Merge pull request #107 from rlzijdeman/master
typo fixes in transform.Rmd
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		@@ -630,7 +630,7 @@ flights %>%
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  summarise(mean = mean(dep_delay))
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```
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We get a lot of missing values! That's because aggregation functions obey the usual rule of missing values: if there's any missing value in the input, the output will be a missing value. `x %>% f(y)` turns into `f(x, y)`ou'll learn more about aggregation functions in Section 5.7.4. Fortunately, all aggregation functions have an `na.rm` argument which removes the missing values prior to computation:
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We get a lot of missing values! That's because aggregation functions obey the usual rule of missing values: if there's any missing value in the input, the output will be a missing value. `x %>% f(y)` turns into `f(x, y)` you'll learn more about aggregation functions in Section 5.7.4. Fortunately, all aggregation functions have an `na.rm` argument which removes the missing values prior to computation:
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```{r}
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flights %>% 
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@@ -731,7 +731,7 @@ batters %>% arrange(desc(ba))
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You can find a good explanation of this problem at <http://varianceexplained.org/r/empirical_bayes_baseball/> and <http://www.evanmiller.org/how-not-to-sort-by-average-rating.html>.
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### Other summary functions.
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### Other summary functions
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Just using means, counts, and sum can get you a long way, but R provides many other useful summary functions:
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