Datasets:

THULab
/

indian_domestic_airline_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.

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Indian Domestic Airline Flights 2018-2025 (TsFile)

Apache TsFile version of Gokul99400/IndianDomesticAirlineDataset.

Overview

Indian domestic airline schedule records covering 2018-2025 across ~100 airports: airline, flight number, route, operating days of week, scheduled departure/arrival times and the schedule validity window (validFrom..validTo). The repo ships two CSVs: Air-Clean.csv (33,734 deduplicated rows) and Air_full-Raw.csv (113,339 rows, incl. duplicates); both are converted into separate TsFiles so no data is dropped. Typical uses: flight schedule analysis, route popularity, seasonal trends.

Clean file: 33,734 rows, 14 airlines, 5,975 flight numbers.
Full raw file: 113,339 rows, 14 airlines, 9,177 flight numbers.
Validity period: 2018-10-28 .. 2025-10-25.
Note: the source column timezone always equals validTo (it stores the schedule-season end date); both columns are kept unchanged.
Within each file, identical duplicate schedule rows (e.g. 3,427 in the raw file) are kept and disambiguated by the seq TAG (stable source row order) instead of being dropped.

Schema (TsFile structure)

Time (INT64, milliseconds) — validFrom, the day the schedule period starts (naive).
airline, flightNumber, origin, destination, daysOfWeek, scheduledDepartureTime, scheduledArrivalTime, seq (TAG, STRING) — the flight schedule identity; scheduledArrivalTime is empty in the raw file where the source left it blank.
timezone, validTo, lastUpdated (FIELD, STRING) — validity window end and metadata dates.

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("indian_domestic_airline_dataset_clean.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())

Source & license

Original dataset: https://huggingface.co/datasets/Gokul99400/IndianDomesticAirlineDataset
License: not declared by the original dataset (card shows unknown); please defer to the original.

Downloads last month: 30

Total file size:

85.8 MB