project_se: project data by grouping, and adding aggregate columns.

In rquery: Relational Query Generator for Data Manipulation at Scale

project data by grouping, and adding aggregate columns.

Description

project data by grouping, and adding aggregate columns.

Usage

project_se(source, assignments, ..., groupby = c(), env = parent.frame())

aggregate_se(source, assignments, ..., groupby = c(), env = parent.frame())

Arguments

source	source to select from.
assignments	new column assignment expressions.
...	not used, force later arguments to be by name
groupby	grouping columns.
env	environment to look for values in.

Value

project node.

Examples

if (requireNamespace("DBI", quietly = TRUE) && requireNamespace("RSQLite", quietly = TRUE)) {
  my_db <- DBI::dbConnect(RSQLite::SQLite(),
                          ":memory:")
  d <- rq_copy_to(
    my_db, 'd',
    data.frame(group = c('a', 'a', 'b', 'b'),
               val = 1:4,
               stringsAsFactors = FALSE))

  op_tree <- d %.>%
    project_se(., groupby = "group", "vmax" %:=% "max(val)")
  cat(format(op_tree))
  sql <- to_sql(op_tree, my_db)
  cat(sql)
  execute(my_db, op_tree) %.>%
     print(.)

  op_tree <- d %.>%
    project_se(., groupby = NULL, "vmax" %:=% "max(val)")
  cat(format(op_tree))
  sql <- to_sql(op_tree, my_db)
  cat(sql)
  execute(my_db, op_tree) %.>%
     print(.)

  DBI::dbDisconnect(my_db)
}

rquery documentation built on Aug. 20, 2023, 9:06 a.m.