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Python Automation Cookbook

You're reading from   Python Automation Cookbook 75 Python automation recipes for web scraping; data wrangling; and Excel, report, and email processing

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Product type Paperback
Published in May 2020
Publisher Packt
ISBN-13 9781800207080
Length 526 pages
Edition 2nd Edition
Languages
Tools
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Author (1):
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Jaime Buelta Jaime Buelta
Author Profile Icon Jaime Buelta
Jaime Buelta
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Toc

Table of Contents (16) Chapters Close

Preface 1. Let's Begin Our Automation Journey 2. Automating Tasks Made Easy FREE CHAPTER 3. Building Your First Web Scraping Application 4. Searching and Reading Local Files 5. Generating Fantastic Reports 6. Fun with Spreadsheets 7. Cleaning and Processing Data 8. Developing Stunning Graphs 9. Dealing with Communication Channels 10. Why Not Automate Your Marketing Campaign? 11. Machine Learning for Automation 12. Automatic Testing Routines 13. Debugging Techniques 14. Other Books You May Enjoy
15. Index

Reading an Excel spreadsheet

MS Office is arguably the most common office suite software, making its formats pretty much standard. MS Excel is probably the most common spreadsheet application and the Excel format is the most common spreadsheet format, mirrored by many other spreadsheet applications.

In this recipe, we'll see how to obtain information from an Excel spreadsheet using the openpyxl module in Python.

Getting ready

We will use the openpyxl module. We should install the module, adding it to our requirements.txt file as follows:

$ echo "openpyxl==3.0.3" >> requirements.txt
$ pip install -r requirements.txt

In the GitHub repository, there's an Excel spreadsheet named movies.xlsx that contains information on the top 10 movies by attendance. The file can be found here: https://github.com/PacktPublishing/Python-Automation-Cookbook-Second-Edition/blob/master/Chapter06/movies.xlsx.

The source of the information can be found at...

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