Book Preview: Numpy 1.5 Beginner’s Guide

Recently, I was linked to the Python Forum because one of my friends on the wxPython IRC channel said that Packt was trying to find reviewers for their new book, Numpy 1.5 Beginner’s Guide by Ivan Idris. I doubt they’re going to find many people on that website though. I’ve certainly never heard of it. Anyway, Packt was kind enough to give me a copy of it as an ebook, so I’ll be reading it over the next couple of weeks so I can review it for this website.

I haven’t used NumPy before, but I hear about it from time to time on the wxPython mailing list and I thought it sounded interesting. So I am glad that there’s a new beginner’s book on the topic. I hope it’s a good one. In the meantime, Packt gave me a link to chapter 3, so you can read that while you wait for my review. It looks like Doug Finke will also be doing a review of this book too, so you may want to keep an eye on his blog to see what he thinks too.

Numpy 1.5 Beginner’s Guide

By Ivan Idris



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  • Anup

    Numpy and Scipy are powerful and free tools available for any engineer. Coupled with  Matplotlib it makes a nice alternative to Matlab. Add Latex to that and you have a powerful report generating tool at your disposal!
    I have used the combination above for offline data analysis and report generation. In general Python has great file parsing abilities. As shown in the sample chapter 3 getting in data from a csv file (very typical scenario) and processing it to see various result is very easy with Numpy. Common functions like least squares curve fitting and fft analysis are easily accomplished with Numpy.
    Just like with Python, you can be productive with Numpy right away. Documentation on their site is very good. Community support at is great and lots of examples are available elsewhere on the internet as well.
    Overall a very useful package for analyzers everywhere!

  • Joaquin Abian

    Great!. I’m not sure if there is a module of mine with no numpy or scipy import. Available Numpy documentation is not that bad. On the other side Scipy would deserve n books (n > 1).
    Looking forward your memo!

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