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minor typos in chapter 5 (#666)

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Stéphane Guillou 2018-06-20 19:10:59 +10:00 committed by Hadley Wickham
parent c7a2442f64
commit 6edfe2c9ed
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6
transform.Rmd
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@ -101,7 +101,7 @@ There's another common problem you might encounter when using `==`: floating poi
```{r}
sqrt(2) ^ 2 == 2
1/49 * 49 == 1
1 / 49 * 49 == 1
```
Computers use finite precision arithmetic (they obviously can't store an infinite number of digits!) so remember that every number you see is an approximation. Instead of relying on `==`, use `near()`:
@ -389,7 +389,7 @@ There are many functions for creating new variables that you can use with `mutat
* Offsets: `lead()` and `lag()` allow you to refer to leading or lagging
values. This allows you to compute running differences (e.g. `x - lag(x)`)
or find when values change (`x != lag(x))`. They are most useful in
or find when values change (`x != lag(x)`). They are most useful in
conjunction with `group_by()`, which you'll learn about shortly.
```{r}
@ -882,7 +882,7 @@ Functions that work most naturally in grouped mutates and filters are known as
1. Delays are typically temporally correlated: even once the problem that
caused the initial delay has been resolved, later flights are delayed
to allow earlier flights to leave. Using `lag()` explore how the delay
to allow earlier flights to leave. Using `lag()`, explore how the delay
of a flight is related to the delay of the immediately preceding flight.
1. Look at each destination. Can you find flights that are suspiciously