From the course: Data Visualization with Python in Excel

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Solution: Create and customize a seaborn visualization

Solution: Create and customize a seaborn visualization

From the course: Data Visualization with Python in Excel

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Solution: Create and customize a seaborn visualization

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(bright upbeat music) - [Presenter] Welcome back. I hope you had fun flexing your Seaborn skills on the classic MPG dataset. I'm going to walk you through a possible solution set here, but if yours are slightly different, that's perfectly fine and great. There's a lot of room for interpretation and creativity and data visualization, and no one size fits all solution. Go ahead and open Seaborne Challenge to follow along. I've read the dataset in here as MPGDF. Let's start on the next worksheet with a scatterplot. We'll use the hue argument to ensure that each origin gets its own color. Then add the usual axis labels and title. Next, we'll look at the distribution of MPG by origin. I suggested either a KDE plot or a violin plot, and here, I've included both. So which one is better? Well, to borrow the data analyst's favorite answer, it depends. The KDE plot on the left provides a smooth density estimate, ideal for observing the overall shape and main density areas of miles per gallon…

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