Python Data Visualization Transcripts
Chapter: Matplotlib
Lecture: Pyplot example
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Now that we have the data loaded into our data frame. Let's do a really simple histogram plot before you plot something in a jupyter
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notebook. Sometimes you may need to use a magic command to tell it that you're plotting with matplot-lib. Now in more recent versions of notebooks,
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you may not have to do this, but I want to point it out because you're going to see this a lot in
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online documentation. So now we've told the notebook that we're going to plot a mat plot lib plot. Let's do a very simple histogram and I like
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using histograms because it's just one variable that we're looking at. In this case, we're going to plot a histocomb of the combined fuel economy
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for all of the values. Now, one of the things you'll notice is that the Histogram is fairly straightforward,
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but you've got all this other information that is getting returned and a lot of times you're not gonna want to see that all the time.
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So there's a little trick you can do if you add that semicolon at the end it will suppress that information.
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So sometimes I will be doing that in the course. And what I'm showing you as an example of the state based interface using pyplot
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that I talked about that we don't want to use. So I'm going to go through that example just a little bit more detail so you
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can see how it works and I'll compare it and contrast with the object oriented interface
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So let me show how to customize the plot using the pyplot interface.
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So I've expand the example so that the plot has more information about what's going on So I continue to do the histogram.
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Then I labeled the X and Y axis with the number of cars and the combined fuel economy. I added a title and then I used plot.show to make
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sure that the final visualization is shown. Now we will go through the object oriented api and show how that works.