Seoul Bike Sharing Demand
About
The dataset contains count of public bicycles rented per hour in the Seoul Bike Sharing System, with corresponding weather data and holiday information
Currently Rental bikes are introduced in many urban cities for the enhancement of mobility comfort. It is important to make the rental bike available and accessible to the public at the right time as it lessens the waiting time. Eventually, providing the city with a stable supply of rental bikes becomes a major concern. The crucial part is the prediction of bike count required at each hour for the stable supply of rental bikes.
The dataset contains weather information (Temperature, Humidity, Windspeed, Visibility, Dewpoint, Solar radiation, Snowfall, Rainfall), the number of bikes rented per hour and date information.
Subject Area
Business
Instances
8,760
Features
14
Data Types
Multivariate
Tasks
Regression
Feature Types
Integer, Continuous
Features
| Name | Role | Type | Units | Missing Values |
|---|---|---|---|---|
| Date | Feature | Date | - | No |
| Rented Bike Count | Feature | Integer | - | No |
| Hour | Feature | Integer | - | No |
| Temperature | Feature | Continuous | C | No |
| Humidity | Feature | Integer | % | No |
| Wind speed | Feature | Continuous | m/s | No |
| Visibility | Feature | Integer | 10m | No |
| Dew point temperature | Feature | Continuous | C | No |
| Solar Radiation | Feature | Continuous | Mj/m2 | No |
| Rainfall | Feature | Integer | mm | No |
| Snowfall | Feature | Integer | cm | No |
| Seasons | Feature | Categorical | - | No |
| Holiday | Feature | Binary | - | No |
| Functioning Day | Target | Binary | - | No |
Introductory Paper
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