Move exercise to better location #514
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@ -831,10 +831,6 @@ daily %>%
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effects of bad airports vs. bad carriers? Why/why not? (Hint: think about
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`flights %>% group_by(carrier, dest) %>% summarise(n())`)
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1. For each plane, count the number of flights before the first delay
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of greater than 1 hour. (Hint: read about cummulative window functions and
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see how their negations work, `vignette("window-functions")`)
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1. What does the `sort` argument to `count()` do. When might you use it?
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## Grouped mutates (and filters)
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@ -896,3 +892,6 @@ Functions that work most naturally in grouped mutates and filters are known as
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1. Find all destinations that are flown by at least two carriers. Use that
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information to rank the carriers.
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1. For each plane, count the number of flights before the first delay
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of greater than 1 hour.
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