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Learning IPython for Interactive Computing and Data Visualization, Second Edition

Learning IPython for Interactive Computing and Data Visualization, Second Edition

By : Cyrille Rossant
4.5 (12)
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Learning IPython for Interactive Computing and Data Visualization, Second Edition

Learning IPython for Interactive Computing and Data Visualization, Second Edition

4.5 (12)
By: Cyrille Rossant

Overview of this book

Python is a user-friendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while the Jupyter Notebook is a rich environment well-adapted to data science and visualization. Together, these open source tools are widely used by beginners and experts around the world, and in a huge variety of fields and endeavors. This book is a beginner-friendly guide to the Python data analysis platform. After an introduction to the Python language, IPython, and the Jupyter Notebook, you will learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in the Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel. By the end of this book, you will be able to perform in-depth analyses of all sorts of data.
Table of Contents (8 chapters)
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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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