Hello everyone and welcome to the introduction to Seaborn lecture and this lecture we're going to briefly
go over what seaborne is how to get it installed onto your computer and how to find the official documentation
.
Seaborn is a statistical plotting library and it's built on top of map plot lib.
So all that map plot lib knowledge that we just learned is going to be really useful when learning about
seaborne seaborne has really beautiful default styles and it's also designed to work really well with
depan those data from objects in order to get it installed onto your computer.
You're going to have to use either Kada install seaborne.
If he's in the Anaconda distribution of Python or if you install Python from some other source you can
also use Pipp install seaborne and just do either your command line or terminal.
Let's go ahead and get a quick tour of the official Web site.
I'm going to go and go to Google and show you how to find the official documentation.
All right here I am at Google in order to find the link to the official documentation.
Since Seaborn is open source it's hosted on get home so you can go in and say get seaborne python.
And that should take you to this firstling right here hub.
And on this page you actually can read all the code says it's open source as far as the statistical
library for this data visualization.
But more importantly you scroll down here you'll see a link to the official documentation.
Go ahead and click this link and it should take it to the official documentation page.
Now something that's nice about this official documentation page is just like any map plot lib site
it has a gallery something that's not so nice is that I wouldn't use this gallery as a reference.
It's more just of a couple of nice examples of what seaborne was able to do.
So go out and click on some of these pictures such as heat map violin plot box plot adjoint plot and
we're going to learn how to create all these plots how to use C more effectively with pandas.
So here's just a couple of quick examples of the kind of things we're going to able to do.
We're going to make really nice looking heat plots or heat maps violin plots grouped box plots and hex
been joint plots you can already probably tell that see Bourne and style go hand-in-hand.
SEABORNE is a really nice looking visualization library.
The other really important link besides the gallery page is the API and the API reference is basically
a reference to the various plot types here.
And this is what we're going to be going over as we learn how to use Seaborn.
So we're going to really effectively learn how to actually call these plots utilize pandas of these
plots and create really nice looking statistical plot visualizations.
All right.
I'm really excited to get started.
Seaborn is one of my favorite libraries for Python So let's go ahead and jump to the next lecture or
actually start coding out Seaborn code.
Thanks everyone and I'll see you at the next lecture