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 Launceston     max temp  17.7
## Observation       2 location Watsonia       max temp  14.4
## Observation       3 location Adelaide       max temp  33.7
## Observation       4 location Sale           max temp  20.2
## Observation       5 location Townsville     max temp  26.7
## Observation       6 location Cobar          max temp  20.1

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 Penrith of 23.8-30.6
## Observed temperature range at Brisbane of 14.7-28.9
## Observed temperature range at Perth of 9.2-28.3
## Observed temperature range at Melbourne of 7-17
## Observed temperature range at Ballarat of 11.8-30.7
## Observed temperature range at Darwin of 19.9-35

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