Correct grammatical typos in transform.Rmd (#153)
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@ -226,15 +226,15 @@ filter(df, is.na(x) | x > 1)
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### Exercises
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1. Find all the flights that:
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1. Find all flights that
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1. That were delayed by more two hours.
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1. That flew to Houston (`IAH` or `HOU`).
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1. There were operated by United, American, or Delta.
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1. Departed in summer (July, August, and September).
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1. That arrived more than two hours late, but didn't leave late.
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1. Were delayed by at least an hour, but made up over 30 minutes in flight.
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1. Departed between midnight and 6am (inclusive).
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1. Were delayed by more two hours
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1. Flew to Houston (`IAH` or `HOU`)
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1. Were operated by United, American, or Delta
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1. Departed in summer (July, August, and September)
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1. Arrived more than two hours late, but didn't leave late
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1. Were delayed by at least an hour, but made up over 30 minutes in flight
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1. Departed between midnight and 6am (inclusive)
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1. Another useful dplyr filtering helper is `between()`. What does it do?
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Can you use it to simplify the code needed to answer the previous
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@ -861,7 +861,7 @@ daily %>%
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Which is more important: arrival delay or departure delay?
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1. Look at the number of cancelled flights per day. Is there are pattern?
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1. Look at the number of cancelled flights per day. Is there a pattern?
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Is the proportion of cancelled flights related to the average delay?
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1. Which carrier has the worst delays? Challenge: can you disentangle the
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