Visualizing Missingness and Data Quality

r

missing_by_variable <- prepared_data |>
  summarise(
    consent_date = sum(is.na(consent_date)),
    age_years = sum(is.na(age_years_derived)),
    day28_outcome = sum(is.na(day28_outcome)),
    discharge_date = sum(is.na(discharge_date))
  ) |>
  pivot_longer(
    cols = everything(),
    names_to = "variable",
    values_to = "missing_count"
  )

missing_by_variable |>
  ggplot(aes(x = reorder(variable, missing_count), y = missing_count)) +
  geom_col() +
  coord_flip() +
  labs(
    title = "Missing Values in Key Variables",
    x = "Variable",
    y = "Missing records"
  )