tests/testthat/_snaps/as_shadow_upset.md

In njtierney/naniar: Data Structures, Summaries, and Visualisations for Missing Data

as_shadow_upset errors when given datasets with <= 1 variables

Code
  as_shadow_upset(diag_na(1))
Condition
  Error in `as_shadow_upset()`:
  ! upset plots for missing data requre at least two variables to have missing data, only one variable, 'x1' has missing values.

Code
  as_shadow_upset(data.frame(x = NA))
Condition
  Error in `as_shadow_upset()`:
  ! upset plots for missing data requre at least two variables to have missing data, only one variable, 'x' has missing values.

Code
  as_shadow_upset(data.frame(numeric(0)))
Condition
  Error in `as_shadow_upset()`:
  ! upset plots for missing data requre at least two variables to have missing data, there are no missing values in your data! This is probably a good thing.

as_shadow_upset errors when given non dataframe or 0 entry

Code
  as_shadow_upset(0)
Condition
  Error in `colSums()`:
  ! 'x' must be an array of at least two dimensions

Code
  as_shadow_upset("a")
Condition
  Error in `colSums()`:
  ! 'x' must be an array of at least two dimensions

Code
  as_shadow_upset(matrix(airquality))
Condition
  Error in `as_shadow_upset()`:
  ! upset plots for missing data requre at least two variables to have missing data, there are no missing values in your data! This is probably a good thing.

Code
  as_shadow_upset(NULL)
Condition
  Error in `colSums()`:
  ! 'x' must be an array of at least two dimensions

njtierney/naniar documentation built on March 19, 2024, 9:48 p.m.