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Mastering Python Data Visualization

You're reading from   Mastering Python Data Visualization Generate effective results in a variety of visually appealing charts using the plotting packages in Python

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783988327
Length 372 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. A Conceptual Framework for Data Visualization 2. Data Analysis and Visualization FREE CHAPTER 3. Getting Started with the Python IDE 4. Numerical Computing and Interactive Plotting 5. Financial and Statistical Models 6. Statistical and Machine Learning 7. Bioinformatics, Genetics, and Network Models 8. Advanced Visualization A. Go Forth and Explore Visualization Index

Scalar selection


Scalar selection is the simplest method to select elements from an array and is implemented using [rowindex] for one-dimensional arrays, [rowindex, columnindex] for two-dimensional arrays, and so on. The following is a simple code that shows an array element reference:

import numpy as np
x = np.array([[2.0,4,5,6], [1,3,5,9]])

x[1,2]
5.0

A pure scalar selection always returns a single element and not an array. The data type of the selected element matches the data type of the array used in the selection. Scalar selection can also be used to assign a value to an array element, as shown in the following code:

x[1,2] = 8

x
array([[2, 4, 5, 6],[1, 3, 8, 9]])
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