dbplyr: win_over – R documentation

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win_over

Generate SQL expression for window functions

Description

win_over() makes it easy to generate the window function specification. win_absent(), win_rank(), win_aggregate(), and win_cumulative() provide helpers for constructing common types of window functions. win_current_group() and win_current_order() allow you to access the grouping and order context set up by group_by() and arrange().

Usage

win_over(
  expr,
  partition = NULL,
  order = NULL,
  frame = NULL,
  con = sql_current_con()
)

win_rank(f)

win_aggregate(f)

win_aggregate_2(f)

win_cumulative(f)

win_absent(f)

win_current_group()

win_current_order()

win_current_frame()

Arguments

`expr`	The window expression
`order`	Variables to order by
`frame`	A numeric vector of length two defining the frame.
`f`	The name of an sql function as a string
`parition`	Variables to partition over

Examples

con <- simulate_dbi()

win_over(sql("avg(x)"), con = con)
win_over(sql("avg(x)"), "y", con = con)
win_over(sql("avg(x)"), order = "y", con = con)
win_over(sql("avg(x)"), order = c("x", "y"), con = con)
win_over(sql("avg(x)"), frame = c(-Inf, 0), order = "y", con = con)

dbplyr

A 'dplyr' Back End for Databases

v2.1.1

MIT + file LICENSE

Authors

Hadley Wickham [aut, cre], Maximilian Girlich [aut], Edgar Ruiz [aut], RStudio [cph, fnd]

Initial release