| --- |
| license: apache-2.0 |
| language: |
| - en |
| pretty_name: US Industry Classification — free sectors for SEC filers, with dates |
| size_categories: |
| - 100K<n<1M |
| task_categories: |
| - tabular-classification |
| tags: |
| - finance |
| - sector |
| - industry |
| - classification |
| - sic |
| - naics |
| - sec |
| - edgar |
| - point-in-time |
| - backtesting |
| - ziplime |
| configs: |
| - config_name: classification |
| data_files: |
| - split: train |
| path: "data/classification/*.parquet" |
| - config_name: by_ticker |
| data_files: |
| - split: train |
| path: "data/by_ticker/*.parquet" |
| - config_name: spans |
| data_files: |
| - split: train |
| path: "data/spans/*.parquet" |
| - config_name: observations |
| data_files: |
| - split: train |
| path: "data/observations/*.parquet" |
| - config_name: sic_codes |
| data_files: |
| - split: train |
| path: "data/sic_codes/*.parquet" |
| - config_name: naics_map |
| data_files: |
| - split: train |
| path: "data/naics_map/*.parquet" |
| - config_name: taxonomy |
| data_files: |
| - split: train |
| path: "data/taxonomy/*.parquet" |
| --- |
| |
| # US Industry Classification |
|
|
| What business a listed company is in — and what business it was in then. |
|
|
| **22 270 filers · 11 334 live tickers · 23 835 dated classification spans · |
| 441 485 statements · 15 sectors, 90 industries · 2009 to 2026** |
|
|
| 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`](recipe/taxonomy.py). |
|
|
| The pipeline lives in [`recipe/`](recipe/) at the same revision as the data. |
| See [PIPELINE.md](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. |
|
|
| ```python |
| 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 |
|
|
| ```python |
| 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: |
|
|
| ```python |
| 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: |
|
|
| ```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](https://huggingface.co/datasets/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](https://huggingface.co/datasets/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](https://huggingface.co/datasets/ZipLime/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](NOTICE). |
|
|
| Rebuilt weekly, Monday 09:40 UTC, by a Hugging Face Job |
| ([`jobs/run.py`](jobs/run.py)) that lints, tests, rebuilds, verifies and only |
| then publishes. |
|
|
