## code to prepare `diabetes` dataset goes here
set.seed(329)
data("Diabetes", package = 'Publish')
#library(tidyverse)
diab_complete <- diab_missing <- as_tibble(Diabetes) %>%
select(-id, -bp.2s, -bp.2d, -AgeGroups, -BMI) %>%
rename(
sbp = bp.1s,
dbp = bp.1d,
height_cm = height.europe,
weight_kg = weight.europe,
time_ppn = time.ppn,
stable_glucose = stab.glu
) %>%
mutate(diabetes = as.numeric(glyhb > 7)) %>%
select(-glyhb, -location, -ratio, -height, -weight) %>%
drop_na()
rows <- sample(nrow(diab_complete), 200)
for(i in rows){
cols <- sample(ncol(diab_complete)-1, size = ncol(diab_complete) - 5)
diab_missing[i, cols] <- NA
}
diab_complete %<>%
as_tibble() %>%
mutate(diabetes = factor(diabetes, labels = c("No", "Yes"))) %>%
select(diabetes, everything())
diab_missing %<>%
as_tibble() %>%
mutate(diabetes = factor(diabetes, labels = c("No", "Yes"))) %>%
select(diabetes, everything())
diabetes <- list(
complete = diab_complete,
missing = diab_missing
)
usethis::use_data(diabetes, overwrite = TRUE)
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