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Dancing with Python

You're reading from   Dancing with Python Learn to code with Python and Quantum Computing

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Product type Paperback
Published in Aug 2021
Publisher Packt
ISBN-13 9781801077859
Length 744 pages
Edition 1st Edition
Languages
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Author (1):
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Robert S. Sutor Robert S. Sutor
Author Profile Icon Robert S. Sutor
Robert S. Sutor
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Toc

Table of Contents (29) Chapters Close

Preface 1. Chapter 1: Doing the Things That Coders Do 2. Part I: Getting to Know Python FREE CHAPTER
3. Chapter 2: Working with Expressions 4. Chapter 3: Collecting Things Together 5. Chapter 4: Stringing You Along 6. Chapter 5: Computing and Calculating 7. Chapter 6: Defining and Using Functions 8. Chapter 7: Organizing Objects into Classes 9. Chapter 8: Working with Files 10. PART II: Algorithms and Circuits
11. Chapter 9: Understanding Gates and Circuits 12. Chapter 10: Optimizing and Testing Your Code 13. Chapter 11: Searching for the Quantum Improvement 14. PART III: Advanced Features and Libraries
15. Chapter 12: Searching and Changing Text 16. Chapter 13: Creating Plots and Charts 17. Chapter 14: Analyzing Data 18. Chapter 15: Learning, Briefly 19. References
20. Other Books You May Enjoy
21. Index
Appendices
1. Appendix A: Tools 2. Appendix B: Staying Current 3. Appendix C: The Complete UniPoly Class
4. Appendix D: The Complete Guitar Class Hierarchy
5. Appendix E: Notices 6. Appendix F: Production Notes

13.5 Scatter plots

We use a scatter plot to display many points. After doing that, we make it fancy with colors, markers, labels, titles, and fonts and adjust the axes so the plot conveys your data effectively and pleasantly.

Like pie, we control most of the look of a scatter plot via keyword arguments to scatter. The data for the plots is the high temperatures for three cities—A, B, and C—over the first ten days of March 2021. The temperatures are in Fahrenheit, and I use numpy arrays to hold the numeric days of the month and the data.

If I merge the data into single arrays for the days and temperatures via the numpy concatenate function, scatter shows all points in the same color with the same marker. The default color is blue.

import matplotlib.pyplot as plt
import numpy as np

days = np.arange(1, 11)

city_high_temperatures = {
    'A': np.array([63, 57, 59, 67, 54...
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