jared
cc4d21ec82
cog_find_peers selects peers from canonical_fips_xwalk by same-type,
same-state, and population-range (ratio or absolute) criteria,
ordered by |log(pop_ratio)| ascending.
cog_peer_compare accepts the find_peers result (or a plain character
vector of govids), pulls spending for target + peers via cog_spending,
and appends summary rows (summary_p25/p50/p75) so the whole result
can be faceted by `role` in a single ggplot call. Summary rows honor
per_capita + adjust_to_year by picking the right value column.
target_rank reports the target's rank among target+peers at max(years).
Provenance is rewritten with verb = cog_peer_compare and peer_count.
Also: globalVariables('.data') in zzz.R to silence R CMD check on
tidy-eval pronouns.
Tests: 21 new / 120 total pass. devtools::check() 0E/0W/2N.
15 lines
357 B
R
15 lines
357 B
R
# R/zzz.R
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.onLoad <- function(libname, pkgname) {
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invisible(NULL)
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}
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# Silence R CMD check "no visible binding" for tidy-eval pronouns used in
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# dplyr verbs. `.data` comes from rlang and is guaranteed to resolve at
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# evaluation time inside dplyr data-masking contexts.
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utils::globalVariables(c(".data"))
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.onUnload <- function(libpath) {
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cog_close()
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}
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