M5: README.md described the bundled fixture as a "3.6 MB two-year slice (2019 + 2020)"; it's now a 15 MB four-year slice (2011, 2012, 2019, 2020), matching the regenerated fixture and the vignette's own description. M2: total-spending.Rmd cited County 1.8% / City 0.8% intergovernmental- to-Direct and County 91.6% L/M, all roughly 2x off against the bundled fixture. Measured directly against the fixture (all 50 states, each of its four years): County IG/Direct 3.4%-5.1%, City IG/Direct 2.6%-3.1%, County L/M 43%-51% (all varying by year). State 17.2%, AL 7.6%, national 11.6%, and City L/M 188.3% were re-checked and left as-is. M1: the "Why Total = Direct + M + L" paragraph described money a local government *receives* and the state "redistributing as M" -- backwards. M and L are both the *queried* government's own payments *out*: M to other local governments, L up to its state. Rewrote the explanation; the conclusion and non-M2-flagged figures are unchanged.
uscogdata
Curated R reader for the Civilytics US Census of Governments finance corpus.
Provides unit-level financial profiles, geographic rollups, and peer comparisons with auditable provenance and built-in cross-vintage correctness. Reads the published corpus (Hive-partitioned parquet + manifest.json) directly from Nextcloud via DuckDB httpfs — no local bulk downloads required.
Status
Under active development (Phase 2 of the cog_pipeline project). See
../cog_pipeline/docs/reader-specification.md for the reader contract this
package implements.
Installation
# pak::pkg_install("gitea.civilytics.org/Civilytics/uscogdata")
Configuration
USCOGDATA_URL— corpus root URL (public Nextcloud share, trailing slash)USCOGDATA_CACHE_DIR— optional override for the manifest cache directoryUSCOGDATA_MANIFEST_TTL_SECS— optional manifest re-fetch TTL (default 3600)
Direct vs Total spending
cog_spending(..., expenditure_concept = c("direct", "total")) controls
whose spending a result counts. "direct" (the default) is a government's
own current operations, capital outlay, and other direct spending. "total"
additionally adds in the intergovernmental legs — money it hands to other
governments to spend on its behalf — which is meaningful for describing one
government's own budget over time, but double-counts when summed across
governments (a state's payment to a county is the same dollar the county
reports as its own direct spending).
Rule of thumb: any figure that spans more than one government uses
direct. cog_geographic_rollup() and cog_peer_compare() enforce this
by refusing expenditure_concept = "total". See
vignette("total-spending", package = "uscogdata") for the full
explanation with worked examples.
Developer notes
Testing
The package ships a bundled fixture corpus at inst/extdata/fixture_corpus/ —
a 15 MB four-year slice (2011, 2012, 2019, 2020) of the full corpus covering
all 50 states. tests/testthat/setup.R automatically points USCOGDATA_URL
at this fixture, so the full test suite runs offline with no network
dependency:
devtools::test() # uses bundled fixture, no credentials required
Releasing against the live corpus
Before cutting a release, run the test suite against the published corpus to catch any drift between the fixture and the real data:
Sys.setenv(USCOGDATA_URL = "<published-corpus-url-with-trailing-slash>")
devtools::test()
When the live-corpus run is clean, strip the fixture from the built package by
adding this line to .Rbuildignore:
^inst/extdata/fixture_corpus$
The test suite is URL-agnostic — setup.R falls back to USCOGDATA_URL when
the bundled fixture is absent, so no test code changes are needed for the
release run or after stripping the fixture.