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The Data Visualization Workshop

You're reading from   The Data Visualization Workshop A self-paced, practical approach to transforming your complex data into compelling, captivating graphics

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781800568846
Length 536 pages
Edition 1st Edition
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Authors (2):
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Mario Döbler Mario Döbler
Author Profile Icon Mario Döbler
Mario Döbler
Tim Großmann Tim Großmann
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Tim Großmann
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Toc

Images

If you want to include images in your visualizations or work with image data, Matplotlib offers several functions for you. In this section, we will show you how to load, save, and plot images with Matplotlib.

Note

The images that are used in this section are sourced from https://unsplash.com/.

Basic Image Operations

The following are the basic operations for designing an image.

Loading Images

If you encounter image formats that are not supported by Matplotlib, we recommend using the Pillow library to load the image. In Matplotlib, loading images is part of the image submodule. We use the alias mpimg for the submodule, as follows:

import matplotlib.image as mpimg

The mpimg.imread(fname) reads an image and returns it as a numpy.array object. For grayscale images, the returned array has a shape (height, width), for RGB images (height, width, 3), and for RGBA images (height, width, 4). The array values range from 0 to 255.

We can also load the image in...

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