label_shadow

data

character a label for when values are missing - defaults to "Missing"

missing

character character a label for when values are complete - defaults to "Not Missing"

complete

Powers <code>add_label_shadow</code>. For the moment it is an internal function.

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.
The work is fully discussed at Tierney & Cook (2018) <arXiv:1809.02264>.

Nicholas Tierney

naniar

Data Structures, Summaries, and Visualisations for Missing Data

Di Cook

Miles McBain

Colin Fay

Mitchell O'Hara-Wild

Jim Hester

Luke Smith

Andrew Heiss

label_shadow function

<dl><dt>data</dt>
<dd>data.frame</dd>
<dt>...</dt>
<dd>extra variable to label</dd>
<dt>missing</dt>
<dd>character a label for when values are missing - defaults to "Missing"</dd>
<dt>complete</dt>
<dd>character character a label for when values are complete - defaults to "Not Missing"</dd></dl>

Arguments

Label shadow values as missing or not missing — label_shadow

<dl>

<dt>data</dt>
<dd>data.frame</dd>


<dt>...</dt>
<dd>extra variable to label</dd>


<dt>missing</dt>
<dd>character a label for when values are missing - defaults to "Missing"</dd>


<dt>complete</dt>
<dd>character character a label for when values are complete - defaults to "Not Missing"</dd>

</dl>

label_shadow: Label shadow values as missing or not missing

Description

Usage

Value

Arguments