[MUSIC] So, now that we've took
a quick look at the dataset, let me show you something pretty cool. So, let's introduce what's
called the GraphLab Canvas. So this kind of type or data, graph
data takes an image data that we have. There's many ways you can visualize it. What we have inside GraphLab Create
is a data visualization companion that can be used to view
the data in various ways. So if you take any data
structure that we play with, any data structure GraphLab Create. So Take any data structure, In GraphLab Create and
you type .show after it. So if you type sf.show is going
to start the GraphLab Canvas and give you visualization,
first visualization of the data structure. In this case,
we have a very simple dataset. When I tab, it does show,
it gives me a link here to a new Web page that
shows you that dataset. So I'm gonna decrease
the font size a little bit. And you'll see that this
dataset has four columns. The First Name, Alex,
Malcolm, Felix, and so on. The Last Name. The Country this person lives in and
their age. And you see that the max age is 25,
the min age is 22, the median age is 23 the mean
age is 23.143 and so on. And if you can click on tabular view,
you can actually view the data. And this is pretty cool. If you have a million rows, it's
really hard to actually view the data. But this allows you to
scroll through millions, 1 billion rows you could scroll
through with this tabular view. And now, if I click on any column,
for example, the age column, it's going to give me, sorry, I selected
something here which was a little weird. Let me just type reload because
it did something funny. A histogram, but if I type Categorical, it's gonna sort it by
the most common value. You see that the most common Value Is
a 23, there's 3 of these folks, and so
that's 42% of the data has age of 23. So we can play with Canvas and visualize
the data in various ways and get started. Now for the notebooks that
we're filming here, the Canvas popping up in a new window like this
makes it kind of awkward to go back and forth when we're just filming. So, instead of open as a new window,
what I'm going to see is how to open the Canvas or some of visualizations
inside of the IPhython Notebook. So, I'm going to call a command
called graphlab.canvas.set_target, and I'm gonna say that the target is
the IPython Notebook, short ipynb. And we're gonna do this again,
and again, and again. But what happens is now the visualizations
that we do are all gonna target this actual notebook. So, let's visualize, again, the age
column, but now inside our notebook. So here's what we're gonna do,
it's pretty cool. We're gonna take this s frame,
sf, and I'm gonna select. The square brackets allows you to select
a particular column or many columns. So, I'm gonna select the column age,
just one, and I'm gonna type .show on it. And I'm gonna tell it that
the view that I want is that sorted Categorical
view that we just saw. So, here we go. We just saw that 23 is
the most common age. People with 23 years of age,
42% of the data. So, now we see how to do a little bit
of visualization using GraphLab Create. We're gonna see several other
visualizations within GraphLab and within other tools during the course. [MUSIC]