Datasets:

eddmpython
/

dartlab-data

license: mit
task_categories:
  - table-question-answering
  - text-classification
  - time-series-forecasting
language:
  - ko
  - en
tags:
  - finance
  - disclosure
  - dart
  - edgar
  - sec
  - xbrl
  - korea
  - financial-statements
  - corporate-filings
  - krx
  - ohlcv
  - market-data
  - 전자공시
  - 재무제표
  - 사업보고서
  - 한국
pretty_name: DartLab 전자공시 + 시장 데이터
size_categories:
  - 1K<n<10K

DartLab Data

Structured company data + market data from DART, EDGAR, KRX

한국 DART 공시 + 미국 SEC EDGAR 공시 + KRX 시장 데이터 — 한 dataset, 여러 카테고리

What is this?

Pre-built Parquet files from DartLab — a Python library that turns DART (Korea), EDGAR (US), and KRX disclosure & market data into one structured company map.

한국 DART 전자공시 + 미국 SEC EDGAR 공시 + KRX 거래소 일별 시장 데이터를 동일한 SSOT 로 묶은 데이터셋.

This dataset is the data layer behind DartLab. When you run dartlab.Company("005930") or dartlab.gather("krx", "close"), the library auto-downloads the relevant parquet from this repo — no API key, no manual collection.

Datasets

7 public categories — each lives at its own subdirectory and is consumed by a specific dartlab engine.

Category	Path	Coverage	Engine
dart/docs	`dart/docs/`	2,547 KR companies, ~8 GB	`Company.show("section")`
dart/finance	`dart/finance/`	2,744 KR companies, ~586 MB	`Company.show("BS"/"IS"/"CF")`
dart/report	`dart/report/`	2,711 KR companies, ~319 MB	`Company.report()` (28 APIs)
dart/scan	`dart/scan/`	KR cross-sectional	`dartlab.scan("...")`
edgar/docs	`edgar/docs/`	970 US companies	`Company.show("section")` (US)
krx/prices ★	`krx/prices/`	1995~today, 17 yearly parquets	`gather("krx", target)`
landing/map	`landing/map/`	KR industry graph	`dartlab.industry()`

dart/docs — DART Disclosure Text

Full-text sections from Korean annual/quarterly reports, parsed into structured blocks.

Column	Description
`rcept_no`	DART filing ID
`rcept_date`	Filing date
`stock_code`	Stock code (6-digit)
`corp_name`	Company name
`report_type`	Annual/quarterly report type
`section_title`	Original section title (한글)
`section_order`	Section ordering
`content`	Section text (markdown)
`blockType`	`text` / `table` / `heading`
`year`	Filing year

File: dart/docs/{stockCode}.parquet — one file per company.

dart/finance — DART Financial Statements

XBRL-based financial data from DART OpenAPI (fnlttSinglAcntAll). BS/IS/CF/SCE × 분기/연간.

Column	Description
`bsns_year`	Business year
`reprt_code`	Report quarter code
`stock_code`	Stock code
`corp_name`	Company name
`fs_div`	`CFS` (consolidated) / `OFS` (separate)
`sj_div`	Statement type (BS/IS/CF/SCE)
`account_id`	XBRL account ID (~97% mapped to standard names)
`account_nm`	Account name (한글)
`thstrm_amount`	Current period amount
`frmtrm_amount`	Prior period amount
`bfefrmtrm_amount`	Two periods prior amount

File: dart/finance/{stockCode}.parquet — one file per company.

dart/report — DART Structured Disclosure APIs

28 DART API categories covering governance, compensation, shareholding, capital changes, audit opinions, and more.

Column	Description
`apiType`	API category (e.g., `dividend`, `employee`, `executive`)
`year` / `quarter`	Reporting period
`stockCode`	Stock code
`corpCode`	DART corp code
(varies)	Category-specific columns

28 API types: dividend, employee, executive, majorHolder, treasuryStock, capitalChange, auditOpinion, stockTotal, outsideDirector, corporateBond, and 18 more.

File: dart/report/{stockCode}.parquet — one file per company.

dart/scan — Cross-Sectional Pre-Built

Pre-computed cross-sectional aggregates across all KR listed companies (governance ratios, cash-flow patterns, financial ratios, etc.) — for ranking/screening without per-company iteration.

Subcategory	Content
`dart/scan/governance/`	Board structure, related-party, ownership concentration
`dart/scan/financial/`	Pre-computed ratios (ROE, debt-to-equity, ...)
`dart/scan/cashflow/`	Operating/investing/financing patterns

Engine: dartlab.scan("governance/...") — one call returns all-company DataFrame.

edgar/docs — EDGAR Disclosure Text

Full-text sections from US annual/quarterly reports (10-K, 10-Q, 8-K, ...), parsed into the same structure as dart/docs. Same library API works for both markets.

File: edgar/docs/{ticker}.parquet.

krx/prices — KRX Daily OHLCV ★ NEW

Daily OHLCV + market cap + listed shares for all KRX-listed companies (KOSPI + KOSDAQ), raw long parquet from KRX OpenAPI.

Column	Description	Unit
`BAS_DD`	Trade date (YYYYMMDD)	string
`ISU_CD`	Stock code (6-digit)	string
`ISU_NM`	Stock name	string
`MKT_NM` / `SECT_TP_NM`	Market / sector	string
`TDD_OPNPRC` / `TDD_HGPRC` / `TDD_LWPRC` / `TDD_CLSPRC`	Open / High / Low / Close	KRW
`ACC_TRDVOL` / `ACC_TRDVAL`	Volume / Amount	shares / KRW
`MKTCAP`	Market cap	KRW
`LIST_SHRS`	Listed shares	shares
`FLUC_RT` / `CMPPREVDD_PRC`	Daily change rate / price	% / KRW

Coverage: 1995-01-04 ~ today (17 yearly partitions: raw-1995.parquet ~ raw-2026.parquet). Update: every weekday at KST 17:00 (after market close + settlement). Auto gap-fill if any cron run is missed. Engine: gather("krx", target, ...) — pivot to wide (rows = stockCode, cols = date) on demand. Adjusted prices (split/bonus/rights) auto-applied via price-series detection (CRSP backward chaining).

import dartlab
dartlab.gather("krx", "close", start="2025-01-01", end="2025-06-30")  # close-price wide
dartlab.gather("krx", "rsi14", start="2025-01-01")                    # 30+ technical indicators
dartlab.gather("krx", "marketCap", start="2025-06-30")                # market cap snapshot

No API key needed — engine reads HF directly. (KRX OpenAPI key is only for operator cron building this dataset.)

landing/map — Industry Map JSON

Pre-built industry graph (nodes + edges) for the Korean market — companies × processes × supply-chain edges. Powers the /map interactive industry visualization.

Engine: dartlab.industry() / c.industry().

Usage

import dartlab

# 1. Korean company — auto-downloads dart/docs + dart/finance + dart/report
c = dartlab.Company("005930")
c.show("BS")                     # balance sheet (dart/finance)
c.show("businessOverview")       # business section text (dart/docs)
c.report("dividend")             # dividend history (dart/report)

# 2. US company — same API, edgar/docs auto
us = dartlab.Company("AAPL")
us.show("IS")

# 3. KRX market data — no API key, HF auto
df = dartlab.gather("krx", "close", start="2024-01-01", end="2024-12-31")  # 1-year wide DataFrame

# 4. Cross-sectional scan
ranked = dartlab.scan("governance/dividend")  # all KR companies, sorted

# 5. Natural language
dartlab.ask("삼성전자 재무건전성 분석해줘")

No API key, no setup — pip install dartlab and the library auto-downloads from this dataset, with local caching.

Data Source

DART (Korea): dart.fss.or.kr — Financial Supervisory Service's electronic disclosure system
EDGAR (US): sec.gov/edgar — SEC's Electronic Data Gathering, Analysis, and Retrieval system
KRX (Korea): openapi.krx.co.kr — Korea Exchange OpenAPI (daily OHLCV + market cap + shares)

All data sourced from public/government systems. Numeric figures preserved as-is from the original source — no rounding, no estimation, no interpolation. Adjusted prices computed at use time (raw + events SSOT).

Update Schedule

Category	Cadence	Trigger
`dart/docs`, `dart/finance`, `dart/report`	Daily incremental + weekly full sync	GitHub Actions (DART)
`dart/scan`	Daily after dart/finance update	GitHub Actions
`edgar/docs`	Daily incremental	GitHub Actions (EDGAR)
`krx/prices`	Every weekday at KST 17:00 (T-0 same-day, auto gap-fill)	GitHub Actions (KRX)
`landing/map`	On industry-map source change	GitHub Actions (map build)

Recent 7-day filings checked incrementally; full re-sync on schema changes.

Learn More

DartLab auto-downloads from this dataset — one stock code gives you the full company map. Start with the intro below.

_{▶ DartLab 30s Demo}

GitHub — github.com/eddmpython/dartlab
Intro blog — DartLab 시작하기 / Getting started
Docs — eddmpython.github.io/dartlab
YouTube — @eddmpython

License

Dataset content licensed MIT. Underlying source data is governed by each source's terms (DART, SEC EDGAR, KRX OpenAPI). See data source attribution.