Python Data Visualization Transcripts
Chapter: Matplotlib
Lecture: Customizing multiple plots
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For the final exercise, we're going to pull together all of the concept we've talked
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about and build a really complex customized visualization in matplot lib. So the first thing I want to do to plot is get what the average fuel
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cost is for the years between 2010 and 2020. So let's build simple data frame.
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So what I've done here is created a new data frame called DF 2010 that only has the years 2010 and higher.
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And then just calculate the average fuel cost using the mean function and rounding it to
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zero decimal places. Now I'm going to build a complex visualization. I'm going to copy and paste the code in here and then I'll walk through each
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line what it does and we'll start at the end with the visualization that we have So I now have two plots side by side in one image that shows the
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fuel cost versus the year. I have a trend line. I have an average line that's annotated and then I also show a histogram with
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the average value annotated. So let's go through the code that we had to pull this together. So we already talked about how I calculated the 1970 cost.
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I decided for this example I would use the gg plot style, I set up my figure and my axes to do one row and two columns and
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I set the figure size a little bit bigger so that it was easier to see Then I plotted my scatter plot of year versus fuel cost on axes one and
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then I also plotted my fitted value and change the colored forest green and added a line style of the two dashes.
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I changed the labels for the year and the fuel cost to clean that up. I also set the wide limit in the X limit Using Axl. Set.
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I said a formatter so that the value was indicated with a dollar sign and had a comma. I also added a horizontal line that was orange with the average
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fuel cost and then I annotated it so that you could see that number 1970. The X. Y position tells it where to put it.
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So I told it to put that line at start or the annotation starting at 2017 That is everything we put in place for axes one.
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This first image I plotted, histogram on axis 2, I changed the color to sky blue and the edge color to white.
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That's what you see is set the format er again so that the dollars would show up nicely on the X axis.
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I added the vertical line and annotated it with 1970 as the average price and then I set the position for the Y position at 3500.
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I also added a title says EPA estimated fuel costs. Set the weight to bold in the size to 14.
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I also then save this final figure using "bbox inches" equals tight so that it
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is nicely formatted and this is a great example to show how powerful matplot lib
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is to combine multiple visualizations together and generate a really nice image that you can include
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in presentations or emails or other activities that you need to do to explain your analysis.