Matplotlib Tutorial 2 - Legends titles and labels

sentdex · Beginner ·🛠️ AI Tools & Apps ·10y ago

Key Takeaways

This video tutorial covers the use of legends, titles, and labels in Matplotlib, a popular data visualization library in Python, to enhance the readability and understanding of graphs.

Full Transcript

what's going on everybody Welcome to part two of our data visualization with python and M plot lib tutorial Series in this tutorial we're going to be talking about uh Legends titles and labels within map plot lib so graphs sometimes can be relatively self-explanatory especially if they're input into some sort of context uh but generally it's a good idea to have a title and labels on your x and y axis and then also a legend can also be really helpful especially if you're plotting multiple you know series of data so uh with that let's go ahead and hop right in so first of all when you're graphing in matplot lib chances are you're not going to actually have any like hardcoded variables otherwise you probably wouldn't be using a programming language you would just I don't know plug it into Excel or something like that so at the end of the day usually what happens is you have x and x is a list and Y and Y will be a python list too and then you'll have some function that populates X and Y but for now I mean we can just uh we can just take our old values here cut and paste and we'll just say X and Y and we'll just pretend this was a function it's not but we'll pretend that for now so uh first of all what we want to do is we can add titles and labels and the way that we're going to do that is we just do it before we call the dot show and so after the plot we can come down here and we can say PLT do and then we can say x label and this will be for that you know bottom axis the x axis and we can just call this the uh plot number and then the PLT doy label and we call this the uh important VAR that's what it is and uh and that should be it uh the next thing we can do is we can also add a title so we can say pt. tile and in here we can say um we can call this an interesting graph and what you can do in a title first let's I guess we'll bring this one up and then I'll show you guys one more thing but uh so let's go ahead and save and run that real quick and here we see we've got this interesting graph title we've got the X ax well the x- axis down here and the y- axis over here and also you can take note that the y axis is automatically like flipped a little bit there so like goes up and down vertically rather than horizontally so this is just automatically done for you and it's mostly just to save space but anyways you can see we've got this title it's a little larger than these numbers down here and all that and later on we'll talk all about customization like everything in M plot lib is customizable so we can also change the font sizes and all everything basically here so anyway uh so we have that now like what if like a lot of people have like subtitles there is a way to do subtitles in M plot live but a lot of times this is good enough when where you'll have interesting graph and then you use a new line character so that's a back slash n so that backs slash is right above your enter key so back sln um check it check it out make sure you don't add a space there if you had a space there it'll add that space on the new line like it'll start with a space and that's not what you want so we could do something like that we'll save and run that and uh sure enough there you go interesting graph check it out cool and all that so um we'll go ahead and close out of this and now the only other thing I want to cover is Legends so um the reason why you would have a legend is maybe if you had two two lines so let's go ahead and add an X2 and a Y2 and let's just give them um we'll do one two and three again but then the Y 2 will be let's just make all these numbers over 10 so let's do 10 14 12 so now what we can do is we can go PLT plot and then X2 Y2 okay and uh to do a legend basically you can all you have to do is just invoke the legend so you can just do pt. Legend and now we have an Legend element here but we have no nothing to put in the legend so there's no way for matplot lib to just know what are l are so we use a a keyword argument in this pip plot. plot and that is going to be label and so we say label equals and then the string of what we want so we would call this the you know first line and then we would call this second one here we would say label equals and then we'll just say this is the second line so that's that now all we need to do is save and run that and there you go now you've got your two lines here's a line up here and here's a line line down here now this is just a really simple and quick you know intro kind of few videos here so as you can see we're we got this line that's running through our Legend that's obviously not what you want happening so later on we'll be talking about uh how to customize the Legend So that does not happen but for now this is good enough just to show the legends exist so um that's it for now we've got the labels now and legends and basically lot of the required elements to make your graph a little more easy to understand if you have any questions or comments about this please feel free to leave them below otherwise as always thanks for watching thanks for all the support and subscriptions and until next time

Original Description

In this tutorial, we're going to cover legends, titles, and labels within Matplotlib. A lot of times, graphs can be self-explanatory, but having a title to the graph, labels on the axis, and a legend that explains what each line is can be necessary. sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
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This tutorial teaches how to add titles, labels, and legends to graphs in Matplotlib to make them more understandable. It covers the basics of graph customization and provides examples of how to use these features.

Key Takeaways
  1. Import the Matplotlib library
  2. Create a graph with plot()
  3. Add a title with plt.title()
  4. Add labels with plt.xlabel() and plt.ylabel()
  5. Add a legend with plt.legend() and label arguments
💡 Customizing graphs with titles, labels, and legends is essential for effective data visualization and communication.

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