Dragon Finance Corpus
Collection
A balanced corpus of public financial data across product classes. • 10 items • Updated
Dataset Preview
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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1539, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 131, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1419, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 976, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 794, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
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/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1401, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1579, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
csv unknown | __key__ string | __url__ string |
|---|---|---|
"REFURSxTS0VXCjAxLzAyLzE5OTAsMTI2LjA5MDAwMAowMS8wMy8xOTkwLDEyMy4zNDAwMDAKMDEvMDQvMTk5MCwxMjIuNjIwMDA(...TRUNCATED) | ./SKEW_History | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/cboe/v(...TRUNCATED) |
"REFURSxPUEVOLEhJR0gsTE9XLENMT1NFCjA5LzE4LzIwMDksMjUuOTEwMDAwLDI2LjY2MDAwMCwyNS45MTAwMDAsMjYuNTQwMDA(...TRUNCATED) | ./VIX3M_History | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/cboe/v(...TRUNCATED) |
"REFURSxPUEVOLEhJR0gsTE9XLENMT1NFCjAxLzAyLzIwMDgsMjQuMzYwMDAwLDI0LjM2MDAwMCwyNC4zNjAwMDAsMjQuMzYwMDA(...TRUNCATED) | ./VIX6M_History | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/cboe/v(...TRUNCATED) |
"REFURSxPUEVOLEhJR0gsTE9XLENMT1NFCjAxLzA0LzIwMTEsMTYuMDYwMDAwLDE2LjA2MDAwMCwxNi4wNjAwMDAsMTYuMDYwMDA(...TRUNCATED) | ./VIX9D_History | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/cboe/v(...TRUNCATED) |
"REFURSxPUEVOLEhJR0gsTE9XLENMT1NFCjAxLzAyLzE5OTAsMTcuMjQwMDAwLDE3LjI0MDAwMCwxNy4yNDAwMDAsMTcuMjQwMDA(...TRUNCATED) | ./VIX_History | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/cboe/v(...TRUNCATED) |
"REFURSxWVklYCjAzLzA2LzIwMDYsNzEuNzMwMDAwCjAzLzE1LzIwMDYsMTUuNzEwMDAwCjAzLzE2LzIwMDYsMjcuOTQwMDAwCjA(...TRUNCATED) | ./VVIX_History | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/cboe/v(...TRUNCATED) |
"REFURSxPUEVOLEhJR0gsTE9XLENMT1NFCjA5LzE2LzIwMDksMjguODkwMDAwLDI5LjMyMDAwMCwyOC42NjAwMDAsMjguODYwMDA(...TRUNCATED) | ./RVX_History | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/cboe/v(...TRUNCATED) |
"REFURSxPUEVOLEhJR0gsTE9XLENMT1NFCjA5LzE0LzIwMDksMjYuNDEwMDAwLDI2LjQ4MDAwMCwyNC44MTAwMDAsMjQuOTMwMDA(...TRUNCATED) | ./VXN_History | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/cboe/v(...TRUNCATED) |
null | rulebook_index | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/data/f(...TRUNCATED) |
null | open_interest_2026-10-12 | "hf://datasets/dragonlimited/Dragon-Finance-Equities@5c607c59ea019705f2c96e93a1f523136f5a00c4/data/n(...TRUNCATED) |
End of preview.
Dragon Finance — equities
Corporate disclosure for US public companies — annual, quarterly and current reports, proxies, registration statements and every attached exhibit.
Part of the Dragon Finance Corpus — US public financial data from federal and official sources only. Nothing licensed, paywalled or registration-only.
Coverage
| Issuers | 488 listed US companies and growing (crawl in progress) |
| Period | 1999–2026 |
| Filings | 10-K, 10-Q, 8-K, DEF 14A, S-1, 13F and /A amendments |
| Structured financials | SEC Financial Statement and Notes data sets, 2009–2026 |
| Also | insider transactions (Form 3/4/5), 13F holdings, MIDAS market structure, Reg A, full filing index, litigation releases, Federal Register |
Size
| metric | value |
|---|---|
| stored | 270.02 GB |
| shards | 181 |
Sources present
| source | jurisdiction | data | licence |
|---|---|---|---|
| Cboe | US | volatility indices | public |
| FINRA | US | rulebook | public |
| Nasdaq Trader | US | daily open-interest files | public |
| SEC EDGAR | US | filings + sidecars | US public record |
| SEC EDGAR complete submissions | US | full filing incl. exhibits | US public record |
| SEC FinStmt Data Sets | US | quarterly XBRL extracts | US public record |
| SEC XBRL companyfacts | US | machine-readable GAAP | US public record |
| Federal Register | US | financial rules and notices | US public record |
| SEC financial-statement-data-sets | US | SEC bulk data set | US public record |
| SEC financial-statement-notes-data-sets | US | SEC bulk data set | US public record |
| SEC insider-transactions-data-sets | US | SEC bulk data set | US public record |
| IRS | US | Statistics of Income / Form 990 | US public record |
| SEC market-structure-data-security-exchange | US | SEC bulk data set | US public record |
| SEC regulation-data-sets | US | SEC bulk data set | US public record |
| SEC | US | EDGAR full-index / log files | US public record |
| treasury | n/a | n/a | n/a |
What you can do with it
- Reconstruct an issuer's filing history
- Pull reported figures and footnotes from 10-K/10-Q
- Track insider transactions and institutional 13F holdings
- Screen disclosure across issuers and years
For engineers
Data is stored as tar shards (the hub caps a directory at 10,000 files and these tiers run to millions). Members keep their original names and relative paths.
import tarfile
with tarfile.open("0000.tar") as tf:
print(tf.getnames()[:5])
tf.extractall("out/")
| shard | size |
|---|---|
README.md |
3.2 KB |
cboe/volatility-indices/0000.tar |
1.46 MB |
cboe/volatility-indices/0001.tar |
450.6 KB |
data/finra/0000.tar |
92.2 KB |
data/nasdaq/0000.tar |
675.8 KB |
data/sec_edgar/0000.tar |
2.17 GB |
Showing 6 of 181 shards.
Every shard records its sha256 in the pipeline ledgers; shards are append-only, so a resumed run re-uploads only what changed. A shard with a failed member is never marked complete, so missed files are retried rather than dropped.
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