From the course: Python Data Visualization: Create Impactful Visuals, Animations, and Dashboards by Pearson

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Demo

Demo - Python Tutorial

From the course: Python Data Visualization: Create Impactful Visuals, Animations, and Dashboards by Pearson

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Demo

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In this demo, we're going to explore Seaborn. We already saw in the previous sections how Seaborn works and how it's structured, and now we're going to get our hands dirty and generate some visualizations using Seaborn. We import all the packages. Before now, we're going to import Seaborn as SNS, which is the standard way. We're also going to use Contextily, which is a simple plotting mapping library that's able to use map tiles from different map providers that we're going to use in some of our visualization going forward. Also, we have Scikit-learn that we're going to use in a couple of examples. The Seaborn I'm using is 0.13.2, Scikit-learn 1.5.2, but actually 1.6.2. Seaborn comes with a number of datasets to make your life easier and to let you explore the functionality of Seaborn more easily. You can get the list of datasets by calling get underscore dataset underscore names. And if you want to load a specific dataset, all you have to do is call load datasets with the dataset…

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