Seoul Bike Sharing Demand

Donated on 2/29/2020

The dataset contains count of public bicycles rented per hour in the Seoul Bike Sharing System, with corresponding weather data and holiday information

Dataset Characteristics

Multivariate

Subject Area

Business

Associated Tasks

Regression

Feature Type

Integer, Real

# Instances

8760

# Features

13

Dataset Information

Additional 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.

Has Missing Values?

No

Variables Table

Variable NameRoleTypeDescriptionUnitsMissing Values
DateFeatureDateno
Rented Bike CountFeatureIntegerno
HourFeatureIntegerno
TemperatureFeatureContinuousCno
HumidityFeatureInteger%no
Wind speedFeatureContinuousm/sno
VisibilityFeatureInteger10mno
Dew point temperatureFeatureContinuousCno
Solar RadiationFeatureContinuousMj/m2no
RainfallFeatureIntegermmno

0 to 10 of 14

Additional Variable Information

Date : year-month-day Rented Bike count - Count of bikes rented at each hour Hour - Hour of he day Temperature-Temperature in Celsius Humidity - % Windspeed - m/s Visibility - 10m Dew point temperature - Celsius Solar radiation - MJ/m2 Rainfall - mm Snowfall - cm Seasons - Winter, Spring, Summer, Autumn Holiday - Holiday/No holiday Functional Day - NoFunc(Non Functional Hours), Fun(Functional hours)

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