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appointments.R
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appointments.R
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#' Medical appointment no shows
#'
#' Predicting no-show medical appointments
#'
#' @source
#' Joni Hoppen, Kaggle Medical Appointment No Shows
#' \href{https://www.kaggle.com/joniarroba/noshowappointments}{https://www.kaggle.com/joniarroba/noshowappointments}.
#'
#' @format A data frame with 110527 rows and 14 variables:
#' \describe{
#' \item{\code{PatientId}}{double. Identification of a patient.}
#' \item{\code{AppointmentID}}{double. dentification of each appointment.}
#' \item{\code{Gender}}{factor. \code{Male, Female}.}
#' \item{\code{ScheduledDay}}{datatime. The day and time of the actual appointment,
#' when they have to visit the doctor.}
#' \item{\code{AppointmentDay}}{double. The day someone called or
#' registered the appointment, this is before appointment of course.}
#' \item{\code{Age}}{double. Age of the patient.}
#' \item{\code{Neighbourhood}}{character. Where the appointment takes place.}
#' \item{\code{Scholarship}}{integer. \code{0=FALSE, 1=TRUE}. Scholarship
#' is a social welfare program providing financial aid to poor Brazilian families.}
#' \item{\code{Hypertension}}{integer. \code{0=FALSE, 1=TRUE}.}
#' \item{\code{Diabetes}}{integer. \code{0=FALSE, 1=TRUE}.}
#' \item{\code{Alcoholism}}{integer. \code{0=FALSE, 1=TRUE}.}
#' \item{\code{Handcap}}{integer. \code{0=FALSE, 1=TRUE}.}
#' \item{\code{SMS_received}}{integer. \code{0=FALSE, 1=TRUE}.
#' 1 or more messages sent to the patient.}
#' \item{\code{No_show}}{factor. \code{Yes, No.}}
#' }
#' @details
#' This Kaggle competition was designed to challenge participants to
#' predict office no-shows. It is also a good dataset to practice
#' date and time manipulation.
#' @examples
#' summary(appointments)
"appointments"