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So visualisations in prison, so in this course, and when we solve the optimization problem, I usually

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prefer to show you how to visualize the decision variables and also the objective function for this

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purpose.

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There are some multiple packages in Python, like Seabourne, like GGGI Plot, like Beaucaire, like

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Pygle and also plotly and your plot leap and gleam and missing no leather.

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And also the main one that I'm going to use it throughout this course is matplotlib so we can use these

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tools to visualize or decision variables or and also the objective function, how they are changing

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with, uh, with the decision maker.

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OK, and also so we don't have any insist of using any specific, um, package in Python, but for simplicity

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I have chosen the Mathlouthi.

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But you feel free to change that part of the code and do the visualization by your own creativity.

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So in order to learn more about the matplotlib, you can Google it.

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And there is a website called matplotlib dot org and it has a gallery.

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It has multiples of.

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Solved examples.

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So you can easily use them and you don't need to memorize everything, of course.

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But if you need anything, you can go to a gallery and find out which of these examples are much closer

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to what you exactly need.

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So this is an example, for example, and you need to import matplotlib.

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That's Pyplot aspect and import numpy as NP.

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And for example, in this plot you can see there are some random shapes are scattered in the plane.

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OK, so this is the application of a scatter plot and you finally show that plot to your audience.

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OK, so that's the way you visualize the things in Python.

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This is very simple, but you need to practice as well.

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Thank you very much.