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Let's start our journey by installing
matplotlib in a Jupyter Notebook.

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Fortunately, that is relatively
straightforward by using pip.

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Let's kick off jupyter notebooks.

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If you aren't familiar
with Jupyter Notebooks,

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check out the teacher's notes for
more information.

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We'll start a new notebook here in
the matplotlib directory I created for

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this course.

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And we'll install our matplotlib package.

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The syntax is slightly different here.

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We import sys,

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Pip install matplotlib.

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And then we can run our cell.

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Just make sure in notebooks that you are
running the pip version associated with

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the current Python kernel and
can be used in the current notebook.

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I already had matplotlib
installed in this environment.

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Now that we have the matplot
library installed,

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we want to import the pyplot module, which
allows us to quickly generate our plots.

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It’s convention to import this as plt.

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Now, we can pass in a list of matplotlib.

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It'll assume that it's
a sequence of y values and

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will auto generate the x values for us.

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We wanted to show some output, right?

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For that, we can use the show method.

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So, plt.plot([1, 2, 3, 4])

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And then, plt.show and run our cell.

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Matplotlib generates our plot and
shows it below our notebook work space.

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It provides a simple line graph
with a default blue solid line.

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But wait a moment,
why does our x-range end at 3?

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Recall that Python ranges start at 0.

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So our x data here is 0, 1, 2, 3.

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We can pass in an equal length argument
and have an x and y pairing as well.

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Let's also add a label to our
y-axis here to get used to

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adding labels to our charts.

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So we'll add in our x-values 1, 4, 9,

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16, plt.ylabel.

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These are very important figures.

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And run our cell, again.

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Now we see a line with our x and
y pairings.

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There are additional
parameters we can pass or

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plot method in addition
to our xy pair values.

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Some of which allow for the customization
of the color and style of the plot.

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Let's turn the line green.

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And the linestyle,
let's do dashdot and run our cell.

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The color argument accepts HTML
color names and code values,

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a tuple of RGB values, grey scale values,
and shortcode values.

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I've included a link in
the teacher's notes for

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complete list of color options as
well as linestyle possibilities.

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What if we want to display multiple
pieces of data on the same plot?

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We can just add another plot
method to our PLT object and

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it will display both data series.

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Let's do 2, 3, 4, 5,
very creative here, and 2, 3, 4, 5.

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Let's make this one hex value 2B5B84.

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And we'll do a linestyle of dashed.

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And run our cell.

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As you might imagine, having multiple data
series on same plot can get confusing.

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Let's see if we can add some
clarity in our next video.