Perform join where the outcome of the join is verifed to match an expected pattern.

Usage

join_control(
  x,
  y,
  join_fun,
  x_control = "any",
  y_control = "any",
  x_fraction = NA_real_,
  y_fraction = NA_real_,
  x_count = NA_integer_,
  y_count = NA_integer_,
  overlap_fraction = NA_real_,
  overlap_count = NA_integer_,
  ...
)

join_many_to_one(x, y)

join_one_to_one(x, y)

Arguments

x, y: tbls to join
join_fun: Any function that can combine x and y (called as join_fun(x, y, ...)). Typically this will be one of dplyr::left_join, dplyr::right_join, etc.
x_control, y_control: What outcome is expected from the x, and y tbls? Default is "any" (see details).
x_fraction, y_fraction, x_count, y_count: What fraction or count of the rows of x and y must be in the final data? Fractions are converted to row counts by rounding up to the nearest integer.
overlap_fraction, overlap_count: What fraction or count of the rows of the return value must overlap (i.e. have rows from both) x and y? Fractions are converted to row counts by rounding up to the nearest integer.
...: Passed to join_fun()

Value

A joined tbl

Details

Options for x_control and y_control are below and may be combined:

"any": Any outcome is acceptable; this overrides all other options.
"all": Each row from the input must appear in the output at least one time.
"unique": A row may appear in the output zero or one time.
"missing": At least one row must not match in the new dataset (the values must be missing). This option is rarely used.
"nomissing": All rows must match in the new dataset (the values must not be missing).

The combination of x_control=c("all", "unique", "nomissing") (or y_control) is a common need to confirm that all values are present exactly one time and that there are no missing values.

Functions

join_many_to_one(): For the common task of many-to-one mapping, the helper function `join_many_to_one()` works.
join_one_to_one(): For the common task of one-to-one mapping, the helper function `join_one_to_one()` works.