Datasets › Electricity
Electricity (Individual household electric power consumption Data Set)
Abstract: Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available.
| Data Set Characteristics | Number of Instances | Area | Attribute Characteristics | Number of Attributes | Date Donated | Associated Tasks | Missing Values |
|---|---|---|---|---|---|---|---|
| Multivariate, Time-Series | 2075259 | Physical | Real | 9 | 2012-08-30 | Regression, Clustering | Yes |
Source:
Georges Hebrail (georges.hebrail '@' edf.fr), Senior Researcher, EDF R&D, Clamart, France Alice Berard, TELECOM ParisTech Master of Engineering Internship at EDF R&D, Clamart, France
Data Set Information:
This archive contains 2075259 measurements gathered in a house located in Sceaux (7km of Paris, France) between December 2006 and November 2010 (47 months). Notes:
- (global_active_power*1000/60 - sub_metering_1 - sub_metering_2 - sub_metering_3) represents the active energy consumed every minute (in watt hour) in the household by electrical equipment not measured in sub-meterings 1, 2 and 3.
- The dataset contains some missing values in the measurements (nearly 1,25% of the rows). All calendar timestamps are present in the dataset but for some timestamps, the measurement values are missing: a missing value is represented by the absence of value between two consecutive semi-colon attribute separators. For instance, the dataset shows missing values on April 28, 2007.
Attribute Information:
date: Date in formatdd/mm/yyyytime: time in formathh:mm:ssglobal_active_power: household global minute-averaged active power (in kilowatt)global_reactive_power: household global minute-averaged reactive power (in kilowatt)voltage: minute-averaged voltage (in volt)global_intensity: household global minute-averaged current intensity (in ampere)sub_metering_1: energy sub-metering No. 1 (in watt-hour of active energy). It corresponds to the kitchen, containing mainly a dishwasher, an oven and a microwave (hot plates are not electric but gas powered).sub_metering_2: energy sub-metering No. 2 (in watt-hour of active energy). It corresponds to the laundry room, containing a washing-machine, a tumble-drier, a refrigerator and a light.sub_metering_3: energy sub-metering No. 3 (in watt-hour of active energy). It corresponds to an electric water-heater and an air-conditioner.
Relevant Papers:
N/A
Citation Request:
This dataset is made available under the “Creative Commons Attribution 4.0 International (CC BY 4.0)” license
Benchmarks archive 2025-07-28
All 6 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Univariate Time Series Forecasting | Electricity | MTGNN (3 step) RRSE 0.0745 | Connecting the Dots: Multivariate Time Series... | benedekrozemberczki/pytorch_geometric_temporal +2 | 12 | Compare |
| Core set discovery | Electricity | EvoCore F1(10-fold) 69.3 | Uncovering Coresets for Classification With... | pietrobarbiero/meco | 1 | Compare |
| Correlated Time Series Forecasting | Electricity | LightCTS FLOPs(M) 239 | LightCTS: A Lightweight Framework for Correlated Time... | ai4cts/lightcts | 1 | Compare |
| GLinear | Electricity | GLinear MSE 0.0883 | Bridging Simplicity and Sophistication using GLinear: A... | t-rizvi/GLinear | 1 | Compare |
| Multivariate Time Series Forecasting | Electricity | GLinear MSE 0.0883 | Bridging Simplicity and Sophistication using GLinear: A... | t-rizvi/GLinear | 1 | Compare |
| Multivariate Time Series Imputation | Electricity | SAITS MAE (100 steps, 10% data missing) 0.735 | SAITS: Self-Attention-based Imputation for Time Series | WenjieDu/PyPOTS +2 | 1 | Compare |
Papers archive 2025-07-28
7 shown of 7 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 32. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| Bridging Simplicity and Sophistication using GLinear: A Novel Architecture for Enhanced Time Series Prediction | 1 | 2 | 2 Jan 2025 | not harvested |
| LightCTS: A Lightweight Framework for Correlated Time Series Forecasting | 1 | 1 | 23 Feb 2023 | not harvested |
| SAITS: Self-Attention-based Imputation for Time Series | 3 | 1 | 17 Feb 2022 | ran 3 of 10 samples (7 unverified) |
| Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks | 3 | 4 | 24 May 2020 | ran 1 of 2 samples (1 unverified; 1 pointer-only for licence) |
| Uncovering Coresets for Classification With Multi-Objective Evolutionary Algorithms | 1 | 1 | 20 Feb 2020 | not harvested |
| Temporal Pattern Attention for Multivariate Time Series Forecasting | 4 | 4 | 12 Sep 2018 | not harvested |
| Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks | 21 | 4 | 21 Mar 2017 | ran 0 of 7 samples (7 unverified) |
Dataset loaders archive 2025-07-28
2 loaders as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
Creative Commons Attribution 4.0 International
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- Electricity
1 variant name, as the archive lists them.
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