Audit a panel dataset

audit_panel() checks whether a dataset has the expected structure of a panel dataset. It reports the number of panel units, time periods, observed rows, unique unit-time cells, expected unit-time cells, missing unit-time cells, duplicate unit-time cells, and whether the panel is balanced.

Usage

audit_panel(data, id, time)

Arguments

data

A data frame or tibble.

id

Unquoted column name identifying the panel unit, such as a person, firm, district, county, or country.

time

Unquoted column name identifying the time period, such as a year, month, quarter, or date.

Value

An object of class panelbuild_panel_audit. The object is a list containing panel metadata, balance information, counts of missing and duplicate unit-time cells, and data frames containing the missing and duplicate cells.

Details

A panel is treated as balanced when every observed panel unit appears in every observed time period exactly once. Missing cells are unit-time combinations that are implied by the full unit-by-time grid but are not present in the data. Duplicate cells are unit-time combinations that appear more than once.

audit_panel() does not modify the input data. It returns an audit object that can be summarized with audit_summary() and inspected with accessor functions such as missing_cells() and duplicate_cells().

See also

audit_summary(), missing_cells(), duplicate_cells(), duplicate_summary(), gap_summary(), complete_panel()

Examples

audit_panel(example_panel, id = id, time = year)
#> Panel audit
#> 
#> Data: example_panel
#> Unit variable: id
#> Time variable: year
#> 
#> Units: 3
#> Time periods: 4
#> Observed rows: 9
#> Observed id-time cells: 8
#> Expected id-time cells: 12
#> Missing id-time cells: 4
#> Duplicate id-time cells: 1
#> Balanced panel: No