy/scipy webs. This book was exactly what I needed and since I have it, it has been proven extremely useful to me. I check it almost everyday.

    Clear, direct and concise it points effectively to the issues I have to deal with in my everyday programming. I don't want another thick book on python, I wanted a clear straight-to-the-point guide where I can, in a minute, find an example related to my problem, to a similar problem or a link to a web where I can find it. And this is IT!

     
    2.0

    Well honed examples wrapped in a book

    By Mike

    from Finland

    About Me Developer

    Verified Reviewer

    Pros

    • Helpful examples

    Cons

    • Difficult to understand
    • Not comprehensive enough

    Best Uses

    • Intermediate
    • Student

    Comments about oreilly SciPy and NumPy:

    The title promised a lot, but indeed this book is essentially a set of examples in a shallow setting not suitable for beginners. The book has matured a lot from the first draft of an edition, but the core problem is still there: there is simply too much to explain in a pocket book format. Now going at fourth edition, the examples have some excellent explanation and the book has a refreshing take on some capabilities SciPy has to offer -- at all of their glory the book is still just a set of examples.

    And while the examples have matured, they are together pretty similar: the good thing is that even the slower readers will get the idea by the end of this book. Wouldn't recommend this as standalone reading. The best use case would be for learners who have picked a more covering text book but would prefer extra examples.

    (3 of 3 customers found this review helpful)

     
    5.0

    Perfect for scientists starting Python

    By Rob

    from Oxford, UK

    About Me Developer, Scientist

    Verified Reviewer

    Pros

    • Easy to understand
    • Helpful examples
    • Well-written

    Cons

      Best Uses

      • Intermediate
      • Novice

      Comments about oreilly SciPy and NumPy:

      This book is pitched just right for someone getting going with SciPy and NumPy. I'm a scientist working in many coding environments and so Python has always been around. I've used it, and these packages, before but never extensively. This book is really helping to consolidate my understanding of these two essential Python packages and learn a lot of new stuff too!

       
      1.0

      Great incredients left raw

      By Mike

      from Finland

      About Me Developer, Student

      Pros

      • Easy to understand

      Cons

      • Not comprehensive enough
      • Too basic

      Best Uses

      • Novice

      Comments about oreilly SciPy and NumPy:

      A book with a great potential, reading about NumPy-SciPy interaction and use cases got me interested to check SciPy and Numpy. All I got is a booklet with dissonant examples and insufficient narrative. The author seems very knowledgeable in his field and some of the examples have a great window at the possibilities but the delivery simply lacks in so many ways. It all looks like produced in a hurry; even the proofreading missed a fair share.

      All in all, a couple of good examples glued with poor narrative makes this book no better than your average blog post.

      Disclosure: I got my copy of the book via O'Reilly's Blogger program for free.

       
      4.0

      I'm a python user now

      By Year of the Snake

      from Sydney, Australia

      About Me Scientist

      Verified Reviewer

      Pros

      • Concise
      • Easy to understand
      • Helpful examples

      Cons

        Best Uses

          Comments about oreilly SciPy and NumPy:

          It took me too long to finally jump into using Python. Starting as a novice, I found that this book provided exactly what I needed, explained in a concise way, to get me to the point of comfortably using Python on a regular basis.

          Most of the the complaints so far have stated the book is too short. My experience is that I wasted time searching for content on the internet, that I found very quickly in this reference once I bought it. Since purchasing it, I haven't needed any other sources for my issues with SciPy and NumPy so far.

          (3 of 4 customers found this review helpful)

           
          1.0

          Great Disappointment

          By Zentaro Konemi

          from Victoria, BC, Canada

          About Me Developer

          Verified Reviewer

          Pros

            Cons

            • Little Content

            Best Uses

              Comments about oreilly SciPy and NumPy:

              This is the worst book I have read published by O'Reilly (about 15+ books). I was very excited to see a title specifically on SciPy but when it arrived I thought at first there was a production or printing error. This book is about 60 pages, counting blanks, and numerous screenshots of non-important or non-informative plots. On top of that, the text is about half python code with little explanation, most of it is not relevant to SciPy at all. The actual SciPy calls are a few lines within program listings that are 10-times longer. The way how the book is presented would qualify more for a O'Reilly "Cookbook" format if not that you only get maybe 5 useful recipes in total-unless you are working on analyzing space telescope images. You get more (and better) information of SciPy after 5 min internet search.

              For NumPy the book has mere 10 pages despite calling NumPy in the title. Another recent O'Reilly book: "Python for Data Analysis" by Wes McKinney, although being mainly about pandas, has far, FAR more information on NumPy (by order of magnitude), and way better quality too.

              (1 of 2 customers found this review helpful)

               
              1.0

              From the O'Reilly Pamphlet Series

              By Analog Kid

              from SF, CA

              About Me Designer, Developer

              Pros

              • Easy to understand
              • Written Clearly

              Cons

              • Not comprehensive enough
              • Too basic

              Best Uses

              • Under Short Leg Of Table

              Comments about oreilly SciPy and NumPy:

              SciPy and NumPy really need a quality text written for them, but this isn't it. I was looking for something to give me more insight than I could get from a webpage. I saw the page count on this, but really didn't consider what that meant once code and plots were inlined.

              There is no meat here.

              (5 of 8 customers found this review helpful)

               
              5.0

              This book *finally* got me into Python

              By Pulsar

              from Europe

              About Me Scientist

              Pros

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

              Cons

                Best Uses

                • Novice

                Comments about oreilly SciPy and NumPy:

                I've been intending to learn Python for years - my prior experience with more "classical" programming languages like Fortran90 and the user-friendly but sluggish environment IDL made me look for a more elegant solution. I knew Python was a language that would fit my needs, but I was put off by the prospect of having to go through yet another learning curve. With this book it has been surprisingly easy to get started and apply my newly-learned abilities during my everyday work.

                I can tell that the earlier reviews on this website were probably written by more experienced programmers than I am - in my view, this book is extremely well-suited for getting started. The examples are clear, and the book takes you from the very basic initial coding to more advanced features. Any scientist will be able to adopt and adapt these examples to develop new and original bits of code.

                And in the end, isn't that how we learn most efficiently?

                (3 of 4 customers found this review helpful)

                 
                1.0

                Sadly, not quite what I wanted/needed

                By Python Gnome

                from Ca

                Comments about oreilly SciPy and NumPy:

                This book, "Scipy and NumPy", is actually not a comprehensive (or even abbreviated) intro to these packages, but rather a brief essay describing some uses with some very simple code. Although the limited Numpy material seemed reasonably useful as a broad overview, the Scipy part was not useful.

                To make it clear what you're getting, this book is really really short. The indicated length (57 pages) is filled only partly with text and code. Characters, lines, and page margins are all printed with plenty of white space in between, and interspersed are images, blank pages, etc. Maybe the remaining text is perfect for some users, but I was unfortunately not one of them.

                Particularly aggravating was the price of >$25.00.

                Rather than complaining more about the only scipy/numpy book that has been written (or at least that I know of), I would suggest that anyone in this community who wants a challenging-but-highly-useful task write a comprehensive intro to SciPy (especially) and Numpy, perhaps using Mark Lutz's wonderful "Python Pocket Reference" as an exemplar. Or perhaps this makes a good challenge to O'Reilly and Eli Bressert to make a more broadly useful second edition.

                (1 of 2 customers found this review helpful)

                 
                1.0

                Nice magazine article

                By Book Nook

                from Birmingham, ALA

                About Me Likes ~~"~books~~"~

                Pros

                  Cons

                  • By Definition Not A Book

                  Best Uses

                  • Small Shim For A Door Jam

                  Comments about oreilly SciPy and NumPy:

                  Seriously....

                  60 pages?

                  Thanks for the overpriced twitter post.

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