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typo fixes in transform.Rmd

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rlzijdeman 2016-06-05 09:19:39 +02:00
parent 2ab8e749c9
commit f9e69b7b94
1 changed files with 2 additions and 2 deletions
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transform.Rmd
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@ -630,7 +630,7 @@ flights %>%
summarise(mean = mean(dep_delay)) summarise(mean = mean(dep_delay))
``` ```
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: 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:
```{r} ```{r}
flights %>% flights %>%
@ -731,7 +731,7 @@ batters %>% arrange(desc(ba))
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>. 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>.
### Other summary functions. ### Other summary functions
Just using means, counts, and sum can get you a long way, but R provides many other useful summary functions: Just using means, counts, and sum can get you a long way, but R provides many other useful summary functions: