Datasets:

THULab
/

telangana_weather

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.

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Telangana Daily Weather 2023–2025 — TsFile

Daily weather observations for the state of Telangana, India, converted to Apache TsFile format from the original CSV dataset.

Original dataset: ron-the-code/Telangana_time_series_2023-2025
Upstream source: Open Data Telangana
Coverage: 2023-02-01 → 2025-01-31, daily granularity (731 distinct days)
Scale: 445,212 rows · 33 districts · 612 weather stations (District + Mandal pairs)

About the original dataset

The original dataset page describes it as:

The dataset was retrieved from Open Data Telangana, from February 1, 2023, to January 31, 2025 with daily granularity. The dataset contains various fields such as District, Mandal, Date, rainfall (in millimeters), minimum and maximum temperature (in Celsius), minimum and maximum wind speed, and humidity. It provides a District and Mandal wise distribution as well.

The source is a single CSV file (Telangana_combined_weather_data.csv), 445,212 rows × 10 columns. One row = one station's readings for one day. Each station has 611–731 daily rows (not every station spans the full 731 days).

Original columns:

Column	Meaning	dtype	min / mean / max
`District`	district name (33)	string	—
`Mandal`	sub-district name	string	—
`Date`	`DD-Mon-YY`, e.g. `01-Feb-23`	string	2023-02-01 .. 2025-01-31
`Rain (mm)`	rainfall	float	0 / 2.97 / 618.5
`Min Temp (°C)`	min temperature	float	0 / 21.73 / 35.3
`Max Temp (°C)`	max temperature	float	-1 / 34.14 / 47.2
`Min Humidity (%)`	min humidity	float	-1 / 48.13 / 99.9
`Max Humidity (%)`	max humidity	float	0 / 90.71 / 100
`Min Wind Speed (Kmph)`	min wind speed	float	0 / 0.22 / 28.8
`Max Wind Speed (Kmph)`	max wind speed	float	0 / 8.34 / 69.9

How it is stored in this TsFile

One table telangana_weather. Each weather station — identified by (District, Mandal) — is an independent time-series, ordered by time.

TsFile column	Category	Type	From	Notes
`Time`	TIME	INT64	`Date`	epoch milliseconds (UTC midnight)
`District`	TAG	STRING	`District`	station identity (device dimension)
`Mandal`	TAG	STRING	`Mandal`	station identity (device dimension)
`Rain_mm`	FIELD	FLOAT	`Rain (mm)`	mm
`Min_Temp_C`	FIELD	FLOAT	`Min Temp (°C)`	°C
`Max_Temp_C`	FIELD	FLOAT	`Max Temp (°C)`	°C
`Min_Humidity_pct`	FIELD	FLOAT	`Min Humidity (%)`	%
`Max_Humidity_pct`	FIELD	FLOAT	`Max Humidity (%)`	%
`Min_Wind_Speed_Kmph`	FIELD	FLOAT	`Min Wind Speed (Kmph)`	km/h
`Max_Wind_Speed_Kmph`	FIELD	FLOAT	`Max Wind Speed (Kmph)`	km/h

Modifications made during conversion

The following changes were applied. Everything is listed explicitly; no other transformation was performed.

Format: CSV → TsFile (single file telangana_weather.tsfile).
District + Mandal set as TAG columns (the device/series dimension). Together they identify a station, so the data is split into 612 independent per-station time-series with strictly increasing time. (Without tags, the 612 stations' readings for the same day would collide on one timestamp.)
Date → Time: the DD-Mon-YY string is parsed to INT64 epoch milliseconds (UTC midnight) to make it a real time axis.
Original Date string column is dropped. Its information is fully preserved in Time (lossless), so it is not stored as a separate field.
Measurement columns renamed to TsFile-safe identifiers (the source names contain spaces, parentheses, °, % which are not valid identifiers). Units are kept inside the new names, e.g. Min Temp (°C) → Min_Temp_C, Max Humidity (%) → Max_Humidity_pct.
Numeric precision: the 7 measurement columns are stored as single-precision FLOAT.
Values are NOT altered. All readings are copied verbatim. In particular, the source uses -1 as a sentinel in Max Temp and Min Humidity (likely "missing"); these -1 values are kept as-is, not converted to null.

Not changed / not dropped

Apart from the Date string column (item 4, losslessly folded into Time), no column or value is removed. The 2 tags and 7 measurements are all retained, and row count is preserved exactly.

Verification

Round-trip checked by reading the TsFile back with the TsFile Python SDK:

row count: TsFile read-back 445,212 == 445,212 staged Parquet ✓
District, Mandal reported as category=TAG; the 7 measurements as FIELD ✓
measurements stored as single-precision FLOAT ✓

License

The upstream HF dataset's dataset.yaml does not declare a concrete license (it contains a placeholder string). The underlying data originates from Open Data Telangana; please consult the original sources for terms before redistribution or commercial use.

Usage

from tsfile import TsFileReader
reader = TsFileReader("telangana_weather.tsfile")
schemas = reader.get_all_table_schemas()          # table: "telangana_weather"
cols = [c.get_column_name() for c in schemas["telangana_weather"].get_columns()]
# query field/tag columns; Time is added automatically by the reader

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Total file size:

8.63 MB