See vignette("translation-function") and vignette("translation-verb") for
details of overall translation technology. Key differences for this backend
are:
Many stringr functions
lubridate date-time extraction functions
More standard statistical summaries
Use simulate_postgres() with lazy_frame() to see simulated SQL without
converting to live access database.
Examples
library(dplyr, warn.conflicts = FALSE)
lf <- lazy_frame(a = TRUE, b = 1, c = 2, d = "z", con = simulate_postgres())
lf %>% summarise(x = sd(b, na.rm = TRUE))
#> <SQL>
#> SELECT STDDEV_SAMP(`b`) AS `x`
#> FROM `df`
lf %>% summarise(y = cor(b, c), z = cov(b, c))
#> <SQL>
#> SELECT CORR(`b`, `c`) AS `y`, COVAR_SAMP(`b`, `c`) AS `z`
#> FROM `df`