% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data-climber_drugs.R
\docType{data}
\name{climber_drugs}
\alias{climber_drugs}
\title{Climber Drugs Data.}
\format{
A data frame with 211 rows and 6 variables.
\describe{
\item{positive_sample}{Idendification number of a specific urine sample.}
\item{hut}{Location where the sample was taken.}
\item{substance}{Substance detected to be present in the urine sample.}
\item{concentration}{Amount of substance found measured in ng/ml.}
\item{screening_analysis}{Indicates that the concentration was determined by screening analysis.}
\item{concomitant}{Indicates that this substance was always detected concomitantly with the previous one, within the same urine sample.}
}
}
\source{
\href{https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0156786#sec012}{PLOS One - Drug Use on Mont Blanc: A Study Using Automated Urine Collection}
}
\usage{
climber_drugs
}
\description{
Anonymous data was collected from urine samples at huts along the climb of Mont Blanc. Several types of drugs were tested, and proportions were reported.
}
\examples{
library(dplyr)

# Calculate the average concentration of each substance and number of occurrences.
climber_drugs |>
  group_by(substance) |>
  summarize(count = n(), mean_con = mean(concentration))

# Proportion samples in which each substance was detected.
climber_drugs |>
  group_by(substance) |>
  summarize(prop = n() / 154)

}
\keyword{datasets}
