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NumPy Cookbook

You're reading from   NumPy Cookbook If you're a Python developer with basic NumPy skills, the 70+ recipes in this brilliant cookbook will boost your skills in no time. Learn to raise productivity levels and code faster and cleaner with the open source mathematical library.

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Product type Paperback
Published in Oct 2012
Publisher Packt
ISBN-13 9781849518925
Length 226 pages
Edition 1st Edition
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Toc

Table of Contents (17) Chapters Close

NumPy Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Winding Along with IPython 2. Advanced Indexing and Array Concepts FREE CHAPTER 3. Get to Grips with Commonly Used Functions 4. Connecting NumPy with the Rest of the World 5. Audio and Image Processing 6. Special Arrays and Universal Functions 7. Profiling and Debugging 8. Quality Assurance 9. Speed Up Code with Cython 10. Fun with Scikits Index

Performing string operations with chararray


NumPy has a specialized chararray object, which can hold strings. It is a subclass of ndarray, and has special string methods. We will download a text from the Python website and use those methods. The advantages of chararray over a normal array of strings are as follows:

  • Whitespace of array elements is automatically trimmed on indexing

  • Whitespace at the ends of strings is also trimmed by comparison operators

  • Vectorized string operations are available, so loops are not needed

How to do it...

Let's create the character array.

  1. Create the character array.

    We can create the character array as a view:

    carray = numpy.array(html).view(numpy.chararray)
  2. Expand tabs to spaces.

    Expand tabs to spaces with the expandtabs function. This function accepts the tab size as argument. The value is 8, if not specified:

    carray = carray.expandtabs(1)
  3. Split lines.

    The splitlines function can split a string into separate lines:

    carray = carray.splitlines()

The following is the complete...

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