label_shadow_matrix

<p>Returns a binary factor of !NA and NA, where !NA indicates a datum that is
not missing, and NA indicates missingness. This function is what powers the
factor levels in <code>as_shadow()</code>.</p>

Missing values are ubiquitous in data and need to be explored and
handled in the initial stages of analysis. 'naniar' provides data structures
and functions that facilitate the plotting of missing values and examination
of imputations. This allows missing data dependencies to be explored with
minimal deviation from the common work patterns of 'ggplot2' and tidy data.

Nicholas Tierney

naniar

Data Structures, Summaries, and Visualisations for Missing Data

Di Cook

Miles McBain

Colin Fay

Jim Hester

Luke Smith

label_shadow_matrix function

Give NAs a more meaningful label — label_shadow_matrix

Give NAs a more meaningful label

label_shadow_matrix: Give NAs a more meaningful label

Description

Usage

Arguments

Value

See Also

Examples