Free to use, free to redistribute. Built entirely from US government works: the SIC code the SEC assigns to every filer, and the Census Bureau's bridge to NAICS. The rollup from those codes to sectors is ZipLime's own, published under Apache-2.0 in recipe/taxonomy.py.

The pipeline lives in recipe/ at the same revision as the data. See PIPELINE.md for the method and its limits.

This is not GICS and not ICB

It cannot be. GICS belongs to MSCI and S&P Dow Jones Indices, ICB to FTSE Russell, and neither can be redistributed — which is the whole reason this exists. Nothing licensed from either was used or consulted.

So expect disagreements, and know where they are:

Alphabet and Meta are Technology here, Communication Services in GICS. The SEC files both under 7370, alongside systems integrators, and nothing in a filing separates an advertising platform from a consultancy.
Disney is Consumer Cyclical here, Communication Services in GICS. Its assigned code is 7990, amusement and recreation. The code is the SEC's.
Blank cheque companies get a sector of their own. GICS has no bucket for one. 2 181 filers here have been one, and anyone building a universe wants to drop them by name rather than find them scattered through Financials.

If you have a GICS or ICB licence, the sic column is here to join against.

The point: it is dated

A company's industry is not a constant. 2 320 filers have been reclassified at least once — most often a blank cheque that became an operating company.

import polars as pl

history = pl.read_parquet("data/by_ticker/*.parquet")
history.filter(pl.col("ticker") == "LCID").select(
    "valid_from", "valid_to", "sic", "sector", "industry"
)
# 2021-07-27 … 2026-08-04 | 3711 | Consumer Cyclical | Automobiles

Churchill Capital IV was SIC 6770, a blank cheque, until it became Lucid. A dataset that states only today's code calls it a car maker in 2020, and a sector-neutral backtest then shorts the automotive basket against an empty shell.

Getting a sector for a ticker

import polars as pl

live = (
    pl.read_parquet("data/by_ticker/*.parquet")
      .filter(pl.col("is_current"))
      .select("ticker", "cik", "sector_code", "sector", "industry", "sic")
)

is_current marks exactly one row per live symbol: the filer's ticker now, under the newest code it has been seen under. For a date in the past, filter on the window instead:

on = pl.date(2015, 6, 30)
history.filter((pl.col("valid_from") <= on) & (on <= pl.col("valid_to")))

Join on cik wherever you have it. It is stable, and it is the key the rest of this dataset family uses.

Configs

Config	Rows	What one row is
`classification`	22 270	one filer: the sector it is in now, fully resolved
`by_ticker`	30 820	one ticker over one window, with the sector it was in then
`spans`	23 835	one run of filings that all stated the same SIC code
`observations`	441 485	one dated statement — the evidence the spans are built from
`sic_codes`	444	one EDGAR SIC code: hierarchy, sector, NAICS bridge, usage
`naics_map`	1 854	one 1987 SIC to 1997 NAICS pair from the Census concordance
`taxonomy`	90	one industry of the taxonomy and the SIC ranges it covers

observations is published so that anyone who disagrees with how the spans were cut can cut their own. It is the only honest way to ship a judgement.

The taxonomy

Fifteen sectors. Thirteen are what you would expect; three exist because the SEC's universe is not just operating companies.

Sector	Live filers	Note
Health Care	1 426	includes Managed Health Care — Centene, Cigna, Elevance
Industrials	1 149
Technology	1 048	includes Internet Software & Services
Financials	1 054
Consumer Cyclical	766
Funds & Trusts	591	closed-end funds, ETFs, securitisation vehicles
Materials	506
Shell & Blank Check	444	SPACs and non-operating establishments
Unclassified	417	almost all depositary receipt programmes
Real Estate	336
Energy	272
Consumer Defensive	267
Telecom & Media	220
Utilities	182
Government	—	foreign sovereigns and public administration

No sector holds more than 17% of the live universe, which is the test the SIC divisions fail: Division D, Manufacturing, is a third of it on its own.

Read the taxonomy without reading Python:

pl.read_parquet("data/taxonomy/*.parquet").select(
    "sector", "industry", "sic_ranges"
)

Where it comes from

Source	What it gives	Rows
XBRL filing headers, via ZipLime/company-fundamentals	the code the SEC had a filer under, on the day it filed — the only free source of SIC history	437 619
EDGAR's submissions archive	today's code for filers that never filed XBRL: delisted before 2009, funds, foreign issuers on paper	3 866
EDGAR's submissions archive, read for forms	what kind of entity a filer with no code is — N-CSR means a registered investment company, F-6 a depositary receipt programme	1 476
Ticker windows, via ZipLime/security-master	which symbol belonged to which filer, when	29 584
SEC's published SIC code list	the title of each code and the office that reviews it	444
Census Bureau 1987 SIC → 1997 NAICS concordance	the NAICS bridge, and the 1987 hierarchy's own titles	1 854

Coverage and honest gaps

97.2% of live tickers get an answer. The remainder are dormant filers EDGAR has never classified and whose forms say nothing either.
Nothing before 2009. XBRL headers begin in 2009 Q2. A company's code in 1998 is in the SGML header of its filings and is not read here.
date_basis tells you what the dates are worth. dated (15 565 rows) means a filing stated the code inside that window. undated (12 765) means a code is known for the filer but nothing dates it to that window, so the latest one is applied across it. unknown (2 490) means no code at all.
Two fifths of EDGAR's codes are roll-ups. 2000 means all of food, 3570 all of computer and office equipment. sic_level says which you have: 284 of the 444 are real four-digit industries, 118 are three-digit groups, 42 are two-digit major groups.
The NAICS bridge is weak and labelled as such. Only 32.7% of codes resolve to exactly one 1997 NAICS industry and 71.8% to one NAICS sector. naics_1997 and naics_sector are filled only where the answer is unique; naics_candidates says how many there were. The full crosswalk is in naics_map.
8731 mixes contract research with research-stage biotech. Charles River and Incyte share a code, and nothing in a filing separates them.
51 symbols are current for two filers, 28 of them in different sectors. Genuine ticker transfers and reuse — Barnes Group handed B to Barrick. Each row is right for its own filer; deciding who owns a symbol today is security-master's job.
The classification is the SEC's opinion, not the company's. Assigned codes go stale; the SEC does not re-review them on a schedule.

Provenance and updates

Sources: SEC EDGAR (filing headers via the sibling dataset, and the submissions archive), the SEC's SIC code list, and the US Census Bureau's SIC-to-NAICS concordance — all US Government works in the public domain. The sector taxonomy is ZipLime's own work under Apache-2.0. See NOTICE.

Rebuilt weekly, Monday 09:40 UTC, by a Hugging Face Job (jobs/run.py) that lints, tests, rebuilds, verifies and only then publishes.

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