jared
7818cd2b1a
Adds schema_version 5 support alongside the existing v4 corpus:
.validate_schema() now accepts a supported set (4, 5) instead of a single
expected version, and cog_spending()/cog_revenue() gain basis =
c("harmonized", "raw"). Harmonized basis routes to new
spending_annotated_harmonized / revenue_annotated_harmonized views built on
spending_long_harmonized / revenue_long_harmonized (REPLACE(harmonized_code
AS item_code), excluding aggregate and NA-harmonized rows); raw basis is
byte-identical to the pre-Phase-R2 behavior. On a v4 corpus, an unspecified
basis silently resolves to "raw" with a provenance note; an explicit
basis = "harmonized" aborts with an actionable message.
Provenance gains basis, basis_note, and a harmonization block
(applied/na_rows_excluded/na_amount_excluded). The five new schema-v5-only
SQL views (harmonized long/annotated views, harmonization_map,
harmonization_recipes, series_breaks_pq) are registered conditionally on
manifest$schema_version >= 5, since DuckDB's read_parquet() errors eagerly
at CREATE VIEW time when the backing file doesn't exist on a v4 corpus.
Fixture corpus regenerated to schema_version 5 / years 2011, 2012, 2019,
2020 (2011->2012 spans the wide-aggregate -> modern-leaf format boundary
needed for the harmonization/recipe work), with the harmonization_map /
harmonization_recipes / series_breaks parquet tables bundled alongside the
existing metadata registries.
33 lines
1.2 KiB
R
33 lines
1.2 KiB
R
# R/revenue.R
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#' Summarized revenue by category
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#'
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#' Mirror of [cog_spending()] for revenue categories. One row per
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#' `(year, canonical_govid, revenue_subtype, category)`. Amounts are returned
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#' in **full U.S. dollars** (raw Census values are in $1,000s; this verb
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#' multiplies by 1000 and records the conversion in `provenance`).
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#'
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#' @inheritParams cog_spending
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#' @return Tibble with columns `year`, `canonical_govid`, `gov_name`,
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#' `revenue_subtype`, `category`, `amt_nominal`, optional `amt_real`,
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#' optional `amt_per_capita_nominal`, optional `amt_per_capita_real`,
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#' optional `pop_source`, `codes_included`, `aggregate_fallback`, `notes`.
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#' @export
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cog_revenue <- function(govid, years, category = NULL,
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per_capita = FALSE, adjust_to_year = NULL,
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basis = c("harmonized", "raw")) {
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.verb_spendrev(
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verb = "cog_revenue",
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view_base = "revenue_annotated",
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subtype_col = "revenue_subtype",
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flow_prefixes = c("T", "A", "U", "B", "C", "D"),
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call = match.call(),
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govid = govid,
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years = years,
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category = category,
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per_capita = per_capita,
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adjust_to_year = adjust_to_year,
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basis = basis
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)
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}
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