Individual Household Electric Power Consumption
Abstract
"Over 2 million minute-level measurements of electric power consumption in one household near Paris over 47 months (2006–2010), including global active/reactive power, voltage, current intensity, and sub-metering for kitchen, laundry, and water heater.[page:1][web:212]"
Description
Overview
The Individual Household Electric Power Consumption dataset contains multivariate time-series measurements from a single house located in Sceaux (7 km south of Paris, France) collected between December 2006 and November 2010.[page:1][web:212]
Data Collection
- 2,075,259 minute-averaged measurements over almost 4 years (47 months).[page:1][web:212]
- About 1.25% of rows contain missing values, represented by the absence of a value between consecutive semicolons in the CSV file.[page:1][web:215]
- All calendar timestamps are present in the dataset structure, but measurements for some timestamps are missing.[page:1]
Variables
- date (dd/mm/yyyy format) and time (hh:mm:ss format).[page:1]
- global_active_power (kilowatt): household global minute-averaged active power.[page:1]
- global_reactive_power (kilowatt): household global minute-averaged reactive power.[page:1]
- voltage (volt): minute-averaged voltage.[page:1]
- global_intensity (ampere): household global minute-averaged current intensity.[page:1]
- sub_metering_1 (watt-hour): energy sub-metering for the kitchen (dishwasher, oven, microwave; hot plates are gas-powered).[page:1]
- sub_metering_2 (watt-hour): energy sub-metering for the laundry room (washing machine, tumble-drier, refrigerator, light).[page:1]
- sub_metering_3 (watt-hour): energy sub-metering for an electric water-heater and air-conditioner.[page:1]
Use Cases
- Time-series load forecasting and energy demand prediction for smart homes.[page:1][web:214]
- Energy disaggregation (NILM) to identify individual appliance usage from whole-house measurements.[page:1]
- Clustering and pattern analysis of household electricity consumption behavior.[page:1][web:214]
License
The UCI page specifies that this dataset is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0), allowing sharing and adaptation with proper credit.[page:1]
📊 View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on UCI Machine Learning Repository.
Preview on UCI Machine Learning Repository
Cite This Dataset
Hebrail, Georges, & Berard, Alice (2012). Individual Household Electric Power Consumption. [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C58K54
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Original source: UCI Machine Learning Repository (2012). Visit official page for more details.
Indexed by IoTDataset.com on Jan 29, 2026
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