jared
c682e6547d
Three core query verbs over the spending_annotated / revenue_annotated DuckDB views. Each verb accepts vector govid, vector years, optional category filter, per_capita flag, and adjust_to_year for CPI-U real-dollar conversion (bundled index). Amounts are returned in full USD (SUM(amt) * 1000) so callers can freely rescale to millions/billions. The $1,000s -> $USD conversion is recorded in provenance$transformations$units_conversion. Every result carries an attr(., "provenance") list matching inst/schemas/provenance-v1.json. cog_explain() prints the structured form via cli or returns the raw list for MCP/JSON consumers. Also: .fetch_or_cache_manifest() now handles local fixture paths so tests can point USCOGDATA_FIXTURE_URL at the pipeline publish_cache/ without a working HTTP server. Tests: 80 pass / 0 fail. devtools::check() 0E/0W/2N (both notes pre-existing / environmental).
30 lines
1.1 KiB
R
30 lines
1.1 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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#' `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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.verb_spendrev(
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verb = "cog_revenue",
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view = "revenue_annotated",
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subtype_col = "revenue_subtype",
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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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)
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}
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