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Hello and welcome to this art tutorial.

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So now it's time for the fun part.

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I can't wait to show you the training
set results and the test set results.

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So let's start to build the graphs.

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So the first thing we're going to do
is to import the ggplot2

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library, which is a very good way
of plotting something in R.

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So I'm going to import it.

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But before importing this library
there might be some of you

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who are starting R for the first time.

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So if we go to our packages here,
you can see that

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the ggplot2 library is here on my RStudio.

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But it might not be the case for you
because

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and that would mean that the ggplot2
library is not installed on your R.

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So just for those of you for which it's
the case, I'm going to install

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ggplot2 library.

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So we have to use this command
install packages here.

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And then in parenthesis we add ggplot2

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g plot two.

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Then we select this press
command and control plus enter to execute.

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And here and as you can see
it's installing the library.

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And that's done.

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So that's the message you should be
obtaining when you install the package.

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Now it should be appearing
in your library.

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So mine is here and we are ready
to start plotting the graph.

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I'm just going to put that in comment.

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So command shift plus C.

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Now it's incoming

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because once it's installed
we don't need to install it again.

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Okay.

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So now let's start to plot our training
set results graph.

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So okay so first thing we need to do
as you can see the ggplot

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two library is not selected here.

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So we will need to select it.

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But we want to automate all this
if we want to use simple linear

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regression on another data set.

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So we will just type here library.

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Then in
parentheses the name of the library.

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Not in quotes actually did ggplot2.

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And as you can see if I select this line

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and execute here,
you see that it's not selected.

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And if I execute it selected here
we just have a suggestion

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to type suppress package started messages
to eliminate package started messages.

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Well that's not very important.

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You can execute that if you don't want
the package started messages.

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But that's okay.

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So I'm just going to enlarge this

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okay.

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And now like for this course the approach
we will be taking to build

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this graph with ggplot2 is going to be
a step by step approach, because we are

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first going to plot all the observation
points in the training set.

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Then we're going to plot
the regression line.

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And then we're going to add a title
and then a label to the x axis

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and a label to the y axis.

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So you know it's going to be step by step.

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First the observation points,

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then the regression line,
then the title, then the labels.

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Okay.

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So let's start with the observation
points.

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So okay.

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So generally to introduce a plot in ggplot
we start by typing

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ggplot parenthesis.

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All right.

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And then that's

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when we start to build step by step
the little components of our graph.

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And since we're adding each component
one by one

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we are going to separate
each of these components by plus.

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So let's go for the first component
plus here I will press enter.

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And here we go for the first component.

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So the first component
are the observation points.

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So very intuitively
we are going to write geom

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underscore point.

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All right.

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So we are going to use this function
of ggplot

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to scatter plot all our observation
points of the training set.

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So the first thing that we need to do
is to precise

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which are going to be the x axis
and the y axis.

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And that's in the esthetic function
which we call x.

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So that's the function that will take as
input the x variables and the y variable.

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So the x variables is our years
experience variable.

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That means the number of years
of experience.

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That's what we want to have in the x axis.

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And the y variable will be our salaries
but the real ones

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not the predicted ones. Yet.

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So therefore we are
going to add in parentheses x

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equals.

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And then we're
going to put all our years of experience.

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But be careful.

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We want to take the years of experience
of the observations in the training set.

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So here we'll just have to specify
training set dollar

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and then years experience.

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So that means that we are taking the years
experience values

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of the observations
in the training set okay.

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And now same for Y.

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And here we do
the same only with the salaries

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which is here okay.

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And that plots all your observation
points.

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The real ones in the plot okay.

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So we could stop here,
but we would like to add a call

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because we will want to make
the distinction between the observation

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points and the regression line
to, you know, make a nice plot.

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So come here and then I'm going to press

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enter to add a new argument of geom point.

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Because this can be a little confusing
here we have

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we have a coming here and coming here.

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This coming here is just to separate the x
and the y in the esthetic function.

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And this coming here is to separate

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the first argument and the second argument
of the June point function.

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So the second argument is color.

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And let's pick red.

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I usually like to have my observation
points in red.

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But you know that's just my taste.

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If you have some other tastes,
you're welcome to, choose

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your favorite color for the observation
points.

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Okay, so that's it for the geom point.

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With this zoom point part, here
we are plotting all the observation

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points of our training set.