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Numpy Beginner's Guide (Update)

You're reading from   Numpy Beginner's Guide (Update) Build efficient, high-speed programs using the high-performance NumPy mathematical library

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781785281969
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

Preface 1. NumPy Quick Start FREE CHAPTER 2. Beginning with NumPy Fundamentals 3. Getting Familiar with Commonly Used Functions 4. Convenience Functions for Your Convenience 5. Working with Matrices and ufuncs 6. Moving Further with NumPy Modules 7. Peeking into Special Routines 8. Assuring Quality with Testing 9. Plotting with matplotlib 10. When NumPy Is Not Enough – SciPy and Beyond 11. Playing with Pygame A. Pop Quiz Answers B. Additional Online Resources C. NumPy Functions' References
Index

Time for action – converting arrays

Convert a NumPy array to a Python list with the tolist() function:

  1. Convert to a list:
    In: b
    Out: array([ 1.+1.j,  3.+2.j])
    In: b.tolist()
    Out: [(1+1j), (3+2j)]
    
  2. The astype() function converts the array to an array of the specified type:
    In: b
    Out: array([ 1.+1.j,  3.+2.j])
    In: b.astype(int)
    /usr/local/bin/ipython:1: ComplexWarning: Casting complex values to real discards the imaginary part
      #!/usr/bin/python
    Out: array([1, 3])
    

    Note

    We are losing the imaginary part when casting from the NumPy complex type (not the plain vanilla Python one) to int. The astype() function also accepts the name of a type as a string.

    In: b.astype('complex')
    Out: array([ 1.+1.j,  3.+2.j])
    

It won't show any warning this time because we used the proper data type.

What just happened?

We converted NumPy arrays to a list and to arrays of different data types. The code for this example is in the arrayconversion.py file in this book's code bundle.

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