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Learning IPython for Interactive Computing and Data Visualization, Second Edition

You're reading from   Learning IPython for Interactive Computing and Data Visualization, Second Edition Get started with Python for data analysis and numerical computing in the Jupyter notebook

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783986989
Length 200 pages
Edition 1st Edition
Languages
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Author (1):
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Cyrille Rossant Cyrille Rossant
Author Profile Icon Cyrille Rossant
Cyrille Rossant
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A primer to vector computing

Vector computing is about efficiently performing mathematical operations on numerical arrays. Many problems in science and engineering actually consist of a sequence of such operations.

This section introduces and demonstrates the multidimensional array data type for numerical computing.

Multidimensional arrays

What is a multidimensional array? Consider a vector containing 1000 real numbers. It has one dimension, since numbers are stored along a single axis. Now, consider a matrix with 1000 rows and 1000 columns. It contains 1,000,000 numbers. Because it has two dimensions, you need to specify both the row and column to refer to a specific number.

More generally, an n-dimensional array, also called ndarray, is an n-dimensional matrix (or tensor). Every number is identified by n indices (i_1, ... i_n).

Many types of real-world data can be represented as ndarrays:

  • The evolution of a stock exchange price is a 1D array (vector) with one value per day (or per hour, per...
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