Book Image

The Python Workshop

By : Olivier Pons, Andrew Bird, Dr. Lau Cher Han, Mario Corchero Jiménez, Graham Lee, Corey Wade
Book Image

The Python Workshop

By: Olivier Pons, Andrew Bird, Dr. Lau Cher Han, Mario Corchero Jiménez, Graham Lee, Corey Wade

Overview of this book

Have you always wanted to learn Python, but never quite known how to start? More applications than we realize are being developed using Python because it is easy to learn, read, and write. You can now start learning the language quickly and effectively with the help of this interactive tutorial. The Python Workshop starts by showing you how to correctly apply Python syntax to write simple programs, and how to use appropriate Python structures to store and retrieve data. You'll see how to handle files, deal with errors, and use classes and methods to write concise, reusable, and efficient code. As you advance, you'll understand how to use the standard library, debug code to troubleshoot problems, and write unit tests to validate application behavior. You'll gain insights into using the pandas and NumPy libraries for analyzing data, and the graphical libraries of Matplotlib and Seaborn to create impactful data visualizations. By focusing on entry-level data science, you'll build your practical Python skills in a way that mirrors real-world development. Finally, you'll discover the key steps in building and using simple machine learning algorithms. By the end of this Python book, you'll have the knowledge, skills and confidence to creatively tackle your own ambitious projects with Python.
Table of Contents (13 chapters)

Visual Analysis

Most people interpret the data visually. They prefer to view colorful, meaningful graphs that make sense of the data. As a data science practitioner, it's your job to create these graphs.

In this section, you will primarily focus on two kinds of graphs: histograms and scatter plots. You will use Python to create these graphs. Although software packages such as Tableau are rather popular, they are essentially drag and drop. Since Python is an all-purpose programming language, the limitations are only what you know and are capable of doing.

The matplotlib Library

A popular Python library for creating graphs is matplotlib. It's traditionally imported as plt, as shown in the following code snippet:

import matplotlib.pyplot as plt
%matplotlib inline

Note the strange second line of code. It basically shows all graphs within Jupyter Notebooks instead of exporting them to external files. It's used when you want to see the graphs right there in...