miss_cat

var1

var2


<code>miss_cat</code> takes a data frame, df , and two variables as strings, var1 and var2, and converts them to a missing TRUE/FALSE matrix, where TRUE = missing. It then uses <code>interaction</code>, to create all the different levels of missingness - TRUE.TRUE, TRUE.FALSE, FALSE.TRUE, and FALSE.FALSE. It then uses the function <code>shadow_cat</code> to collapse across these and put them into the relevant categories


Missing values are ubiquitous in data and need to be explored and
handled in the initial stages of analysis. naniar provides helpers for
exploring missing data dependencies with minimal deviation from the common
workflows of ggplot and tidy data. naniar builds data structures and
functions that ensure missings are plotted easily and enables imputations
to be examined.

miss_cat: Create factor levels of missingness for two variables

Description

Usage

Arguments