Data Science Dojo
Copyright (c) 2016 - 2019 --- **Level** Intermediate
**Recommended Use:** Classification Models
**Domain:** Energy/Buildings
## Occupancy Detection Data Set ### Detect Occupancy through Light, Temperature, Humidity and CO2 sensors --- ![](O6YGSH0.jpg) --- 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: --- ### 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 | --- ### 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, VÃ©ronique 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.