Bike Sharing Regression Project Source: https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset Data Set Information:
Bike sharing systems are a new generation of traditional bike rentals where the whole process from membership, rental and return back has become automatic. Through these systems, users are able to easily rent a bike from a particular position and return back at another position. Currently, there are about over 500 bike-sharing programs around the world which is composed of over 500 thousands bicycles. Today, there exists great interest in these systems due to their important role in traffic, environmental and health issues.Apart from interesting real world applications of bike sharing systems, the characteristics of data being generated by these systems make them attractive for the research. Opposed to other transport services such as bus or subway, the duration of travel, departure and arrival position is explicitly recorded in these systems. This feature turns the bike sharing system into a virtual sensor network that can be used for sensing mobility in the city. Hence, it is expected that most of the important events in the city could be detected via monitoring these data.
Data Columns Description:
● datetime - hourly date + timestamp
● season - 1 = spring, 2 = summer, 3 = fall, 4 = winter
● holiday - whether the day is considered a holiday
● workingday - whether the day is neither a weekend nor holiday
● weather -
○ 1: Clear, Few clouds, Partly cloudy, Partly cloudy
○ 2: Mist + Cloudy, Mist + Broken clouds, Mist + Few clouds, Mist
○ 3: Light Snow, Light Rain + Thunderstorm + Scattered clouds, Light Rain + Scattered clouds
○ 4: Heavy Rain + Ice Pallets + Thunderstorm + Mist, Snow+ Fog
● temp - temperature in Celsius
● atemp - "feels like" temperature in Celsius
● humidity - relative humidity
● windspeed - wind speed
● casual - number of non-registered user rentals initiated
● registered - number of registered user rentals initiated
● count - number of total rentals (Dependent Variable