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Python 3 and Data Visualization

You're reading from   Python 3 and Data Visualization Mastering Graphics and Data Manipulation with Python

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Product type Paperback
Published in Aug 2024
Publisher Mercury_Learning
ISBN-13 9781836645719
Length 281 pages
Edition 1st Edition
Languages
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Authors (2):
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Mercury Learning and Information Mercury Learning and Information
Author Profile Icon Mercury Learning and Information
Mercury Learning and Information
Oswald Campesato Oswald Campesato
Author Profile Icon Oswald Campesato
Oswald Campesato
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Table of Contents (9) Chapters Close

Preface
1. Chapter 1: Introduction to Python 3 2. Chapter 2: NumPy and Data Visualization FREE CHAPTER 3. Chapter 3: Pandas and Data Visualization 4. Chapter 4: Pandas and SQL 5. Chapter 5: Matplotlib for Data Visualization 6. Chapter 6: Seaborn for Data Visualization 7. Index
Appendix: SVG and D3

DISPLAY ATTRIBUTE VALUES

Listing 5.2 displays the contents of mat_attrib_values.py that displays the attribute values of an object in Matplotlib (subplots are discussed later in this chapter).

LISTING 5.2: mat_attrib_values.py

import matplotlib.pyplot as plt
 
fig, ax = plt.subplots()

print("=> attribute values:")
print(plt.getp(fig))

Listing 5.2 contains an import statement, followed by the variables fig and ax that are initialized by invoking the subplots() method of the plt class. The next block of code prints the attribute values in fig wby invoking the plt.getp() method. Launch the code in Listing 5.2 and you will see the following output:

=> attribute values:
    agg_filter = None
    alpha = None
    animated = False
    axes = [<AxesSubplot:>]
    children = [<matplotlib.patches.Rectangle object at 0x11c34f0...
    clip_box = None
    clip_on = True
    clip_path = None
    constrained_layout = False
    constrained_layout_pads = (0.04167, 0.04167,...
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