The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
IATA_CODE: string
AIRPORT: string
CITY: string
STATE: string
COUNTRY: string
LATITUDE: double
LONGITUDE: double
to
{'IATA_CODE': Value('string'), 'AIRLINE': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 220, in _generate_tables
yield Key(file_idx, batch_idx), self._cast_table(pa_table)
~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 156, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
IATA_CODE: string
AIRPORT: string
CITY: string
STATE: string
COUNTRY: string
LATITUDE: double
LONGITUDE: double
to
{'IATA_CODE': Value('string'), 'AIRLINE': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
US DOT Flight Delays — 2015 (Parquet Version)
This dataset contains 5,819,079 records of commercial flights in the United States during 2015.
It has been converted to Parquet for efficient analytics in Python, DuckDB, Ibis, Spark, and Polars.
Files included
- flights.parquet (main fact table)
- airlines.parquet (carrier info)
- airports.parquet (airport geolocation & metadata)
- cancellation_codes.parquet (mapping table)
Source
U.S. Department of Transportation — Bureau of Transportation Statistics
Public Domain (U.S. Government Work)
Original dataset: https://www.transtats.bts.gov/
Notes
- Original data downloaded from the U.S. DOT (via Maven Analytics frontend).
- This version is provided as a Parquet file for efficient loading in Python, DuckDB, Polars, and Ibis.
Schema
- 39 fields in flights.parquet
- Includes departure/arrival times, delays, distance, carrier, and airport identifiers
Recommended Usage
Python (Polars)
import polars as pl
flights = pl.read_parquet("flights.parquet")
airlines = pl.read_parquet("airlines.parquet")
airports = pl.read_parquet("airports.parquet")
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