impute_below_if

<code>impute_below</code> operates on all variables. To only impute variables
that satisfy a specific condition, use the scoped variants,
<code>impute_below_at</code>, and <code>impute_below_if</code>.

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 (2023)
<doi:10.18637/jss.v105.i07>.

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

impute_below_if function

<dl><dt>.tbl</dt>
<dd>data.frame</dd>
<dt>.predicate</dt>
<dd>A predicate function (such as is.numeric)</dd>
<dt>prop_below</dt>
<dd>the degree to shift the values. default is</dd>
<dt>jitter</dt>
<dd>the amount of jitter to add. default is 0.05</dd>
<dt>...</dt>
<dd>extra arguments</dd></dl>

Arguments

Scoped variants of impute_below — impute_below_if

<dl>

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


<dt>.predicate</dt>
<dd>A predicate function (such as is.numeric)</dd>


<dt>prop_below</dt>
<dd>the degree to shift the values. default is</dd>


<dt>jitter</dt>
<dd>the amount of jitter to add. default is 0.05</dd>


<dt>...</dt>
<dd>extra arguments</dd>

</dl>

impute_below_if: Scoped variants of `impute_below`

Description

Usage

Value

Arguments

Examples