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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.

Usage

climber_drugs

Format

A data frame with 211 rows and 6 variables.

positive_sample

Idendification number of a specific urine sample.

hut

Location where the sample was taken.

substance

Substance detected to be present in the urine sample.

concentration

Amount of substance found measured in ng/ml.

screening_analysis

Indicates that the concentration was determined by screening analysis.

concomitant

Indicates that this substance was always detected concomitantly with the previous one, within the same urine sample.

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))
#> # A tibble: 33 × 3
#>    substance       count mean_con
#>    <chr>           <int>    <dbl>
#>  1 Acetazolamide      78   30385.
#>  2 Anastrozole         1     250 
#>  3 Benzoylecgonine     3     181.
#>  4 Betamethasone       3      25 
#>  5 Betaxolol           2     201 
#>  6 Bisoprolol          1      64 
#>  7 Bromazepam          1      23 
#>  8 Brotizolam          1       1 
#>  9 Budesonide          2      15 
#> 10 Caffeine            4    7725 
#> # … with 23 more rows

# Proportion samples in which each substance was detected.
climber_drugs %>%
  group_by(substance) %>%
  summarize(prop = n() / 154)
#> # A tibble: 33 × 2
#>    substance          prop
#>    <chr>             <dbl>
#>  1 Acetazolamide   0.506  
#>  2 Anastrozole     0.00649
#>  3 Benzoylecgonine 0.0195 
#>  4 Betamethasone   0.0195 
#>  5 Betaxolol       0.0130 
#>  6 Bisoprolol      0.00649
#>  7 Bromazepam      0.00649
#>  8 Brotizolam      0.00649
#>  9 Budesonide      0.0130 
#> 10 Caffeine        0.0260 
#> # … with 23 more rows