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Welcome back.

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In the last video we checked out a few different methods of creating that plot.

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Live plots and figures.

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That name is kind of interchangeable same with the name visualization.

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If you hear that they're often referring to the same thing and we looked at a little trick with the

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little percentage sign to set up map plot lib so that our plots appear in our Jupiter notebooks.

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So now we're going to start this video off by checking out the map plot lib and anatomy of a figure

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so let's have a look.

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As I just said I got anatomy of a map plot lib plot and I just said we're going to check out the anatomy

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of a figure.

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So this is how I mean these words are very interchangeable.

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So I want you to be aware of that whenever you're looking at that plot live online.

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If you go in a stack overflow or whatever resource that documentation probably is more formal using

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the word figure we'll see that in a moment.

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But it refers to plot or visualization there always meaning kind of the same thing which is this complicated

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but beautiful mess here.

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So if we look at it figure is kind of like the giant section here the everything.

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The blue square sort of figure contains all of it it's like the blank canvas and then what we're going

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to do is start to add things as we go to make our plots look beautiful.

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So we've got some data here.

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This is heart disease analysis.

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This is the center title.

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Don't worry if this looks a little bit more complicated than the plot we've just done.

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This is a very simple plot here.

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This one's got a bit of fancy colors and a horizontal line titles and legends.

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We're going to work towards making something like this but by the end of the section so we'll get there

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in a moment.

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But you can see here these two axes.

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This is a subplot.

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We've got one plot here actually zero.

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And this is axes one.

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So there's two types of information here.

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But they share an x axis which is the age.

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We've got an x axis label here.

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We've got axes one tidal wave.

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This one's got a legend.

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So does this.

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And then we've got two different y axes label.

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So this one is max heart rate and this one is cholesterol.

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And we've got a main line going through here.

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You might want to take a screenshot of this but don't worry it'll be in the resources section.

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This is kind of the anatomy of most map plot live plots that you'll check out at least for 2D plots

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anyway.

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So yeah you've got label titles and what all these little things do is that they just add to the communication

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value.

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Of course you could make a plot without these titles or these horizontal lines or these fancy colors

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but it would be kind of hard to understand.

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So that's why we add these things here.

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Let's go back before we jump into the next video.

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Let's have a little bit of a look where the object oriented comes from.

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So if we go back to this cell here we might go type thing type

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so here we go.

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We've got map plot libbed figure dot figure.

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So the formal definition for something like this is a figure and then we have map plot lib dot axes

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dot subplots to access subplot.

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So this is what it means when that plot labor talks about the object oriented API.

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So we've got the figure object which is back to our anatomy.

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This is the figure object here.

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This big blue square and then we have the axes objects and now the axes objects.

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They're always kind of a subplot because this is a subplot on a figure but you can have more than one

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axes on a figure if that makes sense.

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If we had two more of these over here this blue box would stretch out to cover those.

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So the figure is the base canvas and the axes are like we're drawing on that base canvas now that we've

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kind of understood the fundamentals of map plot layer with the figure and the accesses.

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Let's check out a workflow in its entirety.

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So we'll type in here map plot lib example workflow.

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Make this a heading so it's a little bit separate map plot lib example workflow.

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So step 0 is import map plot lib and get it ready for plotting in Jupiter beautiful.

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Now we've already done this but I would just want to do it all in one cell so you can see it happening

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that partly inline import map plot lib dot higher plot as P L T step one is to prepare some data prepare

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data X equals we'll keep it nice and simple just as we did before but you'll see in reality X and Y

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can be basically any data or any numbers that you can imagine will go to number three we're getting

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ahead of ourselves here.

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Set up plot.

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Now this is where we use the object orientated method.

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Fig ax equals P LTV dot subplots.

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We're gonna throw in a little keyword here that I want to introduce you because you'll see this a lot.

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Fig size 10 10.

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Now let's see what this means.

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Can we go shift tab.

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Yes we can.

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We go down.

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Is it going to have it.

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It might not figure size parameters.

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We'll keep scrolling through here.

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It's a bit hard to see excise acts.

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Examples.

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Well I'll just tell you what it is.

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Oh you can practice looking at the documentation but what this essentially means is it just height and

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width and they may be back to front.

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It's usually x then y.

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So this is probably width and this is probably height.

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That just means the dimensions of this plot so we'll get here.

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Then we'll go to number three which is plot the data.

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So we want to add to our x x and y.

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What have we done here.

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We've created the figure and we've created an axes and now what we're doing is adding data to our axes.

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Okay.

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Yeah.

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This is making sense for and then we want to customize plots.

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Now we haven't seen names but they're fairly intuitive so I'll let you guess as I'm typing them out

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simple plot.

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That's a good title I think what they actually mean.

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So now that we've we've done just one what do you think we've got we've got X dots set and then a parameter

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saying Title X equals simple plot x axis.

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We'll keep the titles for the X and Y nice and simple Y equals Y axes.

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Wonderful.

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And then we'll go to number five.

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You probably wouldn't usually do this I'm just showing you all this in one hit just for the sake of

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seeing a map plotted workflow running live save the whole figure.

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That's what I'm looking for.

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That's what I said out loud but that's what I didn't type.

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Fig.

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Don't save Fig.

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And then we want to save it too.

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I've got the images folder set up that I already have prepared earlier so you can save it wherever you

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want but this is just going to be the path name sample plot PNG.

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There we go.

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So let's step through this.

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We import map pot lib.

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We tell Jupiter that we want to plot our map plot lib plots in line or figures in line so within the

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notebook we've created some data.

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X and Y.

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We've set up a plot.

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Okay a figure we've given it a size of 10 by 10.

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We've added some data to the plot on our axis and then we've customized the plot.

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Now can you guess what's going to happen here if we look at this.

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Then if we compare it to our anatomy we've got a title we've got X and Y labels.

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Can you guess what this is going to do here.

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We'll see in the second member if in doubt run the code and then we're going to save a figure here.

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We could share it out like that.

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Let's see what this does.

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We got an error.

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That's all right.

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No such directory.

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That's right.

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I thought I knew the path of my image directory doesn't really matter.

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Images.

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What have I got wrong.

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Images.

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I don't think I need the dot dot.

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There we go.

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Simple plot.

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So this is a 10 by 10 figure.

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So let's practice this maybe we change this to 5 Okay yeah so that was width so this is width quite

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beautiful.

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Oh yeah well that's not looking very good so let's put that back to 10.

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Wonderful.

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And so now we can see the title is simple plot the Y label is y axis and the X label is x axis.

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Of course if you had some data on here that was more specific you might want to label your x and y axis

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is tailored to your data.

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But in our case this is just a nice and simple plot.

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As we've got the title here and if we go back up here check in our images folder.

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We've got sample plot dot Peng G which if you didn't want to write this line of code you can also right

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click and go save image as but that is enough you've seen a map hotly workflow.

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You've also seen the anatomy of a map plot leave a plot or figure.

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So before the next video try to create your own plot like this.

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Get his fancy as you like create a little bit of data.

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You could try create an umpire and plot him see how you go.

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Otherwise I'll see you soon.