Datasets:

smilegeng
/

air-quality

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
                  scan = self._scan_metadata(all_files)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 304, in _scan_metadata
                  from tsfile.constants import TIME_COLUMN, ColumnCategory
              ModuleNotFoundError: No module named 'tsfile'
              
              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 66, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/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 格式)

原数据集链接：https://huggingface.co/datasets/neuralsorcerer/air-quality

本数据集由 HuggingFace 数据集 neuralsorcerer/air-quality 转换为 TsFile 格式，数据内容与原数据集完全一致。

原始数据集：neuralsorcerer/air-quality（DOI: 10.57967/hf/5729）
原作者：neuralsorcerer (HuggingFace)
许可证：cc0-1.0（公共领域）

转换说明

原数据集是单个 CSV（air_quality.csv），单一站点（加尔各答），转换后输出一个 TsFile（train.tsfile），不合并、不拆分。
不设 TAG：单一站点、单一序列，datetime 全局唯一且严格单调递增（间隔恒为 1 小时），没有天然的 device 维度，所有列均为 FIELD。
原始 datetime（IST / UTC+5:30 本地时间，CSV 不带时区后缀）按本地壁钟字面值解析为 TsFile 的 Time 列（INT64，毫秒精度），不做时区偏移，读回时间与原 CSV 完全一致。
10 个变量全部以 DOUBLE 保留。
不丢弃任何列、任何行（87672 行全部保留）。

Air Quality & Meteorology Dataset

以下为原数据集介绍，内容保持一致。

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`（原始）/ `train.tsfile`（转换后）	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)。在 TsFile 中作为 Time 列（INT64 毫秒）。
`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.

在 TsFile 中，datetime 作为 Time 列（INT64 毫秒），其余 10 列作为 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).

Downloads last month: 44

Total file size:

6.13 MB