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Course

Basic

How to Read and Write Excel Files in Python

Learn how to work with openpyxl, a popular Excel processing library in Python! Find out how to open, read, and write an Excel file in Python.

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45

Interactive exercises

10 h

Estimated time

260

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Python is a general-purpose language that allows you to perform various tasks related to programming and data science. Thanks to Python, you can freely process many different file formats including Excel and automate your daily work.

Excel, a spreadsheet application developed by Microsoft, is one of the most popular data exchange formats used by businesses and individuals. Most likely, you too are using Excel to record expenses, plan budgets, track progress, and complete many other tasks. Why not use Python to automate boring, everyday Excel-related tasks? Write some code that will do the work for you, and you will have more time to plan your next steps and strategies. Work more efficiently, because time is money!

“How to Read and Write Excel Files in Python” is an online course that introduces you to working with Excel files in Python. You'll learn how Excel files are built and how to work with them, with practical examples. You’ll learn how to process Excel files with openpyxl, a popular Python library that allows you to read and write Excel 2010 and later. We use Python version 3.0.4 for this course, but the features covered in the course are compatible with versions going back to 2.5.0.

In the course, we will first examine how Excel files are organized, and review some basic terminology related to Excel spreadsheets. After the introduction, we will explain how to read Excel files with openpyxl and how to process them in for loops. Finally, we will see how to create Excel files and modify their content in Python. In the final quiz, you’ll do several practical tasks on Excel files.

“How to Read and Write Excel Files in Python” is one of the courses from our Python File Processing track, where you'll learn to work with different file formats in Python. You can complete the courses from this track in whatever order you wish, since they don’t depend on each other. See what will be most useful to you! Remember that each course is a way to make your daily work easier.

Do you deal with Excel files at work? Then this skill is a must-have on your list.

Are you a data science beginner or a business professional performing data analysis using Excel files? Then this course is perfect for you!

Scroll down for an overview of the topics covered in this course, and for more about who all can benefit from it.

What's in It for Me?

  • 45 interactive exercises. Learn at your own pace, anywhere and anytime. Interact with hands-on exercises for improved retention.
  • Lifetime access to the course. When you purchase the course, you'll get instant personal access to all of its content.
  • Certificate of completion. After you successfully finish all of the exercises, you'll get a downloadable PDF certificate to showcase your accomplishment.
  • 30-day money back guarantee. If you're not satisfied with the quality of the course, you can get a refund within 30 days of your purchase.
  • Hints for the exercises. You can ask questions and share insights with other members of the community through the Discuss tab. We'll be more than happy to answer! 😉

What Are the Requirements?

Learn How to:

  • Name the elements of Excel files.
  • Work with Excel files in Python.
  • Open and read an Excel file with openpyxl.
  • Create an Excel file in Python.
  • Write to an Excel file and modify its contents in Python.

Who Should Take This Course?

  • Students taking entry-level classes in Python.
  • Data analysts and other people interested in data science in Python.
  • Business professionals using Excel to analyze data.
  • Anyone working with Excel files who wants to automate simple work tasks.

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1.

Spreadsheet Basics & Opening Excel Files

Learn the basic structure of Excel spreadsheets and how to open them in Python.

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4.

Final Quiz

Put your new skills to the test in these challenging exercises.

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