Flatten a nested volatility list into a single labelled data.table

Takes the nested list produced by the volatility section of [`compute_qualitycontrol()`] (or built manually from [`compute_volatility()`] calls) and collapses it into a single tidy `data.table`. Dictionary labels are joined for the grouping variable and the measured indicator, and a human-readable volatility-function label is added via an internal lookup table.

Usage

flatten_volatility(vol_list, dict = govhr::dictionary)

Arguments

vol_list: A named list (possibly nested) whose leaves are `data.table`s returned by [`compute_volatility()`].
dict: A data.frame with at least columns `variable_id` and `variable_name` used to look up human labels. Defaults to `govhr::dictionary`.

Value

A `data.table` with columns:

`stat_type`: Top-level list element name (e.g. `"salary_vol"`).
`vol_fn`: Code name of the volatility function (e.g. `"pct_change"`).
`vol_fn_label`: Human label (e.g. `"Percent Change"`).
`group_var`: Column name(s) used as the grouping variable.
`group_var_label`: Dictionary label for `group_var` (NA for composites).
`group_val`: Value of the grouping variable (character).
`ref_date`: Time period.
`indicator`: Aggregated indicator code (e.g. `"gross_salary_lcu_sum"`).
`indicator_label`: Dictionary label for the base variable.
`value`: Aggregated numeric value.
`vol_stat`: Computed volatility statistic.