Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
tsfile.exceptions.FileOpenError: 28:
The above exception was the direct cause of the following exception:
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/tsfile/tsfile.py", line 271, in _split_generators
scan = self._scan_metadata(all_files)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
with self._open_reader(file) as reader:
~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
return TsFileReader(file)
File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
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.
QQQ 1-Minute OHLCV (10 Years) — TsFile format
This repository is a conversion to TsFile format of the Hugging Face dataset
Maxim37/timeseries-1m-QQQ-10y.
- Original dataset: Maxim37/timeseries-1m-QQQ-10y
- Symbol: QQQ
- Granularity: 1-minute candlesticks (OHLCV)
- Time range: 2014-01-02 04:00 → 2024-01-10 19:59 (~1.8 million rows)
- License: the original dataset declares no license (this conversion follows suit and adds none).
- Original README: only field definitions (YAML frontmatter), no body description. The description below comes from inspecting the actual data.
Data content
1-minute market data for the single symbol QQQ, one candlestick per row:
| Column | Type | Meaning |
|---|---|---|
Timestamp |
string | candlestick timestamp (minute level, globally unique and strictly increasing) |
Open |
float64 | opening price |
High |
float64 | highest price |
Low |
float64 | lowest price |
Close |
float64 | closing price |
Volume |
int64 | traded volume |
~1.802 million rows, no missing values. Row distribution by year:
| Year | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| rows | 142k | 145k | 141k | 142k | 181k | 183k | 209k | 205k | 219k | 227k | 7k |
Some candlesticks contain anomalous extremes (e.g. some
Closevalues far from the norm); this conversion does no cleaning and keeps them verbatim.
Files
The original dataset has a single split (train), so the output is one TsFile: train.tsfile.
TsFile structure
- No TAG (device): the whole file is a single QQQ;
Timestampis already globally unique and strictly increasing, so there is no natural device/symbol dimension and all data columns are FIELD. - Time: parsed from the original
Timestamptext (2014-01-02 04:00:00, minute level) into INT64 milliseconds. - FIELD:
Open/High/Low/Close(DOUBLE),Volume(INT64).
What changed vs the original dataset
| Item | Original | This TsFile version | Notes |
|---|---|---|---|
| Format | Parquet (single split train) | TsFile (train.tsfile) |
one source file per TsFile |
Timestamp column |
string (2014-01-02 04:00:00) |
parsed into Time (INT64 ms) and the original text column dropped |
time info fully preserved; only the format changes from string to millisecond integer |
Open/High/Low/Close |
float64 | DOUBLE | values unchanged |
Volume |
int64 | INT64 | values unchanged |
| device dimension | none | none (no TAG) | single symbol, no device dimension needed |
| value cleaning | — | no cleaning | original anomalous extremes kept verbatim |
The only dropped column: the original Timestamp text column (its info is folded into Time). Apart from that, no columns are dropped and no values are modified.
Reading example
from tsfile import TsFileReader
reader = TsFileReader("train.tsfile")
for name, schema in reader.get_all_table_schemas().items():
print(name, [c.get_column_name() for c in schema.get_columns()])
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