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@ -532,7 +532,7 @@ flights |> unique_where(tailnum == "N14228", month)
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Here we embrace `condition` because it's passed to `filter()` and `var` because its passed to `distinct()`, `arrange()`, and `pull()`.
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We've made all these examples take a data frame as the first argument, but if you're working repeatedly with the same data, it can make sense to hardcode it.
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For example, the following function always works with the flights dataset and always selects `time_hour`, `carrier`, and `flight` since they are form the compound primary key that allows you to identify a row.
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For example, the following function always works with the flights dataset and always selects `time_hour`, `carrier`, and `flight` since they form the compound primary key that allows you to identify a row.
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```{r}
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flights_sub <- function(rows, cols) {
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