An Exploration Of Effective Pandas Practices With Matt Harrison


January 15th, 2022

49 mins 57 secs

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About this Episode


Pandas has grown to be a ubiquitous tool for working with data at every stage. It has become so well known that many people learn Python solely for the purpose of using Pandas. With all of this activity and the long history of the project it can be easy to find misleading or outdated information about how to use it. In this episode Matt Harrison shares his work on the book "Effective Pandas" and some of the best practices and potential pitfalls that you should know for applying Pandas in your own work.


  • Hello and welcome to Podcast.__init__, the podcast about Python’s role in data and science.
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  • Your host as usual is Tobias Macey and today I’m interviewing Matt Harrison about best practices for using Pandas for data exploration, manipulation, and analysis


  • Introductions
  • How did you get introduced to Python?
  • What motivated you to write a book about Pandas?
    • There are a number of books available that cover some aspect of the Pandas framework or its application. What was missing from the available literature?
    • Who is your target audience for this book?
  • What are some of the most surprising things that you have learned about Pandas while working on this book?
  • What are the sharp edges that you see newcomers to pandas run into most frequently?
  • It is easy to use Pandas in a naive manner and get things done. What are some of the bad habits that you have seen people form in their work with Pandas?
    • How and when do those habits become harmful?
  • What are the most interesting, innovative, or unexpected ways that you have seen Pandas used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on this book?
  • What are some of the projects that you are planning to work on in the near/medium term?

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Closing Announcements

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA