Data on ridership among registered members and casual users of the Capital Bikeshare service in Washington, D.C..

bike_users

Format

A data frame with 534 daily observations, 267 each for registered riders and casual riders, and 13 variables:

date

date of observation

season

fall, spring, summer, or winter

year

the year of the date

month

the month of the date

day_of_week

the day of the week

weekend

whether or not the date falls on a weekend (TRUE or FALSE)

holiday

whether or not the date falls on a holiday (yes or no)

temp_actual

raw temperature (degrees Fahrenheit)

temp_feel

what the temperature feels like (degrees Fahrenheit)

humidity

humidity level (percentage)

windspeed

wind speed (miles per hour)

weather_cat

weather category (categ1 = pleasant, categ2 = moderate, categ3 = severe)

user

rider type (casual or registered)

rides

number of bikeshare rides

Source

Fanaee-T, Hadi and Gama, Joao (2013). Event labeling combining ensemble detectors and background knowledge. Progress in Artificial Intelligence. https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset/