all-is-miss-complete

all_na

all_miss

all_complete

This is shorthand for <code>all(is.na(x))</code> and <code>all(!is.na(x))</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

all-is-miss-complete function

<dl><dt>x</dt>
<dd>an R object to be tested.</dd></dl>

Arguments

Identify if all values are missing or complete — all-is-miss-complete

<dl>

<dt>x</dt>
<dd>an R object to be tested.</dd>

</dl>

Identify if all values are missing or complete

all-is-miss-complete: Identify if all values are missing or complete

Description

Usage

Arguments

Examples