Python Data Visualization Transcripts
Chapter: Seaborn
Lecture: Catplot API summary
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Now I'll show you how to use the cat plot to do some similar analysis. Well look at the same data and show a box plot that compares the average fuel
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economy for the two different date ranges And I've also passed the parameter, show fliers equals false to clean up the visualization a little bit.
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The other thing we can do with the cat plot. So it's very easy to also show other types of plots.
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So I will do this with a boxing plot which is have an interesting little plot to show how the boxes are stacked on top of each other.
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And then if we want to start fastening the data to look at it, we can do that as well.
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So let's take a look at the date range and we'll add a column and now we have box plots for the various date ranges with a column for gas,
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diesel, other and electric. So it makes it very easy to see that there's
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a much different range for the electric vehicles than the fossil fuel vehicles, which makes a lot of sense. Sometimes when we have a lot of columns,
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we may want to just wrap it. So let's do this so that we get more of a 2 x 2 matrix. It's a handy way depending on the data.
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You have to summarize it. What I also like about the catplot Is that we can use the point plot to see trends over time.
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So this will show the average highway 08-fuel economy per year and you can see how it increases quite a bit over time.
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Let's get a little more sophisticated view of this. I can do a point plot as well for this one just like I did here
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but I can say I don't want to join the lines together so that I can see the trends for the highway fuel economy over time as well as the fuel
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type summary. So this is another way to look at the data and depending on your unique data sets, this could be a helpful way,
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but it does highlight just how much flexibility there is with the cat plot.
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Another plot that I like to use quite a bit from a category plot perspective is
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the bar plot and I'll use some of the same variables that we've looked at before But one of the things I do here is set share X equals to false
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And what that allows us to do is to show different values on the X axis. So I can show these two years kind of compare them against each other
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And this is a nice way to see changes over time. I'm also comparing that electric fuel economy versus other fuel economies.
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You can see there's a period of time where there aren't that many electric cars and then once we get into 2011 above,
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there's a lot more examples of electric cars and the highway fuel economy for them.
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Why don't we combine this all by doing the cylinders and the combined fuel economy. I'll also include a column for the drive.
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We'll put a role for the date range, will show the transmission and do a bar chart as well.
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So this gives us a lot of data in these charts using a very simple, consistent API.
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And by varying these values. It's really a quick and efficient way to look at your data, analyze it and see what insights you have and what you need to
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do to solve your own unique problems.