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 Nuriootpa max temp 19.4
## Observation 2 location Portland max temp 13.7
## Observation 3 location Ballarat max temp 14.8
## Observation 4 location Sale max temp 28.5
## Observation 5 location Katherine max temp 39.5
## Observation 6 location Sydney max temp 17.2
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 CoffsHarbour of 8.3-12.9
## Observed temperature range at Tuggeranong of 0.6-13.1
## Observed temperature range at Hobart of 19-34.7
## Observed temperature range at Williamtown of 17.7-28.9
## Observed temperature range at Hobart of 10-23.1
## Observed temperature range at Mildura of 7.4-22.7
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