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Data Science Dojo <br/>
Copyright (c) 2016 - 2019
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**Level:** Intermediate <br/>
**Recommended Use:** Regression/Clustering Models<br/>
**Domain:** Electricity<br/>
## Individual household electric power consumption Data Set
### Find a short term forecast on electricity consumption of a single home
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![](230088-P1ZDYV-666.jpg)
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This *intermediate* level data set has 2075259 rows and 9 columns.
This dataset provides 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.
This data set is recommended for learning and practicing your skills in **exploratory data analysis**, **data visualization**, **clustering** and **regression modelling techniques**.
It also allows you to practice with large number of features. Feel free to explore the data set with multiple **supervised** and **unsupervised** learning techniques. The Following data dictionary gives more details on this data set:
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### Data Dictionary
| Column Position | Atrribute Name | Definition | Data Type | Example | % Null Ratios |
|------------------- |----------------------- |------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |-------------- |---------------------------------- |--------------- |
| 1 | Date | Date: Date in format dd/mm/yyyy | Quantitative | 16/12/2006, 10/5/2007, 24/9/2007 | ? |
| 2 | Time | Time: time in format hh:mm:ss | Quantitative | 17:27:00, 6:56:00, 10:00:00 | ? |
| 3 | Global_Active_Power | Global_active_power: Household global minute-averaged active power (in kilowatt) | Quantitative | 4.216, 5.412, 3.488 | ? |
| 4 | Global_Reactive_Power | Global_reactive_power: Household global minute-averaged reactive power (in kilowatt) | Quantitative | 0.418, 0.47, 0.228 | ? |
| 5 | Voltage | Voltage: Minute-averaged voltage (in volt) | Quantitative | 234.84, 232.78, 233.06 | ? |
| 6 | Global_Intensity | Global_intensity: Household global minute-averaged current intensity (in ampere) | Quantitative | 18.4, 23.2, 15 | ? |
| 7 | Sub_Metering_1 | 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). | Quantitative | 1, 38, 17 | ? |
| 8 | Sub_Metering_2 | 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. | Quantitative | 1, 36, 5 | ? |
| 9 | Sub_Metering_3 | 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 | Quantitative | 17, 0, 18 | ? |
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Note:
(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
### Acknowledgement
This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Individual household electric power consumption Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Individual+household+electric+power+consumption).
The UCI page mentions the following as the source of the data set:
*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*
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