Datasets:
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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.
Air Quality & Meteorology (TsFile format)
Original dataset: https://huggingface.co/datasets/neuralsorcerer/air-quality
This dataset is a conversion to TsFile format of the Hugging Face dataset neuralsorcerer/air-quality, with data content identical to the original.
- Original dataset: neuralsorcerer/air-quality (DOI: 10.57967/hf/5729)
- Original author: neuralsorcerer (Hugging Face)
- License: cc0-1.0 (public domain)
Conversion Notes
- The original dataset is a single CSV (
air_quality.csv) from a single station (Kolkata); the conversion outputs one TsFile (train.tsfile), neither merged nor split. - No TAG: single station, single series;
datetimeis globally unique and strictly monotonic (constant 1-hour interval), so there is no natural device dimension and all columns are FIELD. - The original
datetime(IST / UTC+5:30 local time, no timezone suffix in the CSV) is parsed at its local wall-clock literal value into the TsFileTimecolumn (INT64, millisecond precision) with no timezone offset; read-back times match the original CSV exactly. - All 10 variables are kept as DOUBLE.
- No columns or rows dropped (all 87,672 rows retained).
Air Quality & Meteorology Dataset
The following is the original dataset description, kept verbatim.
Dataset Description
This corpus contains 87,672 hourly records (10 variables + timestamp) that realistically emulate air-quality and local-weather conditions for Kolkata, West Bengal, India. Patterns, trends and extreme events (Diwali fireworks, COVID-19 lockdown, cyclones, heat-waves) are calibrated to published CPCB, IMD and peer-reviewed summaries, making the data suitable for benchmarking, forecasting, policy-impact simulations and educational research.
The data are suitable for time-series forecasting, machine learning, environmental research, and air-quality policy simulation while containing no real personal or proprietary information.
File Information
| File | Records | Approx. Size |
|---|---|---|
air_quality.csv (original) / train.tsfile (converted) |
87,672 (hourly) | ~16 MB |
(Rows = 10 years × 365 days (+ leap) × 24 h ≈ 87.7 k)
Columns & Descriptions
| Column | Unit / Range | Description |
|---|---|---|
datetime |
ISO 8601 (IST) | Hour start timestamp (UTC + 05:30). In TsFile it becomes the Time column (INT64 milliseconds). |
pm25 |
µg m⁻³ (15–600) | Particulate Matter < 2.5 µm. |
pm10 |
µg m⁻³ (30–900) | Particulate Matter < 10 µm. |
no2 |
µg m⁻³ (5–80) | Nitrogen dioxide, traffic proxy. |
co |
mg m⁻³ (0.05–4) | Carbon monoxide. |
so2 |
µg m⁻³ (1–20) | Sulphur dioxide. |
o3 |
µg m⁻³ (5–120) | Surface ozone. |
temp |
°C (12–45) | Dry-bulb air temperature. |
rh |
% (20–100) | Relative humidity. |
wind |
m s⁻¹ (0.1–30) | 10 m wind speed. |
rain |
mm h⁻¹ (0–150) | Hourly precipitation. |
In TsFile,
datetimeis theTimecolumn (INT64 milliseconds) and the remaining 10 columns are FIELD (DOUBLE).
Intended Use Cases
- Environmental Research — seasonal/diurnal pollution dynamics, meteorological drivers
- Machine-Learning Benchmarks — forecasting, anomaly-detection, imputation
- Policy / "What-If" Simulation
- Extreme-Event Studies — Diwali spikes, cyclone wash-outs, heat-wave ozone episodes
- Teaching & Exploration
License
This dataset is released under the CC0-1.0 License (public domain).
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