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     1.0 location Adelaide       max temp  15.3
## Observation     2.0 location CoffsHarbour   max temp  25.2
## Observation     3.0 location Penrith        max temp  28.6
## Observation     4.0 location Canberra       max temp  28.6
## Observation     5.0 location Brisbane       max temp  29.7
## Observation     6.0 location PerthAirport   max temp  20.3

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 Moree of 22.1-32.9
## Observed temperature range at Melbourne of 11.3-30.3
## Observed temperature range at Witchcliffe of 13.8-28
## Observed temperature range at Katherine of NA-NA
## Observed temperature range at Mildura of 18.6-35.7
## Observed temperature range at Walpole of 7.9-13.8


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