filter_keys: Filters .data according to all records in the filter

In SCDB: Easily Access and Maintain Time-Based Versioned Data (Slowly-Changing-Dimension)

Filters .data according to all records in the filter

Description

If filters is NULL, no filtering is done. Otherwise, the .data object is filtered via an inner_join() using all columns of the filter: inner_join(.data, filter, by = colnames(filter))

by and na_by can overwrite the inner_join() columns used in the filtering.

Usage

filter_keys(.data, filters, by = NULL, na_by = NULL, ...)

Arguments

.data	(data.frame(1), tibble(1), data.table(1), or tbl_dbi(1)) Data object.
filters	(data.frame(1), tibble(1), data.table(1), or tbl_dbi(1)) A object subset data by. If filters is NULL, no filtering occurs. Otherwise, an inner_join() is performed using all columns of the filter object.
by	A join specification created with join_by(), or a character vector of variables to join by. If NULL, the default, ⁠*_join()⁠ will perform a natural join, using all variables in common across x and y. A message lists the variables so that you can check they're correct; suppress the message by supplying by explicitly. To join on different variables between x and y, use a join_by() specification. For example, join_by(a == b) will match x$a to y$b. To join by multiple variables, use a join_by() specification with multiple expressions. For example, join_by(a == b, c == d) will match x$a to y$b and x$c to y$d. If the column names are the same between x and y, you can shorten this by listing only the variable names, like join_by(a, c). join_by() can also be used to perform inequality, rolling, and overlap joins. See the documentation at ?join_by for details on these types of joins. For simple equality joins, you can alternatively specify a character vector of variable names to join by. For example, by = c("a", "b") joins x$a to y$a and x$b to y$b. If variable names differ between x and y, use a named character vector like by = c("x_a" = "y_a", "x_b" = "y_b"). To perform a cross-join, generating all combinations of x and y, see cross_join().
na_by	(character()) Columns where NA should match with NA.
...	Further arguments passed to dplyr::inner_join().

Value

An object of same class as .data

Examples

  # Filtering with null means no filtering is done
  filter <- NULL
  identical(filter_keys(mtcars, filter), mtcars) # TRUE

  # Filtering by vs = 0
  filter <- data.frame(vs = 0)
  identical(filter_keys(mtcars, filter), dplyr::filter(mtcars, vs == 0)) # TRUE

  # Filtering by the specific combinations of vs = 0 and am = 1
  filter <- dplyr::distinct(mtcars, vs, am)
  filter_keys(mtcars, filter)

SCDB documentation built on Oct. 4, 2024, 1:09 a.m.