Datasets:

SMVaddadi
/

propensity-data-bls-laus

series_id stringlengths 30 30	year int64 2k 2k	period stringclasses 13 values	value float64 0 52.5M	footnote_codes null
LAUBS060000000000003	2,000	M01	5.2	null
LAUBS060000000000003	2,000	M02	5.2	null
LAUBS060000000000003	2,000	M03	5.3	null
LAUBS060000000000003	2,000	M04	4.6	null
LAUBS060000000000003	2,000	M05	4.5	null
LAUBS060000000000003	2,000	M06	4.9	null
LAUBS060000000000003	2,000	M07	5	null
LAUBS060000000000003	2,000	M08	4.8	null
LAUBS060000000000003	2,000	M09	4.3	null
LAUBS060000000000003	2,000	M10	4.3	null
LAUBS060000000000003	2,000	M11	4.5	null
LAUBS060000000000003	2,000	M12	4.3	null
LAUBS060000000000003	2,000	M13	4.7	null
LAUBS060000000000003	2,001	M01	5.2	null
LAUBS060000000000003	2,001	M02	5.1	null
LAUBS060000000000003	2,001	M03	5.3	null
LAUBS060000000000003	2,001	M04	4.9	null
LAUBS060000000000003	2,001	M05	4.5	null
LAUBS060000000000003	2,001	M06	5.1	null
LAUBS060000000000003	2,001	M07	5.3	null
LAUBS060000000000003	2,001	M08	5.5	null
LAUBS060000000000003	2,001	M09	5.3	null
LAUBS060000000000003	2,001	M10	5.8	null
LAUBS060000000000003	2,001	M11	6.2	null
LAUBS060000000000003	2,001	M12	6.2	null
LAUBS060000000000003	2,001	M13	5.4	null
LAUBS060000000000003	2,002	M01	7.1	null
LAUBS060000000000003	2,002	M02	6.9	null
LAUBS060000000000003	2,002	M03	7.1	null
LAUBS060000000000003	2,002	M04	6.6	null
LAUBS060000000000003	2,002	M05	6.1	null
LAUBS060000000000003	2,002	M06	6.7	null
LAUBS060000000000003	2,002	M07	6.9	null
LAUBS060000000000003	2,002	M08	6.6	null
LAUBS060000000000003	2,002	M09	6.3	null
LAUBS060000000000003	2,002	M10	6.5	null
LAUBS060000000000003	2,002	M11	6.9	null
LAUBS060000000000003	2,002	M12	6.8	null
LAUBS060000000000003	2,002	M13	6.7	null
LAUBS060000000000003	2,003	M01	7.5	null
LAUBS060000000000003	2,003	M02	7.4	null
LAUBS060000000000003	2,003	M03	7.3	null
LAUBS060000000000003	2,003	M04	6.9	null
LAUBS060000000000003	2,003	M05	6.5	null
LAUBS060000000000003	2,003	M06	7.2	null
LAUBS060000000000003	2,003	M07	7.1	null
LAUBS060000000000003	2,003	M08	6.7	null
LAUBS060000000000003	2,003	M09	6.4	null
LAUBS060000000000003	2,003	M10	6.4	null
LAUBS060000000000003	2,003	M11	6.6	null
LAUBS060000000000003	2,003	M12	6.3	null
LAUBS060000000000003	2,003	M13	6.8	null
LAUBS060000000000003	2,004	M01	7	null
LAUBS060000000000003	2,004	M02	6.8	null
LAUBS060000000000003	2,004	M03	7	null
LAUBS060000000000003	2,004	M04	6.2	null
LAUBS060000000000003	2,004	M05	5.7	null
LAUBS060000000000003	2,004	M06	6.3	null
LAUBS060000000000003	2,004	M07	6.3	null
LAUBS060000000000003	2,004	M08	5.8	null
LAUBS060000000000003	2,004	M09	5.5	null
LAUBS060000000000003	2,004	M10	5.6	null
LAUBS060000000000003	2,004	M11	5.7	null
LAUBS060000000000003	2,004	M12	5.6	null
LAUBS060000000000003	2,004	M13	6.1	null
LAUBS060000000000004	2,000	M01	623,883	null
LAUBS060000000000004	2,000	M02	628,129	null
LAUBS060000000000004	2,000	M03	641,455	null
LAUBS060000000000004	2,000	M04	552,748	null
LAUBS060000000000004	2,000	M05	542,003	null
LAUBS060000000000004	2,000	M06	594,308	null
LAUBS060000000000004	2,000	M07	611,155	null
LAUBS060000000000004	2,000	M08	585,195	null
LAUBS060000000000004	2,000	M09	523,451	null
LAUBS060000000000004	2,000	M10	525,197	null
LAUBS060000000000004	2,000	M11	557,517	null
LAUBS060000000000004	2,000	M12	535,749	null
LAUBS060000000000004	2,000	M13	576,733	null
LAUBS060000000000004	2,001	M01	640,687	null
LAUBS060000000000004	2,001	M02	633,956	null
LAUBS060000000000004	2,001	M03	656,708	null
LAUBS060000000000004	2,001	M04	597,851	null
LAUBS060000000000004	2,001	M05	548,690	null
LAUBS060000000000004	2,001	M06	637,562	null
LAUBS060000000000004	2,001	M07	659,990	null
LAUBS060000000000004	2,001	M08	682,807	null
LAUBS060000000000004	2,001	M09	658,671	null
LAUBS060000000000004	2,001	M10	724,237	null
LAUBS060000000000004	2,001	M11	776,682	null
LAUBS060000000000004	2,001	M12	776,875	null
LAUBS060000000000004	2,001	M13	666,226	null
LAUBS060000000000004	2,002	M01	883,115	null
LAUBS060000000000004	2,002	M02	866,902	null
LAUBS060000000000004	2,002	M03	882,297	null
LAUBS060000000000004	2,002	M04	827,184	null
LAUBS060000000000004	2,002	M05	761,630	null
LAUBS060000000000004	2,002	M06	842,202	null
LAUBS060000000000004	2,002	M07	862,365	null
LAUBS060000000000004	2,002	M08	837,060	null
LAUBS060000000000004	2,002	M09	794,280	null

End of preview. Expand in Data Studio

bls_laus — mirror

A convenience mirror of a public dataset, pushed by propensity.data.hf_mirror so that benchmark runs do not depend on a flaky upstream origin.

This is a mirror, not a grant of rights

Copyright and licence remain with the original source named below. Mirroring moves bytes; it does not and cannot change the terms they arrived under. If you intend to redistribute this further, or to use it commercially, read the original terms — not this card, and not the license: field above, which is our best reading and may be wrong.

Provenance

Source: Local Area Unemployment Statistics, U.S. Bureau of Labor Statistics
Origin URL: https://www.bls.gov/lau/
Loader: propensity.data.public_loaders.load_bls_laus
Extract: full pull from origin
Reported source: bls_laus
Rows pushed: 2,087,995
Columns: 5

Licence and redistribution

Licence as found: other (us-public-domain)
Redistribution verdict: open
Basis: BLS, public domain (public_loaders/init.py)

This is US-government material and therefore in the public domain as a matter of US law. The frontmatter says other rather than cc0-1.0 on purpose: CC0 is a waiver that only a rights holder can execute, and we are not the rights holder. Claiming it would be the same error that makes much of this Hub's licence metadata untrustworthy.

Citation

U.S. Bureau of Labor Statistics — Local Area Unemployment Statistics.

Loading

from propensity.data.hf_mirror import load_mirrored

result = load_mirrored("bls_laus", org="SMVaddadi")
result.frame.head()

load_mirrored falls back to the original loader (origin, then its own offline replica) if this mirror is unreachable, so it is safe to depend on.

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