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Data Science Dojo <br/>
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Copyright (c) 2019 - 2020
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**Level** Intermediate <br/>
**Recommended Use:** Classification Models<br/>
**Domain:** Energy/Buildings<br/> 

## Occupancy Detection Data Set 

### Detect Occupancy through Light, Temperature, Humidity and CO2 sensors


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![](O6YGSH0.jpg)
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This *intermediate* level data set has 20560 rows and 7 attributes which are divided into 3 data sets for training and testing.
The data set provides experimental data used for binary classification (room occupancy of an office room) from Temperature, Humidity, Light and CO2. 
Ground-truth occupancy was obtained from time stamped pictures that were taken every minute.
This data set is recommended for learning and practicing your skills in **exploratory data analysis**, **data visualization**, 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:

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### Data Dictionary 

| Column   Position 	| Atrribute Name 	| Definition                                                                                           	| Data Type    	| Example                                        	| % Null Ratios 	|
|-------------------	|----------------	|------------------------------------------------------------------------------------------------------	|--------------	|------------------------------------------------	|---------------	|
| 1                 	| Date           	| Date & time in year-month-day hour:minute:second format                                              	| Qualitative  	| 2/4/2015 17:57, 2/4/2015 17:55, 2/4/2015 18:06		 	| 0             	|
| 2                 	| Temperature    	| Temperature in degree Celcius                                                                        	| Quantitative 	| 23.150, 23.075, 22.890                         	| 0             	|
| 3                 	| Humidity       	| Relative humidity in percentage                                                                      	| Quantitative 	| 27.272000, 27.200000, 27.390000                	| 0             	|
| 4                 	| Light          	| Illuminance measurement in unit Lux                                                                  	| Quantitative 	| 426.0, 419.0, 0.0	                              	| 0             	|
| 5                 	| CO2            	| CO2 in parts per million (ppm)                                                                       	| Quantitative 	| 489.666667,   495.500000, 534.500000           	| 0             	|
| 6                 	| HumidityRatio  	| Humadity ratio:  Derived quantity from temperature and   relative humidity, in kgwater-vapor/kg-air  	| Quantitative 	| 0.004986, 0.005088, 0.005203                   	| 0             	|
| 7                 	| Occupancy      	| Occupied or not: 1 for occupied and 0 for not occupied                                               	| Quantitative 	| 1, 0                                           	| 0             	|


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### Acknowledgement


This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Occupancy Detection Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Occupancy+Detection+#). The UCI page mentions the following publication [Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models. Luis M. Candanedo, Véronique Feldheim. Energy and Buildings. Volume 112, 15 January 2016, Pages 28-39](https://www.researchgate.net/profile/Luis_Candanedo_Ibarra/publication/285627413_Accurate_occupancy_detection_of_an_office_room_from_light_temperature_humidity_and_CO2_measurements_using_statistical_learning_models/links/5b1d843ea6fdcca67b690c28/Accurate-occupancy-detection-of-an-office-room-from-light-temperature-humidity-and-CO2-measurements-using-statistical-learning-models.pdf?origin=publication_detail) as the original source of the data set.