The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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://hf.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://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? 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.