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FULL-COVERAGE grouped ingest of U.S. Census Bureau TIME-SERIES datasets. Enumerates every dataset in https://api.census.gov/data.json, keeps the ones whose c_dataset starts with "timeseries/", and pulls each one FULLY via the Census API (api.census.gov). ONE Parquet per dataset under…
U.S. Census Bureau, Economic Indicators Time Series. Retrieved from https://www.census.gov. Compiled and redistributed by the Elkassabgi Data Library.
Processing: Retrieved from the official source, normalized to a long {series_key, obs_date, value} schema (period-start dates), de-duplicated, and stored as zstd Parquet. Compiled and redistributed by the Elkassabgi Data Library.
FULL-COVERAGE grouped ingest of U.S. Census Bureau TIME-SERIES datasets. Enumerates every dataset in https://api.census.gov/data.json, keeps the ones whose c_dataset starts with "timeseries/", and pulls each one FULLY via the Census API (api.census.gov). ONE Parquet per dataset under data/clean_full/census/, in long "wide-record" form: every retrievable variable as a column (Census returns strings), plus a constructed `series_key` (the non-time dimension columns joined) and the time/period columns. us-public-domain. Strategy per dataset (driven by data.json + variables.json + geography.json): * time-based ("time" required/present) -> one pull per no-parent geo level with time=from+1900 (full history in a single response); plus child geo levels iterated over their required parent(s). * YEAR / year+quarter only (asm area/benchmark, qwi) -> enumerate the year(s) (and quarters) discovered from the API, iterate geographies. * no predicate at all (pseo, some asm value/benchmark) -> single pull per geo. The Census API caps get= at 50 variables, so variables are chunked (<=45) with the key columns repeated in every chunk and the chunks merged on those keys. Usage: python jobs/ingest_census.py --list # just print the catalog census python jobs/ingest_census.py --only timeseries/govs # one dataset python jobs/ingest_census.py --group eits # one group python jobs/ingest_census.py # FULL run (all 93)
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