Datasets:
Tasks:
Time Series Forecasting
Modalities:
Time-series
Sub-tasks:
univariate-time-series-forecasting
Languages:
English
Size:
n<1K
License:
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.
Fitbit Sleep Score Data (TsFile format)
The Fitbit Sleep Score dataset contains timestamped sleep metrics collected from one consenting individual's Fitbit Versa 4 device. It is a case study for sleep analysis, health monitoring, and wellness technology rather than a population-level cohort.
Modalities: Time-series
Source and scale
- Original dataset: aai530-group6/sleep-score-fitbit
- Kaggle source named by the original card: Fitbit Sleep Score Data
- Source revision: b99745afef52c32b608edba1acf25f3e0f6089c4
- One train file with 291 observations, one timestamp per sleep record.
- Source time range: 2022-12-23T09:20:30Z through 2023-11-18T07:59:00Z.
TsFile schema
| Column | Role | TsFile type | Source meaning |
|---|---|---|---|
| Time | TIME | INT64 (ms) | timestamp, parsed as UTC |
| overall_score | FIELD | INT64 | Aggregate sleep score (up to 100) |
| revitalization_score | FIELD | INT64 | Rejuvenating quality score |
| deep_sleep_in_minutes | FIELD | INT64 | Deep sleep duration in minutes |
| resting_heart_rate | FIELD | INT64 | Average resting heart rate |
| restlessness | FIELD | DOUBLE | Restlessness measure |
There are no device TAG columns because the source contains one individual's single series.
Conversion notes
- ISO-8601 timestamps are interpreted in UTC and represented losslessly as integer milliseconds in Time; the original timestamp text is not duplicated as a FIELD.
- All five measurements and all 291 rows are retained and sorted by Time.
- No demographic or additional subject information is inferred from the source.
Files and usage
- sleep_score_fitbit.tsfile
from pathlib import Path
from tsfile import TsFileReader
path = Path("sleep_score_fitbit.tsfile")
with TsFileReader(str(path)) as reader:
table_name = next(iter(reader.get_all_table_schemas()))
with reader.query_table(table_name, ["overall_score", "restlessness"], batch_size=512) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
License and attribution
The source dataset is released under the MIT license. Please respect the source card's privacy and ethical-use notes for this single-person case study. See the original dataset card.
Usage
Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:
from pathlib import Path
from tsfile import TsFileReader
path = Path("sleep_score_fitbit.tsfile")
with TsFileReader(str(path)) as reader:
schemas = reader.get_all_table_schemas()
print("tables:", list(schemas))
table_name = next(iter(schemas))
table = schemas[table_name]
columns = [column.get_column_name() for column in table.get_columns()]
print("columns:", columns)
field_names = [
column.get_column_name()
for column in table.get_columns()
if column.get_column_name() not in {"Time", "time"}
]
if field_names:
with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
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