bike_demand: Seoul Bike Sharing Demand Data

In liver: Toolkit and Datasets for Data Science

Seoul Bike Sharing Demand Data

Description

A dataset containing hourly bike rental demand in Seoul, South Korea, together with weather conditions, seasonal information, holiday status, and whether the bike sharing system was operating on that day.

Usage

data(bike_demand)

Format

A data frame with 8760 observations and 14 variables:

date

Date of observation.

hour

Hour of the day, ranging from 0 to 23.

temperature

Temperature in degrees Celsius.

humidity

Humidity percentage.

wind_speed

Wind speed in meters per second.

visibility

Visibility in units recorded by the source dataset.

dew_point_temperature

Dew point temperature in degrees Celsius.

solar_radiation

Solar radiation in megajoules per square meter.

rainfall

Rainfall in millimeters.

snowfall

Snowfall in centimeters.

season

Season of the year: "spring", "summer", "autumn", or "winter".

holiday

Holiday status: "holiday" or "no holiday".

functioning_day

Whether the bike rental system was operating: "yes" or "no".

bike_count

Number of rented bikes (target variable).

Details

This dataset was obtained from the UCI Machine Learning Repository and renamed bike_demand for inclusion in the liver package. It can be used to illustrate methods for regression, exploratory data analysis, and predictive modeling in R.

Source

https://archive.ics.uci.edu/dataset/560/seoul+bike+sharing+demand

References

Reza Mohammadi (2025). Data Science Foundations and Machine Learning with R: From Data to Decisions. https://book-data-science-r.netlify.app.

See Also

mortgage, bank, churn_mlc, churn, churn_tel, adult, cereal, advertising, marketing, drug, house, house_price, red_wines, white_wines, insurance, caravan, fertilizer, corona

Examples

data(bike_demand)

str(bike_demand)
summary(bike_demand)

liver documentation built on April 7, 2026, 9:07 a.m.