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)
Part I: Getting to Know Python
PART II: Algorithms and Circuits
PART III: Advanced Features and Libraries
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Appendix C: The Complete UniPoly Class
Appendix D: The Complete Guitar Class Hierarchy
Appendix F: Production Notes

14.3 pandas DataFrames

A DataFrame is a flexible 2-dimensional data structure that represents rows and columns. The rows are records, and the columns are data of a particular feature. For example, we will see a DataFrame where the rows correspond to cats, and the columns include their breed and color.

We can access the rows and columns in ways that resemble both lists and dictionaries; that is, we can use numeric indices or string labels/keys. pandas is built on numpy and matplotlib, so you can use their functions and methods for computation and visualization. We discussed those packages in Chapter 13, Creating Plots and Charts.

pandas is a very large Python package and has many functions and methods for working with DataFrames. [PAN] You can often get the result you seek by using Pythonic combinations of row and column operations together with indexing and slicing. Other ...