date
stringlengths 19
19
| data
float64 -1
12.3M
| cols
stringlengths 10
13
|
|---|---|---|
2022-04-02 00:00:00 | 49.208571 | instance_1 |
2022-04-02 00:10:00 | 70.747 | instance_1 |
2022-04-02 00:20:00 | 61.513 | instance_1 |
2022-04-02 00:30:00 | 58.166 | instance_1 |
2022-04-02 00:40:00 | 28.039 | instance_1 |
2022-04-02 00:50:00 | 41.813 | instance_1 |
2022-04-02 01:00:00 | 34.396 | instance_1 |
2022-04-02 01:10:00 | 34.249 | instance_1 |
2022-04-02 01:20:00 | 24.966 | instance_1 |
2022-04-02 01:30:00 | 39.493 | instance_1 |
2022-04-02 01:40:00 | 38.346 | instance_1 |
2022-04-02 01:50:00 | 23.126 | instance_1 |
2022-04-02 02:00:00 | 32.234 | instance_1 |
2022-04-02 02:10:00 | 42.015 | instance_1 |
2022-04-02 02:20:00 | 24.355 | instance_1 |
2022-04-02 02:30:00 | 68.711 | instance_1 |
2022-04-02 02:40:00 | 24.974 | instance_1 |
2022-04-02 02:50:00 | 43.079 | instance_1 |
2022-04-02 03:00:00 | 59.869 | instance_1 |
2022-04-02 03:10:00 | 41.194 | instance_1 |
2022-04-02 03:20:00 | 30.119 | instance_1 |
2022-04-02 03:30:00 | 36.287 | instance_1 |
2022-04-02 03:40:00 | 64.412 | instance_1 |
2022-04-02 03:50:00 | 50.318 | instance_1 |
2022-04-02 04:00:00 | 64.747 | instance_1 |
2022-04-02 04:10:00 | 101.668 | instance_1 |
2022-04-02 04:20:00 | 53.276 | instance_1 |
2022-04-02 04:30:00 | 74.592 | instance_1 |
2022-04-02 04:40:00 | 53.33 | instance_1 |
2022-04-02 04:50:00 | 108.756 | instance_1 |
2022-04-02 05:00:00 | 78.965 | instance_1 |
2022-04-02 05:10:00 | 81.751 | instance_1 |
2022-04-02 05:20:00 | 131.363 | instance_1 |
2022-04-02 05:30:00 | 114.222 | instance_1 |
2022-04-02 05:40:00 | 108.253 | instance_1 |
2022-04-02 05:50:00 | 132.338 | instance_1 |
2022-04-02 06:00:00 | 110.436 | instance_1 |
2022-04-02 06:10:00 | 121.502 | instance_1 |
2022-04-02 06:20:00 | 103.692 | instance_1 |
2022-04-02 06:30:00 | 131.779 | instance_1 |
2022-04-02 06:40:00 | 143.8 | instance_1 |
2022-04-02 06:50:00 | 106.81 | instance_1 |
2022-04-02 07:00:00 | 125.367 | instance_1 |
2022-04-02 07:10:00 | 118.018 | instance_1 |
2022-04-02 07:20:00 | 144.048 | instance_1 |
2022-04-02 07:30:00 | 122.593 | instance_1 |
2022-04-02 07:40:00 | 142.376 | instance_1 |
2022-04-02 07:50:00 | 91.864 | instance_1 |
2022-04-02 08:00:00 | 99.905 | instance_1 |
2022-04-02 08:10:00 | 100.677 | instance_1 |
2022-04-02 08:20:00 | 113.673 | instance_1 |
2022-04-02 08:30:00 | 99.811 | instance_1 |
2022-04-02 08:40:00 | 140.867 | instance_1 |
2022-04-02 08:50:00 | 130.704 | instance_1 |
2022-04-02 09:00:00 | 146.682 | instance_1 |
2022-04-02 09:10:00 | 175.313 | instance_1 |
2022-04-02 09:20:00 | 177.508 | instance_1 |
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 |
2022-04-02 10:00:00 | 181.889 | instance_1 |
2022-04-02 10:10:00 | 188.989 | instance_1 |
2022-04-02 10:20:00 | 114.089 | instance_1 |
2022-04-02 10:30:00 | 147.665 | instance_1 |
2022-04-02 10:40:00 | 146.992 | instance_1 |
2022-04-02 10:50:00 | 124.409 | instance_1 |
2022-04-02 11:00:00 | 177.513 | instance_1 |
2022-04-02 11:10:00 | 138.818 | instance_1 |
2022-04-02 11:20:00 | 157.481 | instance_1 |
2022-04-02 11:30:00 | 134.153 | instance_1 |
2022-04-02 11:40:00 | 178.046 | instance_1 |
2022-04-02 11:50:00 | 171.142 | instance_1 |
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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