‫Hey, monster man.
‫Awesome work so far.
‫This is Bruno.
‫Hey, listen, great work on the last project, but we have another client, and they need this ASAP.
‫We have a hospital with a ton of patient records and they have no idea how to use Excel.
‫They don't really understand all what the numbers mean.
‫We need something visual for them to understand and predict whether a patient might have heart disease
‫or might get heart disease or not.
‫So here's some data.
‫I need you to visualize it for me and make it look pretty so that we can present it to the hospital.
‫You're cool with that, right?
‫All right, great.
‫I heard this library map.
‫La Lib is going to do the job.
‫Oh, by the way, the clients really like the color blue, so make sure the visualizations are in blue.
‫I know kind of a weird request, but hey, they pay us the money.
‫We got to do what they say.
‫All right, everybody, it's time to learn about data visualization.
‫Now, this is a really fun topic because we get to make pretty visualizations, pretty charts, to understand
‫data better.
‫But keep in mind that data visualization is one of those tricky things where it might be really easy
‫to create something visual.
‫But the most important part is to create something that's actually meaningful.
‫It's very easy to do data visualization, wrong, to present a graph that is misleading, a graph that
‫is not accurate.
‫When it comes to data visualization, we have to make sure that what we represent visually is accurate,
‫precise and is meaningful.
‫That's our job.
‫A data scientist turns data that is useless to data that is useful, and data visualization is a big
‫part of that.
‫So let's get started.