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Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 16 new columns ({'gps_code', 'home_link', 'wikipedia_link', 'iata_code', 'name', 'scheduled_service', 'iso_country', 'local_code', 'latitude_deg', 'ident', 'elevation_ft', 'continent', 'keywords', 'iso_region', 'municipality', 'longitude_deg'}) and 4 missing columns ({'frequency_mhz', 'airport_ident', 'description', 'airport_ref'}).
This happened while the csv dataset builder was generating data using
hf://datasets/cjc0013/Ufo_data_clustered/source/airports.csv (at revision a9bd94bfd224fad09c4f2d34f65da802d3d7e399)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
id: int64
ident: string
type: string
name: string
latitude_deg: double
longitude_deg: double
elevation_ft: double
continent: string
iso_country: string
iso_region: string
municipality: string
scheduled_service: string
gps_code: string
iata_code: string
local_code: string
home_link: string
wikipedia_link: string
keywords: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2401
to
{'id': Value('int64'), 'airport_ref': Value('int64'), 'airport_ident': Value('string'), 'type': Value('string'), 'description': Value('string'), 'frequency_mhz': Value('float64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1455, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1054, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 16 new columns ({'gps_code', 'home_link', 'wikipedia_link', 'iata_code', 'name', 'scheduled_service', 'iso_country', 'local_code', 'latitude_deg', 'ident', 'elevation_ft', 'continent', 'keywords', 'iso_region', 'municipality', 'longitude_deg'}) and 4 missing columns ({'frequency_mhz', 'airport_ident', 'description', 'airport_ref'}).
This happened while the csv dataset builder was generating data using
hf://datasets/cjc0013/Ufo_data_clustered/source/airports.csv (at revision a9bd94bfd224fad09c4f2d34f65da802d3d7e399)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)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.
id
int64 | airport_ref
int64 | airport_ident
string | type
string | description
string | frequency_mhz
float64 |
|---|---|---|---|---|---|
70,518
| 6,528
|
00CA
|
CTAF
|
CTAF
| 122.9
|
307,581
| 6,589
|
01FL
|
ARCAL
| null | 122.9
|
75,239
| 6,589
|
01FL
|
CTAF
|
CEDAR KNOLL TRAFFIC
| 122.8
|
60,191
| 6,756
|
04CA
|
CTAF
|
CTAF
| 122.9
|
59,287
| 6,779
|
04MS
|
UNIC
|
UNICOM
| 122.8
|
60,682
| 6,784
|
04NV
|
UNIC
|
UNICOM
| 123
|
60,091
| 6,812
|
05CL
|
CTAF
|
CTAF
| 122.9
|
63,835
| 6,853
|
05UT
|
UNIC
|
UNICOM
| 122.8
|
70,676
| 6,868
|
06FA
|
APP
|
PALM BEACH APP
| 124.6
|
70,677
| 6,868
|
06FA
|
GND
|
GND
| 121.65
|
70,678
| 6,868
|
06FA
|
TWR
|
TWR
| 120.4
|
65,868
| 6,887
|
06MO
|
CTAF
|
CTAF
| 122.9
|
71,176
| 6,924
|
07FA
|
UNIC
|
UNICOM
| 122.7
|
66,637
| 6,943
|
07MT
|
CNTR
|
SALT LAKE CITY CNTR
| 126.85
|
69,383
| 6,954
|
07TE
|
CNTR
|
HOUSTON CNTR
| 126.625
|
61,673
| 7,008
|
08TE
|
UNIC
|
UNICOM
| 122.8
|
61,013
| 7,019
|
09CL
|
CTAF
|
CTAF
| 122.9
|
59,566
| 7,021
|
09FA
|
UNIC
|
UNICOM
| 122.8
|
68,176
| 7,054
|
09TS
|
CNTR
|
ALBUQUERQUE CNTR
| 132.65
|
59,735
| 7,094
|
0AZ2
|
UNIC
|
UNICOM
| 122.95
|
328,741
| 7,102
|
0C2
|
CTAF
| null | 122.9
|
62,825
| 7,116
|
0CA9
|
CTAF
|
CTAF
| 122.9
|
59,296
| 7,213
|
0ID2
|
ARTC
|
SALT LAKE CITY CNTR
| 128.35
|
60,367
| 7,542
|
0TE4
|
UNIC
|
CTAF/UNICOM
| 122.8
|
59,580
| 7,543
|
0TE5
|
CNTR
|
HOUSTON CNTR
| 126.625
|
59,437
| 7,545
|
0TE7
|
UNIC
|
UNICOM
| 122.8
|
67,677
| 7,569
|
0TX1
|
UNIC
|
UNICOM
| 123.05
|
59,357
| 7,712
|
11II
|
CNTR
|
INDIANAPOLIS CNTR
| 134.85
|
59,358
| 7,712
|
11II
|
CTAF
|
CTAF
| 126.2
|
59,360
| 7,712
|
11II
|
MISC
|
RNG CON
| 38.9
|
59,359
| 7,712
|
11II
|
MISC
|
ANG RNG CON
| 138.25
|
71,354
| 7,781
|
12NC
|
APP
|
CHERRY POINT APP
| 119.75
|
69,316
| 7,789
|
12OK
|
UNIC
|
UNICOM
| 123
|
70,478
| 7,838
|
13NC
|
APP
|
CHERRY POINT APP
| 119.35
|
333,203
| 7,838
|
13NC
|
CTAF
| null | 322.1
|
70,367
| 7,898
|
14NC
|
A/D
|
CHERRY POINT APP
| 119.35
|
66,604
| 7,917
|
14TS
|
CNTR
|
HOUSTON CNTR
| 126.625
|
59,174
| 7,928
|
15AR
|
UNIC
|
RDO CTL
| 122.725
|
68,311
| 7,934
|
15FL
|
UNIC
|
UNICOM
| 123
|
60,025
| 8,028
|
16X
|
CNTR
|
FORT WORTH CNTR
| 127.45
|
70,821
| 8,082
|
18AZ
|
UNIC
|
UNICOM
| 122.975
|
67,241
| 8,117
|
18TA
|
CNTR
|
HOUSTON CNTR
| 126.625
|
62,339
| 8,118
|
18TE
|
UNIC
|
UNICOM
| 122.8
|
61,636
| 8,205
|
1AZ0
|
UNIC
|
UNICOM
| 122.725
|
67,423
| 8,222
|
1CA1
|
CTAF
|
CTAF
| 122.9
|
59,235
| 8,233
|
1CD2
|
APP
|
DENVER APP
| 119.3
|
59,171
| 8,297
|
1GA0
|
UNIC
|
UNICOM
| 122.725
|
70,225
| 8,486
|
1MS8
|
APP
|
MERIDIAN APP
| 31.48
|
298,625
| 8,732
|
1WA6
|
CTAF
|
Fall City Traffic
| 122.9
|
59,128
| 8,769
|
1XS8
|
CNTR
|
HOUSTON CNTR
| 126.625
|
70,996
| 8,787
|
20GA
|
MULT
|
MULT
| 122.9
|
63,036
| 8,924
|
22XS
|
A/G
|
TWR
| 143.35
|
63,037
| 8,924
|
22XS
|
ATIS
|
ATIS
| 118.8
|
63,038
| 8,924
|
22XS
|
INFO
|
RNG CTL
| 30.45
|
63,039
| 8,924
|
22XS
|
MISC
|
FORT HOOD FLT FLW
| 38.75
|
63,040
| 8,924
|
22XS
|
OPS
|
GRAY OPS
| 38.7
|
63,041
| 8,924
|
22XS
|
PMSV
|
PMSV GRAY METRO
| 41.2
|
63,042
| 8,924
|
22XS
|
TWR
|
GRAY TWR
| 120.75
|
60,377
| 8,982
|
23XS
|
A/G
|
LONGHORN AUX TWR
| 143.35
|
60,378
| 8,982
|
23XS
|
ATIS
|
ATIS
| 118.8
|
60,379
| 8,982
|
23XS
|
INFO
|
RNG CTL
| 30.45
|
60,380
| 8,982
|
23XS
|
MISC
|
FORT HOOD FLT FLW
| 38.75
|
60,381
| 8,982
|
23XS
|
OPS
|
GRAY OPS
| 38.7
|
60,382
| 8,982
|
23XS
|
PMSV
|
PMSV GRAY METRO
| 41.2
|
60,383
| 8,982
|
23XS
|
TWR
|
GRAY TWR
| 120.75
|
67,720
| 8,990
|
24CL
|
CTAF
|
CTAF
| 122.9
|
60,694
| 9,068
|
25NC
|
MULT
|
MULTICOM
| 122.9
|
60,360
| 9,078
|
25TA
|
CNTR
|
HOUSTON CNTR
| 126.625
|
64,363
| 9,080
|
25TS
|
CNTR
|
ALBUQUERQUE CNTR
| 132.65
|
61,802
| 9,138
|
27AZ
|
CTAF
|
CTAF
| 122.9
|
59,707
| 9,191
|
28CL
|
CTAF
|
CTAF
| 122.8
|
63,365
| 9,223
|
28TA
|
CNTR
|
HOUSTON CNTR
| 126.625
|
63,366
| 9,223
|
28TA
|
UNIC
|
UNICOM
| 122.8
|
69,599
| 9,236
|
29AZ
|
UNIC
|
UNICOM
| 122.8
|
64,791
| 9,277
|
29TX
|
CNTR
|
FORT WORTH CNTR
| 127.45
|
62,214
| 9,354
|
2CL9
|
CTAF
|
CTAF
| 122.9
|
71,454
| 14,060
|
2CN4
|
CTAF
|
CTAF
| 122.9
|
333,743
| 9,368
|
2D7
|
APP/DEP
|
CLEVELAND APP/DEP
| 125.5
|
333,742
| 9,368
|
2D7
|
CTAF
|
CTAF/UNICOM
| 122.8
|
62,263
| 20,770
|
2IG4
|
UNIC
|
UNICOM
| 122.8
|
60,042
| 9,696
|
2OR1
|
UNIC
|
UNICOM
| 122.8
|
67,219
| 9,772
|
2TA6
|
CNTR
|
FORT WORTH CNTR
| 127.45
|
63,137
| 9,774
|
2TA8
|
CNTR
|
HOUSTON CNTR
| 126.625
|
71,475
| 9,784
|
2TE8
|
CNTR
|
HOUSTON CNTR
| 126.625
|
70,329
| 9,809
|
2TX3
|
CNTR
|
HOUSTON CNTR
| 126.625
|
60,402
| 9,810
|
2TX4
|
CNTR
|
HOUSTON CNTR
| 126.625
|
69,995
| 9,835
|
2VG2
|
UNIC
|
UNICOM
| 122.725
|
60,635
| 9,880
|
2XA0
|
CNTR
|
FORT WORTH CNTR
| 127.45
|
60,636
| 9,880
|
2XA0
|
CTAF
|
CTAF
| 122.9
|
70,047
| 9,891
|
2XS3
|
CNTR
|
FORT WORTH CNTR
| 127.45
|
67,073
| 9,893
|
2XS5
|
CNTR
|
HOUSTON CNTR
| 126.625
|
61,432
| 9,985
|
31VA
|
UNIC
|
UNICOM
| 122.75
|
68,592
| 10,080
|
34AZ
|
UNIC
|
UNICOM
| 122.8
|
67,703
| 10,175
|
36CA
|
CTAF
|
CTAF
| 122.9
|
71,005
| 10,177
|
36CN
|
CTAF
|
CTAF
| 122.9
|
61,623
| 10,214
|
36WI
|
CTAF
|
CTAF
| 122.9
|
61,624
| 10,214
|
36WI
|
MISC
|
LIGHT
| 122.6
|
71,572
| 10,265
|
38AZ
|
AWOS
|
AWOS 2
| 119.225
|
71,573
| 10,265
|
38AZ
|
CTAF
|
CTAF
| 122.8
|
58,969
| 10,268
|
38CA
|
UNIC
|
UNICOM
| 122.8
|
UFO Sightings β Cleaned & Unified Dataset (~327k rows)
This dataset merges several publicly available UFO sighting datasets from Kaggle into one cleaned, standardized, and enriched file. The goal is simply to provide a consolidated dataset instead of many fragmented sources with inconsistent formatting.
This release contains a single JSONL file with approximately 327,000 records.
No private or identifying information was present in the original data.
π¦ Source
All entries originate from publicly available UFO sighting datasets on Kaggle. Each row corresponds to a single reported sighting. Source Files located in source folder
π§Ή Cleaning / Normalization Performed
All rows in this unified file were standardized using the same basic rules:
- timestamps parsed and converted into a consistent
t_utc(ISO-8601, UTC) - city/state/country fields harmonized where possible
- latitude/longitude coerced to floats
- basic HTML/unicode cleanup in free-text descriptions (
text) - invalid or fully unparseable rows removed
- source field preserved as
src
No interpretation or filtering based on content was performed.
β¨ Added Contextual Fields
A small number of lightweight βsidecarβ fields were added based on timestamp + coordinates:
moon_illumβ moon illumination fractionmoon_alt_degβ moon altitude in degreesnearest_airport_codeβ closest airport (ICAO)nearest_airport_kmβ distance to that airport in kmwx_bucketβ rough weather bucket (coarse category)
These values are approximate and should be treated as exploratory metadata only.
π§© Clustering Fields (Included in the File)
The dataset includes two fields that come from text-similarity grouping:
cluster_idβ numeric labelprobβ membership confidence
These reflect text similarity, not verified categories or event types. They are included because they were already part of the cleaned file.
π Field Reference
Each row has the following structure (example):
{
"uid": "scrubbed/row327047",
"t_utc": "2013-09-09T09:51:00.000Z",
"lat": 32.7152778,
"lon": -117.1563889,
"text": "2 white lights zig-zag over Qualcomm Stadium...",
"src": "scrubbed",
"city": "san diego",
"state": "ca",
"country": "US",
"cluster_id": 725,
"prob": 1.0,
"moon_illum": 0.163603127,
"moon_alt_deg": -67.0003509521,
"nearest_airport_km": 3.7174715996,
"nearest_airport_code": "KSAN",
"reports_z": null,
"wx_bucket": "unknown"
}
Field descriptions
| Field | Type | Notes |
|---|---|---|
uid |
string | Stable row identifier |
t_utc |
string | Event timestamp, ISO-8601 UTC |
lat, lon |
float | Approximate coordinates |
city, state, country |
string | Cleaned location fields (best-effort) |
text |
string | Free-text sighting description |
src |
string | Original Kaggle dataset source |
cluster_id |
int | Text-similarity cluster (for research use only) |
prob |
float | Cluster membership probability |
moon_illum |
float | Moon illumination (0β1) |
moon_alt_deg |
float | Moon altitude in degrees |
nearest_airport_km |
float | Distance to nearest airport |
nearest_airport_code |
string | ICAO code |
wx_bucket |
string | Approximate weather category |
reports_z |
float/null | Unused placeholder field (kept for completeness) |
β οΈ Notes & Limitations
- Accuracy of timestamps and locations depends entirely on original reporting.
- Weather buckets are coarse (not NOAA-grade).
- Airport distances are approximate nearest-neighbor lookups.
- Cluster labels are based solely on text similarity and do not reflect event reality.
- No claims are made about the nature or validity of any sighting.
π License
Source data was public on Kaggle. This cleaned, merged, and lightly enriched version is released for research and educational use. Users should follow the original dataset licensing terms.
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