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Consolidate Multiple Meta Datasets Into a Single One

Source: R/consolidate_metadata.R
consolidate_metadata.Rd

The purpose of the function is to consolidate multiple meta datasets into a single one. For example, from global and project specific parameter mappings a single lookup table can be created.

Usage

consolidate_metadata(
  datasets,
  key_vars,
  source_var = SOURCE,
  check_vars = "warning",
  check_type = "error"
)

Arguments

datasets

List of datasets to consolidate

Permitted Values: A named list of datasets

key_vars

Key variables

The specified variables must be a unique of all input datasets.

Permitted Values: A list of variables created by exprs()

source_var

Source variable

The specified variable is added to the output dataset. It is set the name of the dataset the observation is originating from.

Permitted Values: A symbol

check_vars

Check variables?

If "message", "warning", or "error" is specified, a message is issued if the variable names differ across the input datasets (datasets).

Permitted Values: "none", "message", "warning", "error"

check_type

Check uniqueness?

If "warning" or "error" is specified, a message is issued if the key variables (key_vars) are not a unique key in all of the input datasets (datasets).

Permitted Values: "none", "warning", "error"

Value

A dataset which contains one row for each by group occurring in any of the input datasets.

Details

All observations of the input datasets are put together into a single dataset. If a by group (defined by key_vars) exists in more than one of the input datasets, the observation from the last dataset is selected.

See also

Creating auxiliary datasets: create_period_dataset(), create_query_data(), create_single_dose_dataset()

Examples

library(tibble)
glob_ranges <- tribble(
  ~PARAMCD, ~ANRLO, ~ANRHI,
  "PULSE",      60,    100,
  "SYSBP",      90,    130,
  "DIABP",      60,     80
)
proj_ranges <- tribble(
  ~PARAMCD, ~ANRLO, ~ANRHI,
  "SYSBP",     100,    140,
  "DIABP",      70,     90
)
stud_ranges <- tribble(
  ~PARAMCD, ~ANRLO, ~ANRHI,
  "BMI",        18,     25
)

consolidate_metadata(
  datasets = list(
    global = glob_ranges,
    project = proj_ranges,
    study = stud_ranges
  ),
  key_vars = exprs(PARAMCD)
)
#> # A tibble: 4 × 4
#>   SOURCE  PARAMCD ANRLO ANRHI
#>   <chr>   <chr>   <dbl> <dbl>
#> 1 study   BMI        18    25
#> 2 project DIABP      70    90
#> 3 global  PULSE      60   100
#> 4 project SYSBP     100   140