+Copyright (c) 2016 - 2019 + +--- + +**Level:** Intermediate

+**Recommended Use:** Regression/Classification Models

+**Domain:** Energy

+ +## Energy Efficiency Data Set + +### Assess heating and cooling load requirements of building + + +--- +![](OFASNQ0.jpg) +--- + +This *intermediate* level data set has 768 rows and 10 columns. +This study looked into assessing the heating load and cooling load requirements of buildings (that is, energy efficiency) as a function of building parameters +Energy analysis using 12 different building shapes simulated in Ecotect has been performed. +The buildings differ with respect to the glazing area, the glazing area distribution, and the orientation, amongst other parameters. +It can also be used as a multi-class classification problem if the response is rounded to the nearest integer. + +This data set is recommended for learning and practicing your skills in **exploratory data analysis**, **data visualization**, **regression** and **classification modelling techniques**. +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: + +--- + +### Data Dictionary + +| Column Position | Atrribute Name | Definition | Data Type | Example | % Null Ratios | +|------------------- |---------------- |------------------------------ |-------------- |------------------------ |--------------- | +| 1 | X1 | Relative Compactness | Quantitative | 0.86, 0.71, 0.79 | 0 | +| 2 | X2 | Surface Area | Quantitative | 588.0, 689.0, 710.5 | 0 | +| 3 | X3 | Wall Area | Quantitative | 318.5, 416.5, 294.0 | 0 | +| 4 | X4 | Roof Area | Quantitative | 110.25, 147.00, 122.50 | 0 | +| 5 | X5 | Overall Height | Quantitative | 7.0, 3.5 | 0 | +| 6 | X6 | Orientation | Quantitative | 2, 3, 5 | 0 | +| 7 | X7 | Glazing Area | Quantitative | 0.1, 0.25, 0.4 | 0 | +| 8 | X8 | Glazing Area Distribution | Quantitative | 0, 2, 4 | 0 | +| 9 | Y1 | Heating Load | Quantitative | 10.43, 11.69, 11.09 | 0 | +| 10 | Y2 | Cooling Load | Quantitative | 13.71, 14.45, 19.34 | 0 | + + +### Acknowledgement + + +This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Energy Efficiency Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Energy+efficiency).

+The UCI page mentions the following publication as the original source of the data set:

+[A. Tsanas, A. Xifara: 'Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools', Energy and Buildings, Vol. 49, pp. 560-567, 2012 (the paper can be accessed from](http://people.maths.ox.ac.uk/tsanas/Preprints/ENB2012.pdf).