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 ({'timestamp', 'MEM', 'CPU'}) and 11 missing columns ({'CPU Core 3 Usage (%)', 'CPU Core 7 Usage (%)', 'CPU Core 6 Usage (%)', 'Date', 'CPU Core 0 Usage (%)', 'CPU Core 4 Usage (%)', 'CPU Core 2 Usage (%)', 'Memory Usage (%)', 'CPU Core 1 Usage (%)', 'CPU Usage (All Cores) (%)', 'CPU Core 5 Usage (%)'}).

This happened while the csv dataset builder was generating data using

hf://datasets/ICOS-AI/live_cpu_utilization/node_3_utilisation_sample_dataset.csv (at revision e3d625be0d1804d51b46d787aa00eef4eec79d6f)

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 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              timestamp: string
              CPU: double
              MEM: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 594
              to
              {'Date': Value(dtype='string', id=None), 'CPU Core 0 Usage (%)': Value(dtype='string', id=None), 'CPU Core 1 Usage (%)': Value(dtype='float64', id=None), 'CPU Core 2 Usage (%)': Value(dtype='float64', id=None), 'CPU Core 3 Usage (%)': Value(dtype='float64', id=None), 'CPU Core 4 Usage (%)': Value(dtype='float64', id=None), 'CPU Core 5 Usage (%)': Value(dtype='float64', id=None), 'CPU Core 6 Usage (%)': Value(dtype='float64', id=None), 'CPU Core 7 Usage (%)': Value(dtype='float64', id=None), 'CPU Usage (All Cores) (%)': Value(dtype='float64', id=None), 'Memory Usage (%)': 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 1420, 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 1052, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, 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 1741, 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 1872, 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 ({'timestamp', 'MEM', 'CPU'}) and 11 missing columns ({'CPU Core 3 Usage (%)', 'CPU Core 7 Usage (%)', 'CPU Core 6 Usage (%)', 'Date', 'CPU Core 0 Usage (%)', 'CPU Core 4 Usage (%)', 'CPU Core 2 Usage (%)', 'Memory Usage (%)', 'CPU Core 1 Usage (%)', 'CPU Usage (All Cores) (%)', 'CPU Core 5 Usage (%)'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/ICOS-AI/live_cpu_utilization/node_3_utilisation_sample_dataset.csv (at revision e3d625be0d1804d51b46d787aa00eef4eec79d6f)
              
              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.

Date
string
CPU Core 0 Usage (%)
string
CPU Core 1 Usage (%)
float64
CPU Core 2 Usage (%)
float64
CPU Core 3 Usage (%)
null
CPU Core 4 Usage (%)
null
CPU Core 5 Usage (%)
null
CPU Core 6 Usage (%)
null
CPU Core 7 Usage (%)
null
CPU Usage (All Cores) (%)
null
Memory Usage (%)
null
2023-06-28 16:26:24
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
0
10.2
null
null
null
null
null
null
null
2023-06-28 16:31:58
[0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]
0
10.3
null
null
null
null
null
null
null
2023-06-28 16:33:00
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
0.3
10.3
null
null
null
null
null
null
null
2023-06-28 16:34:02
[2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
0
10.3
null
null
null
null
null
null
null
2023-06-28 16:35:04
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
0
10.3
null
null
null
null
null
null
null
2023-06-28 16:36:07
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.4
null
null
null
null
null
null
null
2023-06-28 16:37:09
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.7
null
null
null
null
null
null
null
2023-06-28 16:38:11
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.7
null
null
null
null
null
null
null
2023-06-28 16:39:13
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.7
null
null
null
null
null
null
null
2023-06-28 16:40:15
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.7
null
null
null
null
null
null
null
2023-06-28 16:41:17
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.4
null
null
null
null
null
null
null
2023-06-28 16:42:19
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.4
null
null
null
null
null
null
null
2023-06-28 16:43:21
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.4
null
null
null
null
null
null
null
2023-06-28 16:44:23
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.4
null
null
null
null
null
null
null
2023-06-28 16:45:25
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.4
null
null
null
null
null
null
null
2023-06-28 16:46:27
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.4
null
null
null
null
null
null
null
2023-06-28 16:47:29
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
10.4
null
null
null
null
null
null
null
2023-06-28 16:48:31
[0.0, 0.0, 0.0, 1.0, 79.0, 79.0, 83.0, 80.0]
40.6
10.5
null
null
null
null
null
null
null
2023-06-28 16:49:33
[0.0, 0.0, 1.0, 0.0, 83.2, 78.0, 75.2, 78.0]
42.8
10.5
null
null
null
null
null
null
null
2023-06-28 16:50:35
[1.0, 0.0, 0.0, 1.0, 96.0, 80.0, 73.0, 72.3]
41.6
10.5
null
null
null
null
null
null
null
2023-06-28 16:51:37
[3.0, 8.0, 17.2, 0.0, 75.0, 43.0, 93.0, 93.1]
40.5
10.5
null
null
null
null
null
null
null
2023-06-28 16:52:39
[0.0, 0.0, 0.0, 1.0, 80.0, 59.6, 80.8, 63.6]
39.6
10.5
null
null
null
null
null
null
null
2023-06-28 16:53:42
[11.8, 2.0, 5.0, 9.1, 99.0, 100.0, 51.5, 52.0]
37.7
10.5
null
null
null
null
null
null
null
2023-06-28 16:54:44
[6.9, 3.0, 0.0, 1.0, 93.0, 94.0, 76.0, 97.0]
39.6
10.5
null
null
null
null
null
null
null
2023-06-28 16:55:46
[3.9, 0.0, 7.0, 1.0, 75.0, 90.1, 94.0, 64.0]
42.6
10.5
null
null
null
null
null
null
null
2023-06-28 16:56:48
[5.8, 11.1, 0.0, 0.0, 80.0, 92.0, 74.0, 60.0]
36.8
10.5
null
null
null
null
null
null
null
2023-06-28 16:57:50
[2.0, 11.9, 0.0, 1.0, 73.5, 87.0, 66.0, 96.0]
44.2
10.5
null
null
null
null
null
null
null
2023-06-28 16:58:52
[18.6, 11.0, 18.0, 0.0, 88.0, 77.8, 42.0, 90.0]
38.1
10.5
null
null
null
null
null
null
null
2023-06-28 16:59:54
[6.0, 1.0, 0.0, 0.0, 89.1, 58.0, 61.0, 69.7]
39.8
10.5
null
null
null
null
null
null
null
2023-06-28 17:00:56
[3.0, 0.0, 0.0, 7.9, 64.4, 89.1, 86.0, 59.0]
40.8
10.5
null
null
null
null
null
null
null
2023-06-28 17:01:58
[1.0, 0.0, 14.9, 1.0, 70.0, 87.0, 93.0, 70.3]
40.3
10.5
null
null
null
null
null
null
null
2023-06-28 17:03:00
[1.0, 0.0, 0.0, 0.0, 76.0, 91.0, 74.3, 79.2]
42.2
10.5
null
null
null
null
null
null
null
2023-06-28 17:04:02
[2.9, 0.0, 1.0, 7.0, 72.0, 54.5, 94.1, 92.1]
36.9
10.5
null
null
null
null
null
null
null
2023-06-28 17:05:04
[0.0, 0.0, 0.0, 1.0, 83.0, 81.0, 71.3, 80.2]
40.6
10.5
null
null
null
null
null
null
null
2023-06-28 17:06:06
[0.0, 0.0, 0.0, 0.0, 81.2, 81.0, 73.0, 71.0]
39.1
10.5
null
null
null
null
null
null
null
2023-06-28 17:07:08
[1.0, 0.0, 0.0, 1.0, 88.9, 98.0, 52.0, 70.3]
41.1
10.5
null
null
null
null
null
null
null
2023-06-28 17:08:10
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
11.7
null
null
null
null
null
null
null
2023-06-28 17:09:12
[100.0, 100.0, 100.0, 99.0, 99.0, 100.0, 99.0, 99.0]
99.8
12.3
null
null
null
null
null
null
null
2023-06-28 17:10:14
[99.0, 100.0, 100.0, 100.0, 100.0, 99.0, 100.0, 100.0]
100
12.3
null
null
null
null
null
null
null
2023-06-28 17:11:16
[100.0, 100.0, 100.0, 100.0, 100.0, 99.0, 100.0, 100.0]
99.9
12.5
null
null
null
null
null
null
null
2023-06-28 17:12:18
[100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
100
12.6
null
null
null
null
null
null
null
2023-06-28 17:13:20
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
0.1
10.4
null
null
null
null
null
null
null
2023-06-28 17:14:23
[100.0, 72.5, 97.0, 49.1, 100.0, 100.0, 100.0, 100.0]
92.9
13.9
null
null
null
null
null
null
null
2023-06-28 17:15:25
[63.3, 71.3, 71.0, 22.3, 72.7, 73.0, 73.3, 70.3]
0.4
10.4
null
null
null
null
null
null
null
2023-06-28 17:16:27
[21.0, 2.9, 0.0, 0.0, 74.3, 50.0, 64.0, 69.0]
5.6
10.6
null
null
null
null
null
null
null
2023-06-28 17:17:29
[0.0, 0.0, 0.0, 0.0, 53.0, 69.0, 34.3, 64.0]
11.2
10.6
null
null
null
null
null
null
null
2023-06-28 17:18:31
[1.0, 0.0, 0.0, 0.0, 63.0, 0.0, 77.0, 6.0]
20.9
10.6
null
null
null
null
null
null
null
2023-06-28 17:19:33
[0.0, 0.0, 0.0, 1.0, 67.7, 36.0, 55.0, 50.0]
14.2
10.6
null
null
null
null
null
null
null
2023-06-28 17:20:35
[1.0, 0.0, 0.0, 0.0, 57.4, 32.0, 30.7, 73.7]
22.9
10.6
null
null
null
null
null
null
null
2023-06-28 17:21:37
[0.0, 0.0, 0.0, 1.0, 5.0, 34.7, 39.0, 35.0]
22.1
10.6
null
null
null
null
null
null
null
2023-06-28 17:22:39
[0.0, 0.0, 0.0, 0.0, 0.0, 37.0, 47.0, 26.7]
26.6
10.6
null
null
null
null
null
null
null
2023-06-28 17:23:41
[0.0, 0.0, 0.0, 0.0, 35.0, 35.0, 36.6, 35.0]
15.6
10.6
null
null
null
null
null
null
null
2023-06-28 17:24:43
[1.0, 0.0, 0.0, 0.0, 56.4, 27.7, 53.5, 55.4]
23.9
10.6
null
null
null
null
null
null
null
2023-06-28 17:25:45
[0.0, 0.0, 0.0, 0.0, 52.0, 61.0, 23.0, 24.8]
20.8
10.6
null
null
null
null
null
null
null
2023-06-28 17:26:47
[0.0, 0.0, 0.0, 0.0, 31.0, 34.7, 31.7, 31.0]
29.6
10.6
null
null
null
null
null
null
null
2023-06-28 17:27:49
[1.0, 0.0, 0.0, 0.0, 49.0, 50.0, 9.0, 7.9]
27.5
10.6
null
null
null
null
null
null
null
2023-06-28 17:28:51
[0.0, 0.0, 0.0, 0.0, 60.0, 10.0, 38.4, 63.0]
17
10.6
null
null
null
null
null
null
null
2023-06-28 17:29:53
[0.0, 0.0, 0.0, 1.0, 0.0, 27.0, 27.0, 43.0]
26.7
10.6
null
null
null
null
null
null
null
2023-06-28 17:30:55
[0.0, 0.0, 0.0, 0.0, 74.3, 56.0, 34.7, 35.6]
13.5
10.6
null
null
null
null
null
null
null
2023-06-28 17:31:57
[0.0, 0.0, 0.0, 0.0, 48.0, 17.8, 25.0, 23.8]
22.5
10.6
null
null
null
null
null
null
null
2023-06-28 17:32:59
[0.0, 0.0, 0.0, 0.0, 2.0, 38.0, 52.0, 3.0]
23.2
10.6
null
null
null
null
null
null
null
2023-06-28 17:34:02
[1.0, 0.0, 0.0, 1.0, 62.4, 56.4, 44.4, 73.3]
13.2
10.6
null
null
null
null
null
null
null
2023-06-28 17:35:04
[0.0, 1.0, 0.0, 0.0, 51.5, 91.0, 74.3, 39.6]
12.7
10.6
null
null
null
null
null
null
null
2023-06-28 17:36:06
[0.0, 1.0, 0.0, 0.0, 55.0, 34.3, 10.1, 28.0]
21.1
10.6
null
null
null
null
null
null
null
2023-06-28 17:37:08
[11.9, 1.0, 0.0, 0.0, 22.0, 68.3, 32.3, 25.0]
12.1
10.6
null
null
null
null
null
null
null
2023-06-28 17:38:10
[0.0, 0.0, 0.0, 0.0, 60.0, 36.0, 22.2, 36.6]
15.6
10.6
null
null
null
null
null
null
null
2023-06-28 17:39:12
[0.0, 0.0, 0.0, 0.0, 46.5, 25.3, 25.0, 27.0]
29.4
10.7
null
null
null
null
null
null
null
2023-06-28 17:40:14
[0.0, 0.0, 0.0, 0.0, 34.0, 33.7, 41.4, 47.0]
30.7
10.7
null
null
null
null
null
null
null
2023-06-28 17:41:16
[1.0, 0.0, 0.0, 0.0, 85.1, 10.9, 22.8, 34.0]
24.7
10.8
null
null
null
null
null
null
null
2023-06-28 17:42:18
[0.0, 0.0, 0.0, 0.0, 83.8, 36.0, 12.0, 9.0]
22
10.8
null
null
null
null
null
null
null
2023-06-28 17:43:20
[0.0, 0.0, 0.0, 0.0, 59.0, 37.0, 36.0, 45.5]
17.5
10.6
null
null
null
null
null
null
null
2023-06-28 17:44:22
[0.0, 0.0, 0.0, 0.0, 30.7, 13.9, 64.4, 69.0]
20
10.6
null
null
null
null
null
null
null
2023-06-28 17:45:24
[0.0, 0.0, 0.0, 0.0, 37.0, 0.0, 22.2, 72.3]
22.4
10.6
null
null
null
null
null
null
null
2023-06-28 17:46:26
[0.0, 0.0, 0.0, 0.0, 26.7, 34.0, 50.5, 36.6]
21.5
10.6
null
null
null
null
null
null
null
2023-06-28 17:47:28
[1.0, 0.0, 0.0, 0.0, 22.8, 65.7, 0.0, 60.0]
19
10.6
null
null
null
null
null
null
null
2023-06-28 17:48:30
[0.0, 0.0, 0.0, 0.0, 37.0, 0.0, 33.0, 40.0]
22.8
10.6
null
null
null
null
null
null
null
2023-06-28 17:49:32
[0.0, 0.0, 0.0, 0.0, 70.3, 37.0, 36.0, 62.4]
13.3
10.7
null
null
null
null
null
null
null
2023-06-28 17:50:34
[0.0, 0.0, 0.0, 0.0, 81.2, 21.0, 38.0, 34.0]
18
10.7
null
null
null
null
null
null
null
2023-06-28 17:51:36
[0.0, 0.0, 0.0, 0.0, 53.0, 26.0, 38.0, 36.6]
18.1
10.7
null
null
null
null
null
null
null
2023-06-28 17:52:38
[1.0, 0.0, 0.0, 0.0, 49.5, 1.0, 41.0, 0.0]
29.5
10.7
null
null
null
null
null
null
null
2023-06-28 17:53:41
[0.0, 0.0, 0.0, 1.0, 51.5, 6.9, 59.0, 38.0]
18.1
10.8
null
null
null
null
null
null
null
2023-06-28 17:54:43
[1.0, 0.0, 1.0, 0.0, 54.0, 42.0, 13.0, 71.0]
16.7
10.8
null
null
null
null
null
null
null
2023-06-28 17:55:45
[0.0, 0.0, 0.0, 0.0, 18.0, 10.0, 50.0, 45.0]
19.5
10.8
null
null
null
null
null
null
null
2023-06-28 17:56:47
[1.0, 0.0, 0.0, 0.0, 75.0, 37.0, 35.0, 32.3]
14.3
10.8
null
null
null
null
null
null
null
2023-06-28 17:57:49
[0.0, 0.0, 0.0, 0.0, 34.0, 36.4, 38.6, 40.0]
17.2
10.6
null
null
null
null
null
null
null
2023-06-28 17:58:51
[0.0, 0.0, 0.0, 0.0, 37.6, 30.0, 0.0, 3.0]
28.3
10.6
null
null
null
null
null
null
null
2023-06-28 17:59:53
[0.0, 0.0, 0.0, 0.0, 28.0, 56.4, 42.0, 31.0]
25.2
10.6
null
null
null
null
null
null
null
2023-06-28 18:00:55
[0.0, 0.0, 0.0, 0.0, 4.0, 14.1, 38.0, 26.0]
24.7
10.6
null
null
null
null
null
null
null
2023-06-28 18:01:57
[0.0, 0.0, 0.0, 0.0, 38.6, 70.0, 37.0, 39.0]
17.1
10.6
null
null
null
null
null
null
null
2023-06-28 18:02:59
[0.0, 0.0, 0.0, 0.0, 58.4, 56.4, 26.3, 38.4]
19
10.6
null
null
null
null
null
null
null
2023-06-28 18:04:01
[2.0, 0.0, 0.0, 0.0, 26.0, 46.0, 60.6, 38.6]
20.4
10.6
null
null
null
null
null
null
null
2023-06-28 18:05:03
[1.0, 1.0, 2.0, 0.0, 10.1, 21.0, 2.0, 1.0]
1.2
10.4
null
null
null
null
null
null
null
2023-06-28 18:06:05
[0.0, 0.0, 0.0, 0.0, 58.0, 59.0, 76.0, 74.0]
32.8
10.6
null
null
null
null
null
null
null
2023-06-28 18:07:07
[0.0, 3.0, 3.0, 0.0, 62.4, 59.0, 73.3, 59.6]
31.5
10.6
null
null
null
null
null
null
null
2023-06-28 18:08:09
[0.0, 0.0, 0.0, 0.0, 69.0, 96.0, 74.0, 37.0]
31.7
10.6
null
null
null
null
null
null
null
2023-06-28 18:09:11
[0.0, 0.0, 0.0, 0.0, 64.4, 71.0, 63.0, 62.4]
30.8
10.6
null
null
null
null
null
null
null
2023-06-28 18:10:13
[13.1, 20.2, 0.0, 20.0, 49.0, 38.0, 46.5, 42.4]
25
10.6
null
null
null
null
null
null
null
2023-06-28 18:11:15
[14.0, 1.0, 0.0, 0.0, 61.0, 36.6, 59.6, 85.0]
33
10.6
null
null
null
null
null
null
null
2023-06-28 18:12:17
[18.0, 2.0, 15.2, 0.0, 61.0, 62.0, 62.0, 72.3]
39.5
10.6
null
null
null
null
null
null
null
2023-06-28 18:13:19
[0.0, 0.0, 0.0, 0.0, 60.0, 60.0, 56.0, 61.0]
33.7
10.6
null
null
null
null
null
null
null
End of preview.