joinless (version 0.0.1)

joinless_multiple: Infer relationship types between one dataset and multiple counterparts

Description

This function is a convenience wrapper around joinless() that compares a single dataset x against multiple datasets supplied in a list ys. Internally it calls joinless() once per dataset and row-binds the results, adding an extra column that identifies the target dataset.

Usage

joinless_multiple(
  x,
  ys,
  x_vars = NULL,
  y_vars = NULL,
  dataset_names = NULL,
  ...
)

Value

A data frame that row-binds the result of joinless() for all target datasets that were processed. It contains all columns returned by joinless() plus an additional column:

• dataset: identifier of the target dataset (one per element of ys).

If all datasets are skipped, an empty data frame is returned.

Arguments

x

A data frame. The reference dataset to compare from.

ys

A named or unnamed list of data frames. Each element is treated as a separate target dataset to compare x against.

x_vars

Optional character vector of column names in x to compare. Passed directly to joinless(). If NULL, the default behavior of joinless() is used (i.e., it selects up to max_vars variables).

y_vars

Optional character vector of column names to use in each target dataset. If not NULL, the function filters y_vars to those that exist in each dataset in ys before calling joinless(). If NULL, each dataset is allowed to use its own default variable selection in joinless() (up to max_vars).

dataset_names

Optional character vector with labels for each dataset in ys. If NULL and ys is a named list, the list names are used (empty names are replaced by "y1", "y2", …). If ys is unnamed, generic names "y1", "y2", … are generated. The length of dataset_names must match the length of ys if supplied.

...

Additional arguments passed on to joinless(), such as conf, error, n_x, n_y, max_vars, ignore, missingness_tol, type_coerce, seed, verbose, and info.

Details

For each dataset in ys, the function:

• optionally restricts the variables in x via x_vars,

• optionally restricts the variables in that dataset via y_vars,

• calls joinless() with the provided settings,

• tags the output with a dataset name.

When y_vars is not NULL, the function intersects y_vars with the column names of each dataset in ys. This means that:

• Variables listed in y_vars but missing in a given dataset are silently dropped for that dataset.

• If none of the variables in y_vars exist in a particular dataset, that dataset is skipped and a warning is emitted.

This behavior avoids producing "error_type" rows solely due to missing columns in some of the target datasets.

If all datasets are skipped (e.g., because none contain the requested y_vars), the function returns an empty data frame.

Examples

df_base <- data.frame(id = 1:5, value = 1:5)
df_a <- data.frame(id = 3:7, value = 3:7)
df_b <- data.frame(id_alt = 1:5, value = 11:15)

# Compare the same key from df_base against multiple datasets
res <- joinless_multiple(
  x = df_base,
  ys = list(a = df_a, b = df_b),
  x_vars = "id",
  y_vars = c("id", "id_alt"),
  info = TRUE
)