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Fixing typos in EDA.Rmd (#315)

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Brett Klamer 2016-08-26 11:15:59 -04:00 committed by Hadley Wickham
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EDA.Rmd
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@ -220,7 +220,7 @@ It's good practice to repeat your analysis with and without the outliers. If the
or surprising? (Hint: Carefully think about the `binwidth` and make sure
you try a wide range of values.)
1. How many diamonds are 0.99 carat? How many have are 1 carat? What
1. How many diamonds are 0.99 carat? How many are 1 carat? What
do you think is the cause of the difference?
1. Compare and contrast `coord_cartesian()` vs `xlim()` or `ylim()` when
@ -350,7 +350,7 @@ ggplot(data = diamonds, mapping = aes(x = cut, y = price)) +
We see much less information about the distribution, but the boxplots are much more compact so we can more easily compare them (and fit more on one plot). It supports the counterintuitive finding that better quality diamonds are cheaper on average! In the exercises, you'll be challenged to figure out why.
`cut` is an ordered factor: fair is worse than good, which is worse than very good and so on. Many categorical variables don't have such an intrinsic order, so you might want to reorder them to make an more informative display. One way to do that is with the `reorder()` function.
`cut` is an ordered factor: fair is worse than good, which is worse than very good and so on. Many categorical variables don't have such an intrinsic order, so you might want to reorder them to make a more informative display. One way to do that is with the `reorder()` function.
For example, take the `class` variable in the `mpg` dataset. You might be interested to know how highway mileage varies across classes:
@ -593,7 +593,7 @@ diamonds %>%
## Learning more
If you want learn more about the mechanics ggplot2, I'd highly recommend grabbing a copy of the ggplot2 book: <https://amzn.com/331924275X>. It's been recently updated, so it includes dplyr and tidyr code, and has much more space to explore all the facets of visualisation. Unfortunately the book isn't generally available for free, but if you have a connection to a university you can probably get an electronic version for free through SpringerLink.
If you want learn more about the mechanics ggplot2, I'd highly recommend grabbing a copy of the ggplot2 book: <https://amzn.com/331924275X>. It's been recently updated, so it includes dplyr and tidyr code, and has much more space to explore all the facets of visualisation. Unfortunately the book isn't generally available for free, but if you have a connection to a university you can probably get an electronic version for free through SpringerLink.
Another useful resource is the [_R Graphics Cookbook_](https://amzn.com/1449316956) by Winston Chang. Much of the contents are available online at <http://www.cookbook-r.com/Graphs/>.