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2022-04-02 00:00:00
| 49.208571
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instance_1
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2022-04-02 00:10:00
| 70.747
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instance_1
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2022-04-02 00:20:00
| 61.513
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instance_1
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2022-04-02 00:30:00
| 58.166
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instance_1
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2022-04-02 00:40:00
| 28.039
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instance_1
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2022-04-02 00:50:00
| 41.813
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instance_1
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2022-04-02 01:00:00
| 34.396
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instance_1
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2022-04-02 01:10:00
| 34.249
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instance_1
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2022-04-02 01:20:00
| 24.966
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instance_1
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2022-04-02 01:30:00
| 39.493
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instance_1
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2022-04-02 01:40:00
| 38.346
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instance_1
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2022-04-02 01:50:00
| 23.126
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instance_1
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2022-04-02 02:00:00
| 32.234
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instance_1
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2022-04-02 02:10:00
| 42.015
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instance_1
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2022-04-02 02:20:00
| 24.355
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instance_1
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2022-04-02 02:30:00
| 68.711
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instance_1
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2022-04-02 02:40:00
| 24.974
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instance_1
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2022-04-02 02:50:00
| 43.079
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instance_1
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2022-04-02 03:00:00
| 59.869
|
instance_1
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2022-04-02 03:10:00
| 41.194
|
instance_1
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2022-04-02 03:20:00
| 30.119
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instance_1
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2022-04-02 03:30:00
| 36.287
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instance_1
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2022-04-02 03:40:00
| 64.412
|
instance_1
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2022-04-02 03:50:00
| 50.318
|
instance_1
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2022-04-02 04:00:00
| 64.747
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instance_1
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2022-04-02 04:10:00
| 101.668
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instance_1
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2022-04-02 04:20:00
| 53.276
|
instance_1
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2022-04-02 04:30:00
| 74.592
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instance_1
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2022-04-02 04:40:00
| 53.33
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instance_1
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2022-04-02 04:50:00
| 108.756
|
instance_1
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2022-04-02 05:00:00
| 78.965
|
instance_1
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2022-04-02 05:10:00
| 81.751
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instance_1
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2022-04-02 05:20:00
| 131.363
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instance_1
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2022-04-02 05:30:00
| 114.222
|
instance_1
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2022-04-02 05:40:00
| 108.253
|
instance_1
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2022-04-02 05:50:00
| 132.338
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instance_1
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2022-04-02 06:00:00
| 110.436
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instance_1
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2022-04-02 06:10:00
| 121.502
|
instance_1
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2022-04-02 06:20:00
| 103.692
|
instance_1
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2022-04-02 06:30:00
| 131.779
|
instance_1
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2022-04-02 06:40:00
| 143.8
|
instance_1
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2022-04-02 06:50:00
| 106.81
|
instance_1
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2022-04-02 07:00:00
| 125.367
|
instance_1
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2022-04-02 07:10:00
| 118.018
|
instance_1
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2022-04-02 07:20:00
| 144.048
|
instance_1
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2022-04-02 07:30:00
| 122.593
|
instance_1
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2022-04-02 07:40:00
| 142.376
|
instance_1
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2022-04-02 07:50:00
| 91.864
|
instance_1
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2022-04-02 08:00:00
| 99.905
|
instance_1
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2022-04-02 08:10:00
| 100.677
|
instance_1
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2022-04-02 08:20:00
| 113.673
|
instance_1
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2022-04-02 08:30:00
| 99.811
|
instance_1
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2022-04-02 08:40:00
| 140.867
|
instance_1
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2022-04-02 08:50:00
| 130.704
|
instance_1
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2022-04-02 09:00:00
| 146.682
|
instance_1
|
2022-04-02 09:10:00
| 175.313
|
instance_1
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2022-04-02 09:20:00
| 177.508
|
instance_1
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2022-04-02 09:30:00
| 152.638
|
instance_1
|
2022-04-02 09:40:00
| 176.807
|
instance_1
|
2022-04-02 09:50:00
| 142.397
|
instance_1
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2022-04-02 10:00:00
| 181.889
|
instance_1
|
2022-04-02 10:10:00
| 188.989
|
instance_1
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2022-04-02 10:20:00
| 114.089
|
instance_1
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2022-04-02 10:30:00
| 147.665
|
instance_1
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2022-04-02 10:40:00
| 146.992
|
instance_1
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2022-04-02 10:50:00
| 124.409
|
instance_1
|
2022-04-02 11:00:00
| 177.513
|
instance_1
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2022-04-02 11:10:00
| 138.818
|
instance_1
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2022-04-02 11:20:00
| 157.481
|
instance_1
|
2022-04-02 11:30:00
| 134.153
|
instance_1
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2022-04-02 11:40:00
| 178.046
|
instance_1
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2022-04-02 11:50:00
| 171.142
|
instance_1
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2022-04-02 12:00:00
| 142.77
|
instance_1
|
2022-04-02 12:10:00
| 141.939
|
instance_1
|
2022-04-02 12:20:00
| 137.476
|
instance_1
|
2022-04-02 12:30:00
| 150.931
|
instance_1
|
2022-04-02 12:40:00
| 124.092
|
instance_1
|
2022-04-02 12:50:00
| 175.458
|
instance_1
|
2022-04-02 13:00:00
| 162.949
|
instance_1
|
2022-04-02 13:10:00
| 165.198
|
instance_1
|
2022-04-02 13:20:00
| 151.664
|
instance_1
|
2022-04-02 13:30:00
| 169.18
|
instance_1
|
2022-04-02 13:40:00
| 103.296
|
instance_1
|
2022-04-02 13:50:00
| 154.559
|
instance_1
|
2022-04-02 14:00:00
| 88.017
|
instance_1
|
2022-04-02 14:10:00
| 71.681
|
instance_1
|
2022-04-02 14:20:00
| 143.739
|
instance_1
|
2022-04-02 14:30:00
| 113.41
|
instance_1
|
2022-04-02 14:40:00
| 131.731
|
instance_1
|
2022-04-02 14:50:00
| 102.827
|
instance_1
|
2022-04-02 15:00:00
| 114.933
|
instance_1
|
2022-04-02 15:10:00
| 106.082
|
instance_1
|
2022-04-02 15:20:00
| 123.449
|
instance_1
|
2022-04-02 15:30:00
| 114.388
|
instance_1
|
2022-04-02 15:40:00
| 93.306
|
instance_1
|
2022-04-02 15:50:00
| 96.937
|
instance_1
|
2022-04-02 16:00:00
| 90.742
|
instance_1
|
2022-04-02 16:10:00
| 108.942
|
instance_1
|
2022-04-02 16:20:00
| 128.147
|
instance_1
|
2022-04-02 16:30:00
| 135.037
|
instance_1
|
End of preview. Expand
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YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
Intro
The data organization follows TFB format: https://github.com/decisionintelligence/TFB.
TFB data format
TFB stores time series in a format of three column long tables, which we will introduce below:
Format Introduction
First column: date (the exact column name is required, the same applies below.)
- The columns stores the time information in the time series, which can be in either of the following formats:
- Timestamps in string, datetime, or other types that are compatible with pd.to_datetime;
- Integers starting from 1, e.g. 1, 2, 3, 4, 5, ...
Second column: data
- This column stores the series values corresponding to the timestamps.
Third column: cols
- This column stores the column name (variable name).
Multivariate time series example:
A common time series in wide table format:
| date | channel1 | channel2 | channel3 |
|---|---|---|---|
| 1 | 0.1 | 1 | 10 |
| 2 | 0.2 | 2 | 20 |
| 3 | 0.3 | 3 | 30 |
Convert to TFB format:
| date | data | cols |
|---|---|---|
| 1 | 0.1 | channel1 |
| 2 | 0.2 | channel1 |
| 3 | 0.3 | channel1 |
| 1 | 1 | channel2 |
| 2 | 2 | channel2 |
| 3 | 3 | channel2 |
| 1 | 10 | channel3 |
| 2 | 20 | channel3 |
| 3 | 30 | channel3 |
License
This dataset is released under CC BY 4.0
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