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Copy file name to clipboardExpand all lines: 3-Data-Visualization/R/12-visualization-relationships/README.md
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Another way to visualize this progression is to use size, rather than color. For colorblind users, this might be a better option. Edit your visualization to show an increase of price by an increase in dot circumference:
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```r
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library(ggplot2)
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ggplot(honey, aes(x=priceperlb, y=state)) +
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geom_point(aes(size=year),colour="blue") +
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scale_size_continuous(range= c(0.25, 3))
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Question: Is there a clear rise in price of honey per pound year over year? You can most easily discover that by creating a single line chart:
Answer: Yes, with some exceptions around the year 2003:
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✅ Because Seaborn is aggregating data around one line, it displays "the multiple measurements at each x value by plotting the mean and the 95% confidence interval around the mean". [Source](https://seaborn.pydata.org/tutorial/relational.html). This time-consuming behavior can be disabled by adding `ci=None`.
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Question: Well, in 2003 can we also see a spike in the honey supply? What if you look at total production year over year?
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