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Data Wrangling with Python by Katharine Jarmul, Jacqueline Kazil

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Chapter 10. Presenting Your Data

You’ve learned how to analyze your data, and now you’d like to present it. Depending on the audience you have in mind, the presentation can differ greatly. We’ll learn about all different types in this chapter: from simple presentations you can make on your computer to interactive website presentations.

Depending on what you’d like to present, your visualization, with charts, maps, or graphs, might be a major part of the story you are trying to tell. We will cover how to get your own site up and running to share your findings. We’ll also show you how to share a Jupyter notebook, where folks can see your code along with the charts, graphs, and conclusions.

To begin, we’ll explore how to think about your audience and begin telling the stories you have found via your data analysis.

Avoiding Storytelling Pitfalls

Storytelling is not an easy job. Depending on your topic, you might have a difficult time determining solid conclusions from your data. You might encounter inconsistent or inconclusive data. This is OK! We recommend continuing to explore—maybe the story is in the disparate examples you find in your datasets.

Warning

Some of the difficulties you face in storytelling will be due to personal biases you bring to your data analysis. As economist and journalist Allison Schranger aptly discusses in her article “The Problem with Data Journalism”, we bring biases to our analyses that we can’t adequately counter. Her sage advice is to admit those biases ...

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