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 Portland       max temp  21.2
## Observation       2 location Brisbane       max temp  27.5
## Observation       3 location WaggaWagga     max temp  16.8
## Observation       4 location CoffsHarbour   max temp  28.4
## Observation       5 location Ballarat       max temp  16.0
## Observation       6 location Newcastle      max temp  38.2

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 SydneyAirport of 14.8-18.4
## Observed temperature range at NorfolkIsland of 16.1-24.7
## Observed temperature range at Ballarat of 3.9-13.8
## Observed temperature range at Adelaide of 9.7-19.3
## Observed temperature range at Hobart of 3.2-13.2
## Observed temperature range at Ballarat of 5.6-27.1

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