Book Image

Python Automation Cookbook - Second Edition

By : Jaime Buelta
Book Image

Python Automation Cookbook - Second Edition

By: Jaime Buelta

Overview of this book

In this updated and extended version of Python Automation Cookbook, each chapter now comprises the newest recipes and is revised to align with Python 3.8 and higher. The book includes three new chapters that focus on using Python for test automation, machine learning projects, and for working with messy data. This edition will enable you to develop a sharp understanding of the fundamentals required to automate business processes through real-world tasks, such as developing your first web scraping application, analyzing information to generate spreadsheet reports with graphs, and communicating with automatically generated emails. Once you grasp the basics, you will acquire the practical knowledge to create stunning graphs and charts using Matplotlib, generate rich graphics with relevant information, automate marketing campaigns, build machine learning projects, and execute debugging techniques. By the end of this book, you will be proficient in identifying monotonous tasks and resolving process inefficiencies to produce superior and reliable systems.
Table of Contents (16 chapters)
14
Other Books You May Enjoy
15
Index

Plotting a simple sales graph

In this recipe, we'll see how to draw a sales graph by drawing bars proportional to sales in different periods.

Getting ready

We can install matplotlib in our virtual environment using the following commands:

$ echo "matplotlib==3.2.1" >> requirements.txt
$ pip install -r requirements.txt

In some OSes, this may require us to install additional packages; for example, in Ubuntu, it may require us to run apt-get install python3-tk. Check the matplolib documentation for details.

If you are using macOS, it's possible that you'll get an error like this: RuntimeError: Python is not installed as a framework. Refer to the matplotlib documentation on how to fix it: https://matplotlib.org/faq/osx_framework.html.

How to do it...

  1. Import matplotlib:
    >>> import matplotlib.pyplot as plt
    
  2. Prepare the data to be displayed on the graph:
    >>> DATA = (
    ...    ...