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The dataset generation failed because of a cast error
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 3 new columns ({'VIS', 'TIDE', 'DEWP'}) and 1 missing columns ({'TSTMP'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Qdrant/NOAA-Buoy/orig_downloads/2023/csv/42002_Apr.csv (at revision 719a1bbbcd79abe70fffcaaf280aedc717e8ae2b)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://huggingface.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
#YY: string
MM: string
DD: string
hh: string
mm: string
WDIR: string
WSPD: string
GST: string
WVHT: string
DPD: string
APD: string
MWD: string
PRES: string
ATMP: string
WTMP: string
DEWP: string
VIS: string
TIDE: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2178
to
{'TSTMP': Value(dtype='string', id=None), '#YY': Value(dtype='int64', id=None), 'MM': Value(dtype='int64', id=None), 'DD': Value(dtype='int64', id=None), 'hh': Value(dtype='int64', id=None), 'mm': Value(dtype='int64', id=None), 'WDIR': Value(dtype='int64', id=None), 'WSPD': Value(dtype='float64', id=None), 'GST': Value(dtype='float64', id=None), 'WVHT': Value(dtype='float64', id=None), 'DPD': Value(dtype='float64', id=None), 'APD': Value(dtype='float64', id=None), 'MWD': Value(dtype='float64', id=None), 'PRES': Value(dtype='float64', id=None), 'ATMP': Value(dtype='float64', id=None), 'WTMP': Value(dtype='float64', id=None)}
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 1321, 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 935, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, 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 3 new columns ({'VIS', 'TIDE', 'DEWP'}) and 1 missing columns ({'TSTMP'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Qdrant/NOAA-Buoy/orig_downloads/2023/csv/42002_Apr.csv (at revision 719a1bbbcd79abe70fffcaaf280aedc717e8ae2b)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://huggingface.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.
TSTMP
string | #YY
int64 | MM
int64 | DD
int64 | hh
int64 | mm
int64 | WDIR
int64 | WSPD
float64 | GST
float64 | WVHT
float64 | DPD
float64 | APD
float64 | MWD
float64 | PRES
float64 | ATMP
float64 | WTMP
float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2023-04-01 00:10:00-05:00
| 2,023
| 4
| 1
| 0
| 10
| 149
| 6.9
| 9.3
| 1.89
| 7.69
| 5.72
| 108
| 1,014.3
| 25.1
| 24.9
|
2023-04-01 00:40:00-05:00
| 2,023
| 4
| 1
| 0
| 40
| 148
| 7
| 9.5
| 1.94
| 7.69
| 5.88
| 120
| 1,014.5
| 25.1
| 24.8
|
2023-04-01 01:10:00-05:00
| 2,023
| 4
| 1
| 1
| 10
| 150
| 7.4
| 9.4
| 1.92
| 7.69
| 5.92
| 122
| 1,014.8
| 25
| 24.9
|
2023-04-01 01:40:00-05:00
| 2,023
| 4
| 1
| 1
| 40
| 152
| 6.5
| 8.2
| 2.12
| 7.14
| 6
| 130
| 1,015.3
| 25
| 24.8
|
2023-04-01 02:10:00-05:00
| 2,023
| 4
| 1
| 2
| 10
| 150
| 7.4
| 9.1
| 2.13
| 7.69
| 6.1
| 126
| 1,015.6
| 25.1
| 24.9
|
2023-04-01 02:40:00-05:00
| 2,023
| 4
| 1
| 2
| 40
| 144
| 7
| 8.6
| 1.9
| 7.14
| 5.91
| 133
| 1,016
| 25
| 24.8
|
2023-04-01 03:10:00-05:00
| 2,023
| 4
| 1
| 3
| 10
| 146
| 7.2
| 9.4
| 1.93
| 7.69
| 6.01
| 138
| 1,016.1
| 25.1
| 24.9
|
2023-04-01 03:40:00-05:00
| 2,023
| 4
| 1
| 3
| 40
| 147
| 6.4
| 8.1
| 1.94
| 7.69
| 5.96
| 129
| 1,016.4
| 25
| 24.9
|
2023-04-01 04:10:00-05:00
| 2,023
| 4
| 1
| 4
| 10
| 148
| 6.4
| 8.2
| 1.82
| 7.69
| 5.87
| 120
| 1,016.3
| 24.9
| 24.9
|
2023-04-01 04:40:00-05:00
| 2,023
| 4
| 1
| 4
| 40
| 146
| 5.8
| 7.3
| 1.97
| 7.69
| 6.06
| 140
| 1,016.4
| 24.9
| 24.9
|
2023-04-01 05:10:00-05:00
| 2,023
| 4
| 1
| 5
| 10
| 148
| 5.2
| 7.1
| 1.76
| 7.69
| 5.94
| 133
| 1,016.6
| 24.9
| 24.9
|
2023-04-01 05:40:00-05:00
| 2,023
| 4
| 1
| 5
| 40
| 147
| 5
| 6.6
| 1.88
| 7.69
| 5.99
| 131
| 1,016.5
| 24.9
| 24.9
|
2023-04-01 06:10:00-05:00
| 2,023
| 4
| 1
| 6
| 10
| 147
| 4.4
| 5.8
| 1.72
| 7.69
| 5.93
| 141
| 1,016.5
| 24.9
| 24.9
|
2023-04-01 06:40:00-05:00
| 2,023
| 4
| 1
| 6
| 40
| 142
| 4.1
| 5.5
| 1.71
| 7.69
| 5.84
| 125
| 1,016.4
| 24.8
| 24.9
|
2023-04-01 07:10:00-05:00
| 2,023
| 4
| 1
| 7
| 10
| 136
| 3.8
| 5
| 1.51
| 7.69
| 5.71
| 136
| 1,016.1
| 24.8
| 24.9
|
2023-04-01 07:40:00-05:00
| 2,023
| 4
| 1
| 7
| 40
| 137
| 4.2
| 6
| 1.66
| 7.69
| 5.84
| 129
| 1,015.9
| 24.8
| 24.9
|
2023-04-01 08:10:00-05:00
| 2,023
| 4
| 1
| 8
| 10
| 133
| 3.3
| 4.9
| 1.43
| 7.69
| 5.75
| 115
| 1,016.1
| 24.8
| 24.9
|
2023-04-01 08:40:00-05:00
| 2,023
| 4
| 1
| 8
| 40
| 132
| 3
| 4.3
| 1.52
| 7.69
| 5.62
| 120
| 1,015.8
| 24.8
| 24.9
|
2023-04-01 09:10:00-05:00
| 2,023
| 4
| 1
| 9
| 10
| 125
| 3.1
| 4.6
| 1.6
| 7.14
| 5.86
| 138
| 1,015.8
| 24.7
| 24.9
|
2023-04-01 09:40:00-05:00
| 2,023
| 4
| 1
| 9
| 40
| 118
| 2.9
| 4.3
| 1.5
| 7.69
| 5.74
| 116
| 1,015.6
| 24.7
| 24.8
|
2023-04-01 10:10:00-05:00
| 2,023
| 4
| 1
| 10
| 10
| 99
| 2.3
| 3.2
| 1.34
| 7.69
| 5.59
| 111
| 1,016
| 24.7
| 24.8
|
2023-04-01 10:40:00-05:00
| 2,023
| 4
| 1
| 10
| 40
| 104
| 2.8
| 3.7
| 1.37
| 7.14
| 5.58
| 125
| 1,016
| 24.7
| 24.8
|
2023-04-01 11:10:00-05:00
| 2,023
| 4
| 1
| 11
| 10
| 108
| 3.4
| 4.6
| 1.39
| 7.14
| 5.66
| 128
| 1,016.1
| 24.7
| 24.8
|
2023-04-01 11:40:00-05:00
| 2,023
| 4
| 1
| 11
| 40
| 117
| 4.4
| 5.7
| 1.44
| 7.14
| 5.66
| 127
| 1,016.2
| 24.8
| 24.8
|
2023-04-01 12:10:00-05:00
| 2,023
| 4
| 1
| 12
| 10
| 104
| 3.7
| 4.6
| 1.28
| 7.69
| 5.56
| 95
| 1,016.8
| 24.8
| 24.8
|
2023-04-01 12:40:00-05:00
| 2,023
| 4
| 1
| 12
| 40
| 72
| 3.1
| 4
| 1.34
| 7.14
| 5.55
| 115
| 1,017.2
| 24.8
| 24.8
|
2023-04-01 13:10:00-05:00
| 2,023
| 4
| 1
| 13
| 10
| 84
| 3.4
| 4.5
| 1.35
| 6.67
| 5.63
| 133
| 1,017.4
| 24.9
| 24.8
|
2023-04-01 13:40:00-05:00
| 2,023
| 4
| 1
| 13
| 40
| 98
| 3.5
| 4.5
| 1.28
| 6.67
| 5.54
| 106
| 1,017.7
| 24.9
| 24.9
|
2023-04-01 14:10:00-05:00
| 2,023
| 4
| 1
| 14
| 10
| 84
| 3.7
| 4.9
| 1.48
| 7.14
| 5.88
| 114
| 1,018
| 25.2
| 24.9
|
2023-04-01 14:40:00-05:00
| 2,023
| 4
| 1
| 14
| 40
| 78
| 3.7
| 5
| 1.41
| 7.14
| 5.78
| 117
| 1,018.3
| 25.2
| 24.9
|
2023-04-01 15:10:00-05:00
| 2,023
| 4
| 1
| 15
| 10
| 90
| 3.9
| 4.8
| 1.23
| 6.25
| 5.59
| 126
| 1,018.6
| 25.2
| 24.9
|
2023-04-01 15:40:00-05:00
| 2,023
| 4
| 1
| 15
| 40
| 86
| 3.7
| 4.8
| 1.21
| 6.67
| 5.33
| 102
| 1,018.8
| 25.3
| 24.9
|
2023-04-01 16:10:00-05:00
| 2,023
| 4
| 1
| 16
| 10
| 91
| 4.1
| 5
| 1.21
| 7.14
| 5.49
| 114
| 1,018.9
| 25.3
| 25
|
2023-04-01 16:40:00-05:00
| 2,023
| 4
| 1
| 16
| 40
| 93
| 4.4
| 5.4
| 1.16
| 6.67
| 5.27
| 133
| 1,019
| 25.4
| 25.1
|
2023-04-01 17:10:00-05:00
| 2,023
| 4
| 1
| 17
| 10
| 99
| 4
| 5.1
| 1.23
| 6.67
| 5.53
| 126
| 1,019
| 25.4
| 25.1
|
2023-04-01 17:40:00-05:00
| 2,023
| 4
| 1
| 17
| 40
| 108
| 4.2
| 5.3
| 1.25
| 7.14
| 5.44
| 102
| 1,018.6
| 25.5
| 25.2
|
2023-04-01 18:10:00-05:00
| 2,023
| 4
| 1
| 18
| 10
| 122
| 4.8
| 6
| 1.35
| 6.67
| 5.64
| 110
| 1,018.4
| 25.6
| 25.2
|
2023-04-01 18:40:00-05:00
| 2,023
| 4
| 1
| 18
| 40
| 124
| 4.7
| 6.1
| 1.31
| 6.67
| 5.57
| 125
| 1,017.9
| 25.7
| 25.2
|
2023-04-01 19:10:00-05:00
| 2,023
| 4
| 1
| 19
| 10
| 129
| 4.8
| 6
| 1.27
| 6.67
| 5.52
| 120
| 1,017.4
| 25.7
| 25.3
|
2023-04-01 19:40:00-05:00
| 2,023
| 4
| 1
| 19
| 40
| 135
| 5.4
| 6.9
| 1.24
| 6.25
| 5.55
| 126
| 1,017.1
| 25.7
| 25.3
|
2023-04-01 20:10:00-05:00
| 2,023
| 4
| 1
| 20
| 10
| 141
| 5.3
| 7.1
| 1.38
| 6.25
| 5.7
| 138
| 1,016.7
| 25.7
| 25.3
|
2023-04-01 20:40:00-05:00
| 2,023
| 4
| 1
| 20
| 40
| 147
| 5.6
| 6.9
| 1.42
| 6.67
| 5.74
| 136
| 1,016.3
| 25.8
| 25.3
|
2023-04-01 21:10:00-05:00
| 2,023
| 4
| 1
| 21
| 10
| 148
| 5.7
| 7
| 1.31
| 6.67
| 5.52
| 133
| 1,016.1
| 25.7
| 25.3
|
2023-04-01 21:40:00-05:00
| 2,023
| 4
| 1
| 21
| 40
| 147
| 4.3
| 6.2
| 1.37
| 6.67
| 5.6
| 148
| 1,016.1
| 25.7
| 25.3
|
2023-04-01 22:10:00-05:00
| 2,023
| 4
| 1
| 22
| 10
| 150
| 4.2
| 5.4
| 1.38
| 7.69
| 5.69
| 121
| 1,016.1
| 25.8
| 25.4
|
2023-04-01 22:40:00-05:00
| 2,023
| 4
| 1
| 22
| 40
| 137
| 3
| 4.1
| 1.4
| 6.67
| 5.68
| 142
| 1,016.1
| 25.8
| 25.4
|
2023-04-01 23:10:00-05:00
| 2,023
| 4
| 1
| 23
| 10
| 135
| 3.1
| 4.1
| 1.2
| 6.67
| 5.52
| 145
| 1,016.3
| 25.7
| 25.4
|
2023-04-01 23:40:00-05:00
| 2,023
| 4
| 1
| 23
| 40
| 131
| 2.8
| 3.7
| 1.35
| 6.25
| 5.74
| 143
| 1,016.4
| 25.7
| 25.4
|
2023-04-02 00:10:00-05:00
| 2,023
| 4
| 2
| 0
| 10
| 121
| 2.8
| 4.1
| 1.34
| 7.14
| 5.62
| 153
| 1,016.4
| 25.5
| 25.3
|
2023-04-02 00:40:00-05:00
| 2,023
| 4
| 2
| 0
| 40
| 115
| 2.6
| 3.7
| 1.26
| 7.14
| 5.62
| 163
| 1,016.6
| 25.4
| 25.3
|
2023-04-02 01:10:00-05:00
| 2,023
| 4
| 2
| 1
| 10
| 125
| 3.2
| 4
| 1.34
| 6.67
| 5.58
| 139
| 1,016.8
| 25.3
| 25.3
|
2023-04-02 01:40:00-05:00
| 2,023
| 4
| 2
| 1
| 40
| 133
| 3.7
| 5
| 1.28
| 6.67
| 5.46
| 139
| 1,016.9
| 25.2
| 25.3
|
2023-04-02 02:10:00-05:00
| 2,023
| 4
| 2
| 2
| 10
| 133
| 3.7
| 4.6
| 1.3
| 6.67
| 5.63
| 147
| 1,017.2
| 25.2
| 25.2
|
2023-04-02 02:40:00-05:00
| 2,023
| 4
| 2
| 2
| 40
| 129
| 3.7
| 4.7
| 1.14
| 6.67
| 5.29
| 151
| 1,017.5
| 25.2
| 25.2
|
2023-04-02 03:10:00-05:00
| 2,023
| 4
| 2
| 3
| 10
| 126
| 3.5
| 4.4
| 1.17
| 6.67
| 5.41
| 158
| 1,017.8
| 25.1
| 25.2
|
2023-04-02 03:40:00-05:00
| 2,023
| 4
| 2
| 3
| 40
| 123
| 3.4
| 4.2
| 1.13
| 6.67
| 5.34
| 161
| 1,018.1
| 25.1
| 25.2
|
2023-04-02 04:10:00-05:00
| 2,023
| 4
| 2
| 4
| 10
| 132
| 3.3
| 4.3
| 1.16
| 6.25
| 5.41
| 129
| 1,018.1
| 25.1
| 25.2
|
2023-04-02 04:40:00-05:00
| 2,023
| 4
| 2
| 4
| 40
| 134
| 3.2
| 4.1
| 1.24
| 6.25
| 5.61
| 145
| 1,018
| 25.1
| 25.2
|
2023-04-02 05:10:00-05:00
| 2,023
| 4
| 2
| 5
| 10
| 138
| 3.1
| 4
| 1.13
| 6.25
| 5.37
| 136
| 1,017.7
| 25
| 25.2
|
2023-04-02 05:40:00-05:00
| 2,023
| 4
| 2
| 5
| 40
| 145
| 2.9
| 4.1
| 1.11
| 6.25
| 5.26
| 156
| 1,017.6
| 24.9
| 25.2
|
2023-04-02 06:10:00-05:00
| 2,023
| 4
| 2
| 6
| 10
| 149
| 2.8
| 3.6
| 1.08
| 6.25
| 5.29
| 136
| 1,017.3
| 24.9
| 25.2
|
2023-04-02 06:40:00-05:00
| 2,023
| 4
| 2
| 6
| 40
| 153
| 3
| 3.7
| 1.04
| 6.25
| 5.24
| 136
| 1,016.9
| 24.9
| 25.2
|
2023-04-02 07:10:00-05:00
| 2,023
| 4
| 2
| 7
| 10
| 159
| 3.5
| 4.4
| 1.04
| 6.25
| 5.38
| 163
| 1,016.4
| 24.9
| 25.2
|
2023-04-02 07:40:00-05:00
| 2,023
| 4
| 2
| 7
| 40
| 162
| 4.2
| 4.9
| 0.92
| 6.67
| 5.16
| 141
| 1,016
| 24.8
| 25.1
|
2023-04-02 08:10:00-05:00
| 2,023
| 4
| 2
| 8
| 10
| 161
| 3.9
| 5
| 1.04
| 6.67
| 5.39
| 114
| 1,015.8
| 24.8
| 25.1
|
2023-04-02 08:40:00-05:00
| 2,023
| 4
| 2
| 8
| 40
| 162
| 3.4
| 4.6
| 0.95
| 7.14
| 5.39
| 125
| 1,015.3
| 24.7
| 25.1
|
2023-04-02 09:10:00-05:00
| 2,023
| 4
| 2
| 9
| 10
| 157
| 3.6
| 4.4
| 0.92
| 7.14
| 5.25
| 137
| 1,015.1
| 24.7
| 25.1
|
2023-04-02 09:40:00-05:00
| 2,023
| 4
| 2
| 9
| 40
| 156
| 4.8
| 5.7
| 1.01
| 7.69
| 5.43
| 108
| 1,014.8
| 24.7
| 25.1
|
2023-04-02 10:10:00-05:00
| 2,023
| 4
| 2
| 10
| 10
| 152
| 5
| 5.9
| 0.92
| 7.14
| 5.19
| 116
| 1,014.6
| 24.7
| 25.1
|
2023-04-02 10:40:00-05:00
| 2,023
| 4
| 2
| 10
| 40
| 153
| 4.4
| 5.1
| 0.84
| 6.67
| 5.11
| 117
| 1,014.8
| 24.7
| 25.1
|
2023-04-02 11:10:00-05:00
| 2,023
| 4
| 2
| 11
| 10
| 146
| 3.3
| 4.2
| 0.88
| 6.25
| 5.18
| 148
| 1,014.6
| 24.6
| 25.1
|
2023-04-02 11:40:00-05:00
| 2,023
| 4
| 2
| 11
| 40
| 119
| 3
| 3.6
| 0.8
| 6.25
| 5.08
| 126
| 1,014.8
| 24.6
| 25.1
|
2023-04-02 12:10:00-05:00
| 2,023
| 4
| 2
| 12
| 10
| 121
| 3.2
| 4
| 0.9
| 7.14
| 5.41
| 104
| 1,015.2
| 24.6
| 25
|
2023-04-02 12:40:00-05:00
| 2,023
| 4
| 2
| 12
| 40
| 116
| 3.1
| 3.8
| 0.78
| 7.14
| 5.26
| 90
| 1,015.5
| 24.7
| 25
|
2023-04-02 13:10:00-05:00
| 2,023
| 4
| 2
| 13
| 10
| 121
| 3.7
| 4.5
| 0.77
| 7.69
| 5.16
| 88
| 1,015.8
| 24.9
| 25
|
2023-04-02 13:40:00-05:00
| 2,023
| 4
| 2
| 13
| 40
| 130
| 5.2
| 6.5
| 0.79
| 6.67
| 5.09
| 100
| 1,015.8
| 25
| 25
|
2023-04-02 14:10:00-05:00
| 2,023
| 4
| 2
| 14
| 10
| 136
| 5.8
| 6.8
| 0.77
| 7.69
| 5.11
| 99
| 1,016.3
| 25
| 25
|
2023-04-02 14:40:00-05:00
| 2,023
| 4
| 2
| 14
| 40
| 143
| 5.7
| 7
| 0.8
| 7.69
| 4.93
| 95
| 1,016.6
| 25.2
| 25
|
2023-04-02 15:10:00-05:00
| 2,023
| 4
| 2
| 15
| 10
| 138
| 4.9
| 6
| 0.8
| 7.69
| 4.91
| 96
| 1,016.4
| 25.3
| 25
|
2023-04-02 15:40:00-05:00
| 2,023
| 4
| 2
| 15
| 40
| 132
| 4.5
| 5.6
| 0.82
| 7.14
| 4.99
| 103
| 1,016.4
| 25.3
| 25.1
|
2023-04-02 16:10:00-05:00
| 2,023
| 4
| 2
| 16
| 10
| 126
| 4.4
| 5.4
| 0.8
| 7.14
| 5.1
| 85
| 1,016.4
| 25.3
| 25.1
|
2023-04-02 16:40:00-05:00
| 2,023
| 4
| 2
| 16
| 40
| 118
| 4.8
| 5.9
| 0.75
| 7.14
| 4.71
| 92
| 1,016.1
| 25.4
| 25.2
|
2023-04-02 17:10:00-05:00
| 2,023
| 4
| 2
| 17
| 10
| 121
| 5.8
| 6.9
| 0.78
| 7.69
| 4.9
| 106
| 1,015.6
| 25.4
| 25.2
|
2023-04-02 17:40:00-05:00
| 2,023
| 4
| 2
| 17
| 40
| 123
| 6.5
| 8.1
| 0.85
| 7.14
| 4.9
| 112
| 1,015.3
| 25.4
| 25.2
|
2023-04-02 18:10:00-05:00
| 2,023
| 4
| 2
| 18
| 10
| 124
| 7
| 8.7
| 0.88
| 7.14
| 4.86
| 137
| 1,014.7
| 25.4
| 25.2
|
2023-04-02 18:40:00-05:00
| 2,023
| 4
| 2
| 18
| 40
| 125
| 6.7
| 8
| 0.9
| 7.14
| 4.67
| 141
| 1,014.2
| 25.5
| 25.2
|
2023-04-02 19:10:00-05:00
| 2,023
| 4
| 2
| 19
| 10
| 129
| 7.1
| 9
| 0.91
| 7.14
| 4.44
| 130
| 1,013.6
| 25.5
| 25.2
|
2023-04-02 19:40:00-05:00
| 2,023
| 4
| 2
| 19
| 40
| 132
| 7.1
| 8.8
| 1.05
| 7.14
| 4.81
| 127
| 1,013.1
| 25.5
| 25.2
|
2023-04-02 20:10:00-05:00
| 2,023
| 4
| 2
| 20
| 10
| 137
| 7.3
| 9
| 0.9
| 7.14
| 4.49
| 118
| 1,012.8
| 25.6
| 25.3
|
2023-04-02 20:40:00-05:00
| 2,023
| 4
| 2
| 20
| 40
| 142
| 7.2
| 8.8
| 0.99
| 6.67
| 4.52
| 138
| 1,012.3
| 25.6
| 25.3
|
2023-04-02 21:10:00-05:00
| 2,023
| 4
| 2
| 21
| 10
| 150
| 7.9
| 10.2
| 1.03
| 6.25
| 4.57
| 133
| 1,011.8
| 25.6
| 25.2
|
2023-04-02 21:40:00-05:00
| 2,023
| 4
| 2
| 21
| 40
| 155
| 8
| 10.1
| 1.09
| 6.25
| 4.58
| 139
| 1,011.7
| 25.6
| 25.3
|
2023-04-02 22:10:00-05:00
| 2,023
| 4
| 2
| 22
| 10
| 155
| 8
| 9.6
| 1.07
| 6.67
| 4.41
| 141
| 1,011.3
| 25.6
| 25.3
|
2023-04-02 22:40:00-05:00
| 2,023
| 4
| 2
| 22
| 40
| 157
| 7.9
| 9.6
| 1.08
| 7.14
| 4.41
| 119
| 1,011.3
| 25.6
| 25.2
|
2023-04-02 23:10:00-05:00
| 2,023
| 4
| 2
| 23
| 10
| 159
| 8
| 9.6
| 1.09
| 5.88
| 4.43
| 147
| 1,011.2
| 25.6
| 25.2
|
2023-04-02 23:40:00-05:00
| 2,023
| 4
| 2
| 23
| 40
| 160
| 8.4
| 10.3
| 1.12
| 6.67
| 4.49
| 124
| 1,011.1
| 25.5
| 25.2
|
2023-04-03 00:10:00-05:00
| 2,023
| 4
| 3
| 0
| 10
| 162
| 8.4
| 10
| 1.11
| 5.26
| 4.38
| 147
| 1,011.1
| 25.4
| 25.2
|
2023-04-03 00:40:00-05:00
| 2,023
| 4
| 3
| 0
| 40
| 163
| 8.3
| 10.1
| 1.16
| 6.67
| 4.52
| 125
| 1,011.1
| 25.4
| 25.2
|
2023-04-03 01:10:00-05:00
| 2,023
| 4
| 3
| 1
| 10
| 164
| 8.8
| 10.2
| 1.23
| 6.67
| 4.58
| 124
| 1,011.2
| 25.3
| 25.2
|
2023-04-03 01:40:00-05:00
| 2,023
| 4
| 3
| 1
| 40
| 166
| 8.3
| 10.1
| 1.12
| 5.26
| 4.35
| 147
| 1,011.1
| 25.3
| 25.3
|
End of preview.
NOAA Buoy meterological data
NOAA Buoy Data was downloaded, processed, and cleaned for tasks pertaining to tabular data. The data consists of meteorological measurements. There are two datasets
- From 1980 through 2022 (denoted with "years" in file names)
- From Jan 2023 through end of Sept 2023 (denoted with "2023" in file names)
The original intended use is for anomaly detection in tabular data.
Dataset Details
Dataset Description
This dataset contains weather buoy data to be used in a tabular embedding scenarios. Buoy 42002 was chosen because it had many years of historical data and was still actively collecting information
Here is the buoy's page and its historical data page:
- https://www.ndbc.noaa.gov/station_page.php?station=42002
- https://www.ndbc.noaa.gov/station_history.php?station=42002
Only standard meteorological data and ocean data was downloaded. Downloaded started at 1980, which is the first full year of collecting wave information.
Data Fields
{'TSTMP': 'timestamp', '#YY': '#yr', ' MM': 'mo', 'DD': 'dy', 'hh': 'hr', 'mm': 'mn', 'WDIR': 'degT', 'WSPD': 'm/s', ' GST': 'm/s', ' WVHT': 'm', 'DPD': 'sec', 'APD': 'sec', 'MWD ': 'degT', 'PRES': 'hPa', ' ATMP': 'degC', ' WTMP': 'degC' }
Dataset Creation
Curation Rationale
The original data has inconsistent delimiters, different and inappropriate missing data values, and was not harmonized across years. Pre-2023 was edited in the same way as the previous data but kept separate to allow for train and inference.
Source Data
Initial Data Collection and Normalization
Data Downloaded on Oct 12 2023
All code used to transform the data can be found in the buoy-python directory. This is NOT production code and the focus was on correct results and minimizing time spent writing cleaning code.
- #YY, MM, DD, hh, mm were concatenated to create a timestamp and stored in a new column.
- From 1980 until 2005 there was no recording of minutes. Minutes for those years was set to 00.
- All missing data was set to a blank value rather than an actual number
- Remove all rows without wave data from all the data sets ( missing value in WVHT and DPD)
- Columns MWD, DEWP, VIS, and TIDE were removed because of consistent missing values
- From 2005 -> 2006 Wind direction goes from being called WD to WDIR
- From 2006 -> 2007 Header goes from just 1 line with variable names to 2 lines with the second line being units.
These steps were used to create full_2023_remove_flawed_rows, the 2023 months, and full_years_remove_flawed_rows the previous data going back to 1980
Since the original purpose of this data was anomaly detection. The two data sets above received further processing.
- All data values were converted to Z-scores (file named zscore_2023)
- For 1980 - 2022, all rows with 2 or more fields with Z-scores > 2 were removed from the dataset (file named trimmed_zscores_years )
Uses
Direct Use
Primary use is working with tabular data and embeddings, particularly for anomaly detection
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