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+Data Science Dojo
+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
+
+
+---
+
+---
+
+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).