R/data_bike_users.R

In bayesrules: Datasets and Supplemental Functions from Bayes Rules! Book

#' Capital Bikeshare Bike Ridership (Registered and Casual Riders)
#' 
#' Data on ridership among registered members and casual users of the Capital Bikeshare service in Washington, D.C..
#' 
#' @format A data frame with 534 daily observations, 267 each for registered riders and casual riders, and 13 variables:
#' \describe{
#'   \item{date}{date of observation}
#'   \item{season}{fall, spring, summer, or winter}
#'   \item{year}{the year of the date}
#'   \item{month}{the month of the date}
#'   \item{day_of_week}{the day of the week}
#'   \item{weekend}{whether or not the date falls on a weekend (TRUE or FALSE)}
#'   \item{holiday}{whether or not the date falls on a holiday (yes or no)}
#'   \item{temp_actual}{raw temperature (degrees Fahrenheit)}
#'   \item{temp_feel}{what the temperature feels like (degrees Fahrenheit)}
#'   \item{humidity}{humidity level (percentage)}
#'   \item{windspeed}{wind speed (miles per hour)}
#'   \item{weather_cat}{weather category (categ1 = pleasant, categ2 = moderate, categ3 = severe)}
#'   \item{user}{rider type (casual or registered)}
#'   \item{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. \url{https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset/}
"bike_users"