Book Image

Python Automation Cookbook

By : Jaime Buelta
Book Image

Python Automation Cookbook

By: Jaime Buelta

Overview of this book

Have you been doing the same old monotonous office work over and over again? Or have you been trying to find an easy way to make your life better by automating some of your repetitive tasks? Through a tried and tested approach, understand how to automate all the boring stuff using Python. The Python Automation Cookbook helps you develop a clear understanding of how to automate your business processes using Python, including detecting opportunities by scraping the web, analyzing information to generate automatic spreadsheets reports with graphs, and communicating with automatically generated emails. You’ll learn how to get notifications via text messages and run tasks while your mind is focused on other important activities, followed by understanding how to scan documents such as résumés. Once you’ve gotten familiar with the fundamentals, you’ll be introduced to the world of graphs, along with studying how to produce organized charts using Matplotlib. In addition to this, you’ll gain in-depth knowledge of how to generate rich graphics showing relevant information. By the end of this book, you’ll have refined your skills by attaining a sound understanding of how to identify and correct problems to produce superior and reliable systems.
Table of Contents (12 chapters)

Adding legends and annotations

When drawing graphs with dense information, a legend may be required to determine the specific colors or help better understand the data presented. In matplotlib, legends can be pretty rich and have multiple ways of presenting them. Annotations to draw attention to specific points are also good ways to focus the message for the audience.

In this recipe, we'll create a graph with three different components and display a legend with information to better understand it, as well as annotating the most interesting points on our graph.

Getting ready

We need to install matplotlib in our virtual environment:

$ echo "matplotlib==2.2.2" >> requirements.txt
$ pip install -r requirements...