Regression data of the usage of rental bikes in Washington D.C., USA

This data set contains information on hourly bike sharing usage in Washington, D.C. for the years 2011-2012. The target variable is count, the total number of bikes lent out to users at a specific time.

Usage

data(bikes)

Format

An object of class data.frame with 727 rows and 11 columns.

Source

This is a subset of the original data, which can be found on the OpenML database (ID = 42712).

Details

This data frame contains the following columns:

season: Season of the year
year: Year; 0=2011, 1=2012
month: Month of the year
holiday: If a day is a public holiday (y/n)
weekday: Day of the week
workingday: If a day is aworking day (y/n)
weather: Weather situation
temp: Temperature in degrees celsius
humidity: Humidity (relative)
windspeed: Windspeed in miles per hour
count: Total number of bikes lent out to users

References

Fanaee-T, Hadi, and Gama, Joao, "Event labeling combining ensemble detectors and background knowledge", Progress in Artificial Intelligence (2013): pp. 1-15, Springer Berlin Heidelberg, doi:10.1007/s13748-013-0040-3.

Vanschoren, Joaquin, et al. "OpenML: networked science in machine learning." ACM SIGKDD Explorations Newsletter 15.2 (2014): 49-60.