APProjects/us-warn-act-employer-layoff-history

US layoff-notice history by employer — 27,307 employers, rebuilt daily

Last rebuilt: 2026-09-08. One row per employer, not per notice. Every US WARN Act layoff notice we can reach from 42 state labor-department portals, grouped by a canonicalized employer name, so you can ask employer-level questions in one line instead of writing the groupby yourself.

27,307	employers with at least one WARN notice on file
5,751	of them have filed more than once
55%	share of all 48,191 notices that come from those repeat filers
2,231	employers that have filed in more than one state
26	states covered by the widest filer (Walmart)
5,362,155	workers named across every notice that publishes a headcount

The single most useful thing in here: layoffs are concentrated in employers who do it repeatedly. 5,751 employers (21% of the list) account for 26,635 of 48,191 notices (55%). A one-notice employer is the common case; the notices themselves are not.

Quickstart

from datasets import load_dataset
ds = load_dataset("APProjects/us-warn-act-employer-layoff-history", split="train")
print(ds[0])

import pandas as pd
url = ("https://huggingface.co/datasets/APProjects/us-warn-act-employer-layoff-history"
       "/resolve/main/data/employer_history.csv")
df = pd.read_csv(url)

df.nlargest(20, "workers_affected")[["company_canonical", "notices", "workers_affected", "n_states"]]
df[df.n_states >= 5].sort_values("notices", ascending=False).head(20)   # serial multi-state filers
df[df.latest_activity >= "2026-01-01"]                                   # who is still filing now

Columns

column	meaning
company_canonical	employer name after canonicalization (Amazon.com Services LLC and Amazon roll up together)
notices	WARN notices on file for this employer
notices_with_headcount	how many of those notices publish an integer headcount
workers_affected	sum of headcounts, over notices_with_headcount rows only
states	pipe-separated USPS codes this employer has filed in
n_states	length of that list
first_activity	earliest dated notice (notice date, or effective date when the state publishes none)
latest_activity	most recent dated notice, same rule
dated_by_effective	how many of this employer's rows were dated by effective date because no notice date was published

The largest employers by workers noticed

employer	notices	workers	states	first	latest
United Airlines	34	63,380	11	1993-10-28	2021-07-01
Boeing	402	42,214	12	1998-11-30	2026-04-13
Northwest Airlines	3	27,698	2	1998-08-11	2005-07-29
Walt Disney Parks and Resorts U.S	26	24,769	2	2015-01-21	2021-01-20
usi services group	1	23,695	1	2020-03-01	2020-03-01
OS Restaurant Services	21	21,045	6	2019-04-01	2020-05-15
Walmart	130	20,749	26	2015-04-13	2026-06-23
David's Bridal	38	20,085	16	2020-05-15	2023-08-11
Tesla	48	19,995	4	2017-08-30	2024-05-13
Tend Exchange Subsidiary LLC and Delaware Tender Staffing	1	16,132	1	2025-05-20	2025-05-20
Kmart	175	14,737	16	1994-09-16	2019-09-04
Amazon	69	14,119	12	2009-03-25	2026-08-31

Honest scope — read this before you cite it

• workers_affected undercounts. Only rows that publish an integer headcount are summed; notices_with_headcount tells you how many that was for each employer.
• Dates. MI, PA and SC publish no notice date at all. Those rows are dated by their effective date and counted in dated_by_effective rather than silently guessed.
• Grouping is by name, not by legal entity. Canonicalization merges obvious variants; it cannot merge a subsidiary filing under its own name, and it cannot split two unrelated businesses that share a name. There is no employer identifier in WARN data — no EIN, no DUNS — so any employer-level WARN dataset, including this one, is a name-matching exercise. Treat the rollup as a strong hint, not a legal fact.
• Coverage is 42 states, not 50. Not covered yet: AR, HI, ID, MA, MN, MO, ND, NH, NV, OH, WY. The notice-level mirror carries coverage.json with the authoritative per-state list and scrape stamps.
• Compiled from state workforce-agency portals. Independent project, not affiliated with any government agency; not legal, financial or employment advice.

Where this comes from

Derived on every daily refresh from the notice-level dataset: APProjects/us-warn-act-layoffs-notices-daily (48,191 notices, 42 states, back to 1988). Companion from the same morning's run: the monthly time series (one row per month, 1988 → today, plus a per-state table). All three are rebuilt by the same pipeline on the same morning, so they are never out of step with each other. Full site with per-state and per-employer pages, roll-ups, search and RSS: approjects-warn-act-notices.static.hf.space.

A one-off scrape of WARN data starts rotting the week it is posted — states amend headcounts, re-issue notices and drop rows. Compare the rebuild date at the top of this card with the "last modified" date on any other US WARN dataset before you pick one.

Getting told when an employer on this list files again

Everything above is free, CC BY 4.0, no account. The one paid thing this project sells is the watching: WARN Watch — up to 25 employer terms plus whole states, matched on every daily rebuild for a year, with a private alert page, RSS and an optional Slack / Discord / Teams webhook ($49/year). Every alert carries that employer's whole filing record from this dataset. Try it first for nothing: free 30-day watch, no card, nothing renews.

Corrections: open an issue — they ship the same day.

Cite as: "WARN Feed — US layoff-notice history by employer, rebuilt 2026-09-08, huggingface.co/datasets/APProjects/us-warn-act-employer-layoff-history".