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All righty.

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So we've seen create quite a complex plot.

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But in terms of customization we've kind of glazed over these set parameters and title and X label and

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Y label or not.

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So what we're gonna do now is look at customization of plots a little bit more in-depth.

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And by the end of this video perhaps the next video we're going to replicate or transform this plot

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into something which looks exactly like the one we've got here.

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So the data's still the same but you can kind of see that there's a different style in terms of color

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line and just the tax is a little bit different the font.

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The axes are a little bit different.

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So let's get into it a is what we're going to do first is have a look at some different styles of matte

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plot lib.

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So the beautiful thing about matte plot lib is that again one of its other customizable parameters is

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this style of plot that you're using.

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So if the default one which is what we're kind of using now doesn't quite look how you want it to look.

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You can try other different styles so let's go down here and make a little section customizing matte

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plot lib plots and getting stylish.

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Yeah that's what we're gonna do.

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We in stylish see the different styles available.

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Now what this is going to do is if we call BLT dot style dot available it's going to tell us what kind

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of styles map plot Lee has available to us right now by default by just importing that plot layer right

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at the top.

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We're using the default style but as you can see there's about 20 other styles that you can use.

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So let's try out a few of these but first we remind ourselves of what the default style looks like.

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That way we can compare and see which one we like best because I've tried a few of these and I kind

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of know which ones I like.

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But again it'll come down to personal preference of what kind of style you want to use so this is the

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default style.

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Plotting the car sales data frame that we've seen a few times now.

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So car sales don't head the same car sales.

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Well car sales data frame report the plus column got a beautiful line graph.

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Now that's that's pretty good on its own.

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So let's have a look.

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Maybe we want to use peyote dot style to use and I'm gonna choose the seaborne white grid.

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Let's see what that looks like we'll type that in seaborne White red.

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Wonderful.

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So that's going to update Matt Gottlieb's style internally.

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So if we call the same plot that we did before.

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Price dot plot put a semicolon at the end.

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So it looks a bit different.

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Now we've got some grid lines here.

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We've got a little bit of a gap here maybe the Axis his limit is a bit higher for the y axis but generally

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quite the same as the default map plot lib style now.

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And you might think that the map bot lib default style is perfect for unis and that's okay.

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We've gone through these different styles right because I want you to understand just how customizable

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these plots are.

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Let's try another plot dot style dot use.

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And this time we might just use the default save on.

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So if we go up here Seabourn on its own now Seabourn is another plodding library that's built off map

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plot lib.

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And now we're going to a car sales price.

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Wonderful.

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So now kind of a little bit different.

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So this is what.

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Great.

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So we've got a white background that kind of makes sense but the default Seabourn style kind of has

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this gray background.

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But again we're still plotting the exact same data just mixing up the style mixing up the colors.

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Why don't we try another kind of plot.

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Where did car sales help launch now that the style is set to Seabourn.

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How about we check the odometer K M and then let's go.

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Domino versus price.

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We've seen this plot somewhere before.

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Kind.

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Eagles will make it a scatter plot.

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There we go.

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So a little bit different to the original scatter plot that we've seen before.

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This one maybe look a bit better to you.

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I personally prefer the Seabourn style so I might run this line of code when I start a new notebook.

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So run it right at the top under my map plot maybe imports just to make sure all my plots are in the

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Seabourn style so we'll save that there.

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That's not a good habit to get into is just hitting command or control s every so often with your notebooks

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and we might use one more plot just for good luck plot style this time we're going to use G.G. plot

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which is up here G.G. plot is a different kind of style.

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And so do the price graph again price.

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The plot.

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There you go.

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So now we got a bit of a different maybe a creamy Gray I don't know how you would describe that color

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but the line is definitely changed to red as you can see seaborne kind of comes with some axis titles

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by default whereas these don't have them.

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OK.

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Now these are some sweet looking plot.

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And now we're seeing that a change up the style.

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How about the titles the legend and the Axis scenes like this one doesn't have any.

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It just has numbers on both axes if a plot is worth a thousand words adding a few more can't hurt right.

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So let's do that.

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We'll go or create some dummy data create some data x equals.

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We've seen this before.

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Number pi Rand in we'll go 10 for there we go.

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We've got an array there.

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Wonderful.

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Now we'll put that into a data frame.

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We've created a data frame like this before but we're just going to practice practice practice reworking

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some of the things we've already done.

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That way they start to sink into memory a bit more.

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See these wonderful.

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Now this should give us a data frame.

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Four columns 10 rows of some random numbers.

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Beautiful.

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And now we're going to create a simple plot.

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Now this we're going to use a pipeline API because we want to just create a plot quickly.

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If you wanted to create something more in-depth like we've done here where is there you would probably

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use the object orientated API.

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But because we're doing some quick and dirty plots at the moment we'll just use the plot straight from

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the pan this data frame with the pie plot API so kind equals bar and then we going to look at the type

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of x beautiful.

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So this is a bar graph that we've built just off this data frame here we've got some negative and positive

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values different colors for the different columns.

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That all makes sense.

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And now we're going to customize our plot with this set method.

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So we've got X.

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We'll rewrite it X so we can see it all in one cell.

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After plot kind equals bar.

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Wonderful.

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And now we want to add some labels and a title.

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So we want X dot set and we've got title.

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So as you can probably guess this is gonna set the title random bar graph from data frame

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wonderful I've spelt graph terribly.

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That's right.

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There we go.

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And then within this set set has a few parameters here.

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So we go shift tab there we go shift keyword args.

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So this is probably another one you probably want to look into the documentation to start to figure

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out all the different kinds of customizations you can add to it.

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But we're just gonna go through the main ones which are Title X label and Y label deprived the bare

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minimum you'd want on any plot or figure that you create right.

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You want to know what's on the x axis and you want to know what's on the y axis rather than just having

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numbers in row number random number.

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Simple titles and then we'll make the legend visible.

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Now this one is kind of confusing because the legend already is visible but if it wasn't visible some

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plots do have a legend already built in.

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So you can use this X dot legend dot set it visible and then sets that visible to true which won't really

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change ours because it's already visible.

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But let's see what happens.

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What do we got here.

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Axis plot has no property title.

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Oh another typo.

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There we go.

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Wonderful.

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So now we've got the same exact same plot as up here but now we've just used a set method to add in

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an axis label on the Y and the X and a title.

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So that's starting to look a lot more communicative right there right.

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Now what if the style we're using doesn't quite suit the plot.

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We're trying to make.

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So that's what I'll probably look into the next video will change around the style within a set style.

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So that sounds a little confusing.

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Don't worry we'll go through it in the next video but in the meantime try out creating some of your

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own plots using plot style and use and pick one.

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Anyone from this list and you start to get a feel for what the different styles look like.

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My personal favorite is probably C bone or bond white greed seaborne generally just has some great styles

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down here.

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All right let's take a little break write some custom code and I'll see you shortly.