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Welcome back.

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Now we're really going to step it up a notch.

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We're going to see the full power of the map politely but object orientated method.

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We're going to build upon what we've done here.

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So we've created this this heart disease and cholesterol levels with our over 50s data frame.

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But now we're going to add a subplot to this so we can visualize cholesterol levels and we might get

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out over 50 data frame here so we can stop having to scroll up we're going to combine that with fell

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act which is I'm not sure if I'm pronouncing that by the way either fell ash which is Mack's heart rate.

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So we want to have a subplot where we've got cholesterol and fell patch on the y axis is but they're

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both going to have age as the x axis.

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So let's see that in action.

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We want to title this subplot of coal age though which beautiful Well we want to go here.

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We're going to recreate this we could copy and paste this code but again we want to practice writing

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from scratch.

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So let's see it in full force Fig.

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We want to use the object orientated method.

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Now if you've had a go at creating a subplot on your own.

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This is the way you might have used but if not this is how I would create a subplot of these two.

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So remember we want two different accesses.

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So fig axe zero and ax.

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This is gonna be ax one.

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There we go.

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So what this is saying is now we're creating a single figure but it's going to have two axes on it.

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Remember axes are this year why in X where you can add data.

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So let's use the same commanders before some plots.

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And I want to end rows equals two.

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We want in calls is gonna be one our previous figure size was 10 and six.

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But let's make this ten and ten see what that looks like.

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And now we want to go add data to ax zero.

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Actually let's see what this looks like before we even plot fig size.

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Oh we got an equal there beautiful.

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So now we've got two blank canvases to start adding our data on here.

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So we want to add data to access zero which is this one here so just gonna be this exact same as before.

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We'll do something like this.

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So now we're gonna add some data to access zero just like we've done up here.

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We're gonna do something similar to this but again we're not copying pasting we'll do it from scratch

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so we won't scatter equals ax zero dot scatter and we're gonna go X is going to be the over 50 age column

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Y equals over 50.

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And this is gonna be just a collateral column beautiful.

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And then we're going to go see equals we're gonna color it with over 50 target column.

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Now let's see what that looks like.

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Beautiful we've seen this before.

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So customize at 0 0 we want to go X 0 dot set and we want to add a title.

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This is gonna be heart disease and cholesterol levels.

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Wonderful.

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And then we want an X label which is going to be age and then we want to go y label which will be cholesterol.

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Nothing new here we've seen this before but now it's only on axis zero which is amazing.

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Maybe we add at a legend to act zero same code as a four x zero dot legend scatter dot legend elements

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and then we're going to go.

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Title Eagle's target.

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Beautiful.

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What did we have up here.

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We had a main line.

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So that's what we can do with the hate line.

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So add a main line.

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So we're just replicating the plot we've done before axis zero dot.

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Page line No we need to pass hate line of why so we want over 50s.

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It's going to be a cholesterol.

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So we'll do well dot main and then we'll add a line style as dash dash and that should be the same plot

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as what we've got above.

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But now it's on a subplot so I want to challenge you to before we go through it.

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See if you can replicate what we've done here but with the foul ash column instead of the cholesterol

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column on this subplot here I'll give you a second.

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All right.

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If you had a go.

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All good.

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If not let's go through it.

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So now we want to add data to ax 1 because remember we've got X one up here.

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Excellent.

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Same thing we've done before but this time all we're going to do is change it from ax zero to ax 1.

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And then of course the column will be different all the data that we use will be a little bit different.

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So in this case it's 1 x the X is still going to be the age column.

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What's going to change is what's on the y axis.

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So we are over 50 now actually.

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Wonderful.

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Color is gonna be the same because we're focused on our target variable which is whether or not the

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patient has heart disease.

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So there we go.

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Let's see what this looks like okay.

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So we're starting to get somewhere now.

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We've got some data on both our axis is let's customize it just like we've done with Axis zero.

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And do that with x 1 x 1 don't set let's add a title title.

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This one will be heart disease and max heart right.

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Wonderful.

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And then we're going to go X label.

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Okay everyone that is just that age because we're using the same column for The X and the Y label.

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This is gonna be fell act so we'll actually put in max heart rate because we want it to be a bit more

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communicative than just that latch.

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So if someone came and had a look at our plot didn't know what flash meant they'll know it means max

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heart rate okay.

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Standing graphics and progress.

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Now we still have a couple more things to do.

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We want a similar set up to what we've got here.

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So let's add a legend to X1 axe one bolt legend.

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Now again we're creating quite similar plots here with the subplot that we're making.

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So these two are quite similar as you've seen before you could have a scatter plot here and you could

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have a histogram here or something like that but we're just using this as an example.

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So title ego's target wonderful.

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Well I don't mean line as well.

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So Ax one dot ax.

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Page line now we're gonna color it with the Y is going to be this time instead of cholesterol it's going

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to be all that wonderful dot main and then the line style we're going to keep it with our trusty dash

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and then we'll add a semicolon here and let's have a look.

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What have we messed up.

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We got an error line today has no property line star.

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This is classic typos everywhere.

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Here we go.

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So it's okay to make errors right.

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You're never going to type out all the code correctly every time the first time beautiful.

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This is starting to look really good.

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Okay.

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What we're starting to see we've got to age x axis label here but this is also age so maybe we could

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tell them to share the X..

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So let's say where can we add that maybe have in here.

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I want to share the X so share X equals true

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but now we can remove this label on access zero so what is this going to do if we put in share X equals

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true.

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What do you think.

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There we go.

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So what this is done is it's telling our plot to go that our subplots here have the same x value so

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we don't need to put in the age label there maybe you would keep it in there for a bit more.

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So it's a bit more communicative that's kind of one way you can start to clean up your plots.

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And now what we might do is add a title to this overall things.

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We've got both subplots are titled What we might want to title the entire figure.

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So let's see how we do that.

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Add a title to the figure.

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Now this is big because remember we've created a figure and we've added data and customization for the

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actresses but now we want to start to access the figure directly which is that big blue square on our

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map plot level anatomy.

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We filled up these two and our subplots.

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Now we want a title our figure so we can do that with Fig Doc sup which he stands for I think it says

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for Super title I actually don't know what some stand for.

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I just know that it's subtitle and then we go.

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Heart disease analysis and we'll create the font size we want it to be pretty big font size and a font

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weight of bold and put a semicolon at the end beautiful.

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Look at this.

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Maybe we have to zoom out a tiny bit so we can see it all in one hit.

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There we go.

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Are you starting to see what this is kind of looking like.

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Remember right at the start in the concept lecture we looked at the anatomy of a map plotted figure.

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We looked at that plant and it was quite complex has a lot going on.

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Well what you've done is you've just followed along and recreated something very similar.

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Now what we're going to do in the next video is style this a little bit better so fix up some of the

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colors.

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The important thing to remember is it looks like a lot of code here and actually is.

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We've got 25 30 lines of code there.

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But what we've done is we've built this figure from scratch using the object orientated map plot lib

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method.

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And so now what seemed at the start to be a very complex and complicated plot is actually just quite

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simple right.

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You create a figure you create a couple of accesses you add data to the accesses you add some customizations

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like titles and a legend in a horizontal line and you start to get something looking like this.

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Now that's something that you can put in a demonstration or show your colleagues in a presentation something

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like that right now you're starting to see just how powerful that plot lib object orientated API can

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be.

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All right let's wrap this video up have a practice maybe create your own subplot without a scatter try

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a histogram and maybe a bar graph.

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Can you do that on the same figure.

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Otherwise I'll see you in the next video and we'll learn a little bit more customization of these plots.