Datasets:

SMVaddadi
/

propensity-data-bls-ces

series_id stringlengths 30 30	year int64 1.94k 2.03k	period stringclasses 13 values	value float64 -905.5 18.2k ⌀	footnote_codes stringclasses 2 values
SMS00000000000000021	1,991	M01	38.2	null
SMS00000000000000021	1,991	M02	25.5	null
SMS00000000000000021	1,991	M03	37.3	null
SMS00000000000000021	1,991	M04	45.1	null
SMS00000000000000021	1,991	M05	43.1	null
SMS00000000000000021	1,991	M06	64.7	null
SMS00000000000000021	1,991	M07	51	null
SMS00000000000000021	1,991	M08	60.8	null
SMS00000000000000021	1,991	M09	71.6	null
SMS00000000000000021	1,991	M10	60.8	null
SMS00000000000000021	1,991	M11	55.9	null
SMS00000000000000021	1,991	M12	59.8	null
SMS00000000000000021	1,992	M01	74.5	null
SMS00000000000000021	1,992	M02	64.7	null
SMS00000000000000021	1,992	M03	67.6	null
SMS00000000000000021	1,992	M04	87.3	null
SMS00000000000000021	1,992	M05	80.4	null
SMS00000000000000021	1,992	M06	56.9	null
SMS00000000000000021	1,992	M07	79.4	null
SMS00000000000000021	1,992	M08	66.7	null
SMS00000000000000021	1,992	M09	60.8	null
SMS00000000000000021	1,992	M10	85.3	null
SMS00000000000000021	1,992	M11	84.3	null
SMS00000000000000021	1,992	M12	66.7	null
SMS00000000000000021	1,993	M01	86.3	null
SMS00000000000000021	1,993	M02	87.3	null
SMS00000000000000021	1,993	M03	50	null
SMS00000000000000021	1,993	M04	90.2	null
SMS00000000000000021	1,993	M05	93.1	null
SMS00000000000000021	1,993	M06	81.4	null
SMS00000000000000021	1,993	M07	83.3	null
SMS00000000000000021	1,993	M08	81.4	null
SMS00000000000000021	1,993	M09	80.4	null
SMS00000000000000021	1,993	M10	89.2	null
SMS00000000000000021	1,993	M11	91.2	null
SMS00000000000000021	1,993	M12	92.2	null
SMS00000000000000021	1,994	M01	65.7	null
SMS00000000000000021	1,994	M02	78.4	null
SMS00000000000000021	1,994	M03	96.1	null
SMS00000000000000021	1,994	M04	88.2	null
SMS00000000000000021	1,994	M05	91.2	null
SMS00000000000000021	1,994	M06	92.2	null
SMS00000000000000021	1,994	M07	88.2	null
SMS00000000000000021	1,994	M08	84.3	null
SMS00000000000000021	1,994	M09	92.2	null
SMS00000000000000021	1,994	M10	64.7	null
SMS00000000000000021	1,994	M11	97.1	null
SMS00000000000000021	1,994	M12	76.5	null
SMS00000000000000021	1,995	M01	74.5	null
SMS00000000000000021	1,995	M02	84.3	null
SMS00000000000000021	1,995	M03	92.2	null
SMS00000000000000021	1,995	M04	53.9	null
SMS00000000000000021	1,995	M05	50	null
SMS00000000000000021	1,995	M06	83.3	null
SMS00000000000000021	1,995	M07	45.1	null
SMS00000000000000021	1,995	M08	94.1	null
SMS00000000000000021	1,995	M09	86.3	null
SMS00000000000000021	1,995	M10	57.8	null
SMS00000000000000021	1,995	M11	74.5	null
SMS00000000000000021	1,995	M12	85.3	null
SMS00000000000000021	1,996	M01	49	null
SMS00000000000000021	1,996	M02	88.2	null
SMS00000000000000021	1,996	M03	76.5	null
SMS00000000000000021	1,996	M04	74.5	null
SMS00000000000000021	1,996	M05	88.2	null
SMS00000000000000021	1,996	M06	80.4	null
SMS00000000000000021	1,996	M07	61.8	null
SMS00000000000000021	1,996	M08	88.2	null
SMS00000000000000021	1,996	M09	73.5	null
SMS00000000000000021	1,996	M10	94.1	null
SMS00000000000000021	1,996	M11	96.1	null
SMS00000000000000021	1,996	M12	67.6	null
SMS00000000000000021	1,997	M01	83.3	null
SMS00000000000000021	1,997	M02	92.2	null
SMS00000000000000021	1,997	M03	91.2	null
SMS00000000000000021	1,997	M04	86.3	null
SMS00000000000000021	1,997	M05	93.1	null
SMS00000000000000021	1,997	M06	81.4	null
SMS00000000000000021	1,997	M07	86.3	null
SMS00000000000000021	1,997	M08	60.8	null
SMS00000000000000021	1,997	M09	98	null
SMS00000000000000021	1,997	M10	86.3	null
SMS00000000000000021	1,997	M11	93.1	null
SMS00000000000000021	1,997	M12	96.1	null
SMS00000000000000021	1,998	M01	63.7	null
SMS00000000000000021	1,998	M02	92.2	null
SMS00000000000000021	1,998	M03	60.8	null
SMS00000000000000021	1,998	M04	74.5	null
SMS00000000000000021	1,998	M05	100	null
SMS00000000000000021	1,998	M06	73.5	null
SMS00000000000000021	1,998	M07	66.7	null
SMS00000000000000021	1,998	M08	88.2	null
SMS00000000000000021	1,998	M09	86.3	null
SMS00000000000000021	1,998	M10	73.5	null
SMS00000000000000021	1,998	M11	100	null
SMS00000000000000021	1,998	M12	91.2	null
SMS00000000000000021	1,999	M01	49	null
SMS00000000000000021	1,999	M02	94.1	null
SMS00000000000000021	1,999	M03	79.4	null
SMS00000000000000021	1,999	M04	86.3	null

End of preview. Expand in Data Studio

bls_ces — 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: Current Employment Statistics, U.S. Bureau of Labor Statistics
Origin URL: https://www.bls.gov/ces/
Loader: propensity.data.public_loaders.load_bls_ces
Extract: full pull from origin
Reported source: bls_ces
Rows pushed: 9,943,746
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 — Current Employment Statistics (state).

Loading

from propensity.data.hf_mirror import load_mirrored

result = load_mirrored("bls_ces", 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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