cast_shadow_shift

Shift the values and add a shadow column. It also respects the dplyr
verbs <code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.

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

cast_shadow_shift function

<dl><dt>data</dt>
<dd>data.frame</dd>
<dt>...</dt>
<dd>One or more unquoted variable names separated by commas. These
respect the dplyr verbs <code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.</dd></dl>

Arguments

Add a shadow and a shadow_shift column to a dataset — cast_shadow_shift

<dl>

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


<dt>...</dt>
<dd>One or more unquoted variable names separated by commas. These
respect the dplyr verbs <code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.</dd>

</dl>

cast_shadow_shift: Add a shadow and a shadow_shift column to a dataset

Description

Usage

Value

Arguments

See Also

Examples