Book Image

Dancing with Python

By : Robert S. Sutor
Book Image

Dancing with Python

By: Robert S. Sutor

Overview of this book

Dancing with Python helps you learn Python and quantum computing in a practical way. It will help you explore how to work with numbers, strings, collections, iterators, and files. The book goes beyond functions and classes and teaches you to use Python and Qiskit to create gates and circuits for classical and quantum computing. Learn how quantum extends traditional techniques using the Grover Search Algorithm and the code that implements it. Dive into some advanced and widely used applications of Python and revisit strings with more sophisticated tools, such as regular expressions and basic natural language processing (NLP). The final chapters introduce you to data analysis, visualizations, and supervised and unsupervised machine learning. By the end of the book, you will be proficient in programming the latest and most powerful quantum computers, the Pythonic way.
Table of Contents (29 chapters)
2
Part I: Getting to Know Python
10
PART II: Algorithms and Circuits
14
PART III: Advanced Features and Libraries
19
References
20
Other Books You May Enjoy
Appendices
Appendix C: The Complete UniPoly Class
Appendix D: The Complete Guitar Class Hierarchy
Appendix F: Production Notes

13.2 Bar charts

Bar charts are popular in the media to show count and measurement data. I suspect people create many of these in Microsoft Excel, but you can also use matplotlib to make bar charts for display or publication. We saw bar charts when we generated histograms for the results of quantum circuits in section 9.7.2.

Most of the methods, functions, and stylistic control we saw in the last section for plots also apply to bar charts. Experiment until you like what you see.

13.2.1 Basic bar charts

The most straightforward bar chart corresponds to a list of numeric data values. These values are the heights of the bars.

import matplotlib.pyplot as plt

data = [21, 14, 10, 9, 19]

# draw the bar chart
bar_chart = plt.bar(range(1, len(data) + 1), data)
<Figure size 432x288 with 1 Axes>
plt.show()
A basic bar chart with 5 bars

It’s more informative for your bar chart viewers if you label the chart and the horizontal ...