The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 127, in _split_generators
self.info.features = datasets.Features.from_arrow_schema(pq.read_schema(f))
~~~~~~~~~~~~~~^^^
File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 2459, in read_schema
file = ParquetFile(
where, memory_map=memory_map,
decryption_properties=decryption_properties)
File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 328, in __init__
self.reader.open(
~~~~~~~~~~~~~~~~^
source, use_memory_map=memory_map,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
...<8 lines>...
arrow_extensions_enabled=arrow_extensions_enabled,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "pyarrow/_parquet.pyx", line 1656, in pyarrow._parquet.ParquetReader.open
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
DartLab Data
Structured company data from DART & EDGAR disclosure filings
DART 전자공시 + EDGAR 공시 데이터 — 한국 2,700사 / 미국 970사
What is this?
Pre-collected Parquet files from DartLab — a Python library that turns DART (Korea) and EDGAR (US) disclosure filings into one structured company map.
한국 DART 전자공시 시스템과 미국 SEC EDGAR에서 수집한 기업 공시 데이터입니다.
This dataset is the data layer behind DartLab. When you run dartlab.Company("005930"), the library automatically downloads the relevant parquet from this repo.
Dataset Structure
dart/
├── docs/ 2,547 companies ~8 GB disclosure text (sections, tables, markdown)
├── finance/ 2,744 companies ~586 MB financial statements (BS, IS, CF, XBRL)
└── report/ 2,711 companies ~319 MB structured disclosure APIs (28 types)
Each file is one company: {stockCode}.parquet
docs — Disclosure Text
Full-text sections from annual/quarterly reports, parsed into structured blocks.
| Column | Description |
|---|---|
rcept_no |
DART filing ID |
rcept_date |
Filing date |
stock_code |
Stock code |
corp_name |
Company name |
report_type |
Annual/quarterly report type |
section_title |
Original section title |
section_order |
Section ordering |
content |
Section text (markdown) |
blockType |
text / table / heading |
year |
Filing year |
finance — Financial Statements
XBRL-based financial data from DART OpenAPI (fnlttSinglAcntAll).
| 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 |
account_nm |
Account name (Korean) |
thstrm_amount |
Current period amount |
frmtrm_amount |
Prior period amount |
bfefrmtrm_amount |
Two periods prior amount |
report — Structured Disclosure APIs
28 DART API categories covering governance, compensation, shareholding, and more.
| Column | Description |
|---|---|
apiType |
API category (e.g., dividend, employee, executive) |
year |
Year |
quarter |
Quarter |
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 more.
Learn More
DartLab auto-downloads from this dataset — one stock code gives you the full company map. Start with the intro below.
- GitHub — github.com/eddmpython/dartlab
- Intro blog — DartLab 시작하기 / Getting started
- Docs — eddmpython.github.io/dartlab
- YouTube — @eddmpython
Data Source
- DART (Korea): dart.fss.or.kr — Korea's electronic disclosure system operated by the Financial Supervisory Service
- EDGAR (US): sec.gov/edgar — SEC's Electronic Data Gathering, Analysis, and Retrieval system
All data is sourced from public government disclosure systems. Financial figures are preserved as-is from the original filings — no rounding, no estimation, no interpolation.
Update Schedule
This dataset is updated automatically via GitHub Actions (daily). Recent filings (last 7 days) are checked and collected incrementally.
License
Apache 2.0 — same as DartLab.
Support
If DartLab is useful for your work, consider supporting the project:
- GitHub Issues — bug reports, feature requests
- Blog — 120+ articles on Korean disclosure analysis
- Downloads last month
- 7,754