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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

By : Ivan Idris
2 (1)
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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

2 (1)
By: Ivan Idris

Overview of this book

This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.
Table of Contents (16 chapters)
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14
C. NumPy Functions' References
15
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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