add_n_miss

data

Variable names to use instead of the whole dataset. By default this
looks at the whole dataset. Otherwise, this is one or more unquoted
expressions separated by commas. These also respect the dplyr verbs
<code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc. By default will add "_all" to
the label if left blank, otherwise will add "_vars" to distinguish that it
has not been used on all of the variables.

label

It can be useful when doing data analysis to add the number of missing data
points into your dataframe. <code>add_n_miss</code> adds a column named "n_miss",
which contains the number of missing values in that row.

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

add_n_miss function

<dl><dt>data</dt>
<dd>a dataframe</dd>
<dt>...</dt>
<dd>Variable names to use instead of the whole dataset. By default this
looks at the whole dataset. Otherwise, this is one or more unquoted
expressions separated by commas. These also respect the dplyr verbs
<code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc. By default will add "_all" to
the label if left blank, otherwise will add "_vars" to distinguish that it
has not been used on all of the variables.</dd>
<dt>label</dt>
<dd>character default is "n_miss".</dd></dl>

Arguments

Add column containing number of missing data values — add_n_miss

<dl>

<dt>data</dt>
<dd>a dataframe</dd>


<dt>...</dt>
<dd>Variable names to use instead of the whole dataset. By default this
looks at the whole dataset. Otherwise, this is one or more unquoted
expressions separated by commas. These also respect the dplyr verbs
<code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc. By default will add "_all" to
the label if left blank, otherwise will add "_vars" to distinguish that it
has not been used on all of the variables.</dd>


<dt>label</dt>
<dd>character default is "n_miss".</dd>

</dl>

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add_n_miss: Add column containing number of missing data values

Description

Usage

Value

Arguments

See Also

Examples