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 gonna 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 in data visualization is a big part
of that.
So let's get started.