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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

Squarify

At this point, we will briefly talk about tree maps. Tree maps display hierarchical data as a set of nested rectangles. Each group is represented by a rectangle, of which its area is proportional to its value. Using color schemes, it is possible to represent hierarchies (groups, subgroups, and so on). Compared to pie charts, tree maps use space efficiently. Matplotlib and Seaborn do not offer tree maps, and so the Squarify library that is built on top of Matplotlib is used. Seaborn is a great addition for creating color palettes.

Note

To install Squarify, first launch the command prompt from the Anaconda Navigator. Then, execute the following command: pip install squarify.

The following code snippet is a basic tree map example. It requires the squarify library:

%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import squarify
colors = sns.light_palette("brown", 4)
squarify.plot(sizes=[50, 25, 10, 15], \
    ...
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