6.6 Glue Pipelines

20180729 We can use glue::glue_data() within pipes and operate over the rows of the data that is piped into the operator.

weatherAUS %>%
  sample_n(6) %>%
  glue_data("Observation",
            " {rownames(.) %>% as.integer() %>% comma() %>% sprintf('%7s', .)}",
            " location {Location %>% sprintf('%-14s', .)}",
            " max temp {MaxTemp %>% sprintf('%5.1f', .)}")

## Observation       1 location Walpole        max temp  25.9
## Observation       2 location Sydney         max temp  29.4
## Observation       3 location Hobart         max temp  20.7
## Observation       4 location Witchcliffe    max temp  20.0
## Observation       5 location GoldCoast      max temp  21.5
## Observation       6 location BadgerysCreek  max temp  24.4

It can also be useful with the tidy verse work flow.

weatherAUS %>%
  sample_n(6) %>%
  mutate(TempRange = glue("{MinTemp}-{MaxTemp}")) %>%
  glue_data("Observed temperature range at {Location} of {TempRange}")

## Observed temperature range at Cobar of 5.8-21.5
## Observed temperature range at Launceston of 8.2-17.9
## Observed temperature range at Perth of 16.5-29.9
## Observed temperature range at Sydney of 9.5-22.4
## Observed temperature range at Moree of 9.1-24.1
## Observed temperature range at PearceRAAF of 19.7-33.6

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