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Hello, dear friend.



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So in this lesson, we are going to examine some of the basic terms in matplotlib library.



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So let's start.



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Now, of course, you remember.



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And our last lesson, we talked about the pipeline and how to use matplotlib.



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So now we need to understand the pipeline, my lab and matplotlib concepts as well.



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OK, so what is PI plot and what does it do?



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So hopefully remember that when we talked about MATLAB in our last lesson, we said we can do the same



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things in Python with the help of matplotlib.



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So.



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We can use all of these things with the help of pipeline.



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So basically Pipeline is a collection of command style functions that make matplotlib work like MATLAB.



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You with me?



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So each pipelined function makes some change to a particular figure.



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So here this table shows that some of the function found the types of plots and pipeline.



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And we will use some of them in our following lessons, so don't worry, you don't have to memorize



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them all now.



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It as well, you might also remember that we used some of them in our previous lesson.



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Any of them look familiar.



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So if you want to let's see an example again.



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So first, we all need to import our library and module import numbI, as in P.



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Import matplotlib doormat plot as GLT.



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And, of course, we're going to need to enter a magic statement for displaying our plot outputs inside



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the Jupiter notebook itself precent matplotlib Inli.



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Now we can create an incendiary object between one and nine using the arrange function from the Numpty



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Library.



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And a X equals and P dot arrange.



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One nine.



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So our variable serves as values on the X axis of the graph.



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Now we're going to need another variable for the Y axis, so let's define it and a Y.



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Equals and picked a range.



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327 three.



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So our two dimensions, X and Y axes are already ready.



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So let's try to plot it out.



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With the help of the plot function, we can do it.



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All right, so Pulte dot plot and a X.



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And a Y.



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And there's a result.



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So now, of course, we can try different types of plots in our plot table.



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BLT to bar.



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And X and a Y.



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And there's a result.



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So that's how you get a result for a bar plan.



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Now, how about Paltalk, Barack H.



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Nax.



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Anyway.



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And there's that resume.



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So this time we'll get the result with a BA plot horizontally.



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So let me show you another one.



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Polka dot polar.



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Aex.



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And why?



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There's that result, so that's how you get a polar plot.



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But that step.



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Nax.



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And a Y.



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And here's the result.



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So there's how you get a step, Plott.



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All right, so let's move on.



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So the other one is piai lab.



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So what is Piw Lab and what does it do?



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Well, my lab is a module that has a procedural interface to the matplotlib, object oriented, plodding



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library, and it gets installed alongside matplotlib.



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So basically, my lab is a module within the Matplotlib library that was built to mimic matte labs global



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style.



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So it exists only to bring a number of functions and classes from both numbI and Matplotlib into the



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namespace making for an easy transition for a former MATLAB users who were not used to needing to import



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statements.



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That's pretty cool, huh?



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And it all works seamlessly.



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So let's have a look with some of the examples about the pilot module.



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So, as you know, we import our module first.



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SciLab import.



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Now define a new variable named X, and it'll refer to the X axis X equals.



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And now we can use our no BS line space method and its value, so we'll let it be well in space.



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Minus three, three and 30.



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So let's define another variable in Whitehall, refer to the Y, axis Y equals.



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So its value is going to be X two.



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And now we can use our plot.



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So plot.



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X y.



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And the result is, as you see.



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So the beginning pilot was so popular, especially with old MATLAB users, you can see probably too



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many examples in usage areas out there, but now Python does not recommend it anymore.



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So here you can see the relationship between biolab, matplotlib and implied matplotlib is a library



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in Python.



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My plot is a module in matplotlib and my lab is a module used just like an interface.



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So that's it.



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So we covered in this lesson the difference between pilot by plot and matplotlib, because at some point



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these terms are going to get confusing.



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But now you know how to differentiate.



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So we will meet in the next lesson.



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Until then, have a nice day.