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Hey monster man.

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Awesome work so far.

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This is Bruno.

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Hey listen great work on the last project but we have another client and they need this ASAP.

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We have a hospital with a ton of patient records and they have no idea how to use Excel.

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They don't really understand all what the numbers mean.

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We need something visual for them to understand and predict whether a patient might have heart disease

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or might get heart disease or not.

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So here's some data I need you to visualize it for me and make it look pretty so that we can present

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it to the hospital.

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You're cool with that right.

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All right.

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Great.

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I heard this library map LA lib is gonna do the job.

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Oh by the way the clients really like the color blue so make sure the visualizations are in blue.

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I know kind of a weird request but hey they pay us the money.

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We got to do what they say.

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All right everybody.

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It's time to learn about data visualization.

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Now this is a really fun topic because we get to make pretty visualizations pretty charts to understand

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data better.

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But keep in mind that data visualization is one of those tricky things where it might be really easy

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to create something visual but the most important part is to create something that's actually meaningful.

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It's very easy to do data visualization wrong to present a graph that is misleading.

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A graph that is not accurate when it comes to data visualization we have to make sure that what we represent

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visually is accurate precise and is meaningful.

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That's our job.

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A data scientist turns data that is useless to data that is useful in data visualization is a big part

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of that.

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So let's get started.