@@ -598,7 +598,7 @@ delays <- flights %>%
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    dist = mean(distance, na.rm = TRUE),
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					    dist = mean(distance, na.rm = TRUE),
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    delay = mean(arr_delay, na.rm = TRUE)
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					    delay = mean(arr_delay, na.rm = TRUE)
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  ) %>% 
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					  ) %>% 
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  filter(delay, count > 20, dest != "HNL")
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					  filter(count > 20, dest != "HNL")
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```
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					```
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This focuses on the transformations, not what's being transformed, which makes the code easier to read. You can read it as a series of imperative statements: group, then summarise, then filter. As suggested by this reading, a good way to pronounce `%>%` when reading code is "then".
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					This focuses on the transformations, not what's being transformed, which makes the code easier to read. You can read it as a series of imperative statements: group, then summarise, then filter. As suggested by this reading, a good way to pronounce `%>%` when reading code is "then".
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