AI & Python #37: Books I Read to Automate Some Boring Tasks
Python automation.
In this article, I will show you 3 books that helped me automate tasks such as sending emails, collecting data, creating reports, and more!
1. Automate the Boring Stuff with Python
This is a book that I think many have heard of. Automate the Boring Stuff with Python teaches you how to write programs that can accomplish in minutes what would take hours to do manually. Unlike some books listed in this article, this book doesn’t require any prior programming experience.
The book starts with some Python basics and then explains how to automate tedious tasks such as searching for text in a file, creating files, renaming files, searching the web, downloading content from the web (also known as web scraping), and sending email responses and text notifications.
The fact that Automate the Boring Stuff has a section that covers web scraping, makes this book worth it for data scientists. This skill will allow you to build your own dataset for your next data science project.
Also, I consider automation projects essential for those who have to deal with lots of repetitive tasks at work. If you’re quite familiar with the basics of Python, I would recommend you skip Part I and pick a project that you find interesting in Part II. By solving these real-world problems you will increase your knowledge of Python while automating your life.
2. Python Automation Cookbook: 75 Python automation ideas
This book is for Python beginners who want to expand their knowledge by automating everyday tasks. That said, you should at least know the basics of Python before reading this book.
The book contains 75 Python automation ideas with applications in the areas of marketing, sales, data science, and more. You will learn how to automate the web, generate automatic spreadsheet reports with graphs, communicate with automatically generated emails, get notifications via text message, and schedule tasks on your computer.
In the latest edition of this book, two new chapters were added: Cleaning & Processing Data and Machine Learning for Automation. Both are great chapters for those who want to automate data science tasks.
In Cleaning & Processing Data, you will learn how to batch process to speed up working with large data. I liked this project idea because cleaning and processing data usually takes a lot of a data scientist’s time.
On the other hand, the Machine Learning for Automation chapter shows how to use Google’s Machine Learning APIs to extract text from images. At the end of the chapter, you will create and train a model that detects which department an email should be assigned using text as input.
3. Python for Excel: A Modern Environment for Automation and Data Analysis
Microsoft Excel is probably the most popular tool used for data analysis; however, its automation language, VBA, stopped evolving a long time ago. This is why some Excel users adopted Python to automate their everyday tasks.
In this book, the creator of xlwings (a package to automate Excel with Python) shows how to integrate both Python and Excel efficiently. The book starts with some Python core concepts and then teaches you all the stuff you need to learn for automation and data analysis. You will learn how to use Pandas to clean and analyze data, learn xlwings to build interactive Excel tools (using Python under the hood), and automate tedious tasks like consolidating Excel workbooks and producing reports.
By the end of the book, you will replace VBA, Power Query, and Power Pivot with Python.