make_missing

Randomly make values missing in all data columns, or a
subset of columns

For the purposes of teaching, it is often desirable to show
examples of working with messy data and how to clean it. This R package
creates messy data from clean, tidy data frames so that students have a
clean example to work towards.

Nicola Rennie

messy

Create Messy Data from Clean Data Frames

make_missing function

<dl><dt>data</dt>
<dd>input dataframe</dd>
<dt>cols</dt>
<dd>set of columns to apply transformation to. If <code>NULL</code>
will apply to all columns. Default <code>NULL</code>.</dd>
<dt>messiness</dt>
<dd>Percentage of values to change. Must be
between 0 and 1. Default 0.1.</dd>
<dt>missing</dt>
<dd>A single value, vector, or list of what the
missing values will be replaced with. If length is greater
than 1, values will be replaced randomly.
Default <code>NA</code>.</dd></dl>

Arguments

Make missing — make_missing

<dl>

<dt>data</dt>
<dd>input dataframe</dd>


<dt>cols</dt>
<dd>set of columns to apply transformation to. If <code>NULL</code>
will apply to all columns. Default <code>NULL</code>.</dd>


<dt>messiness</dt>
<dd>Percentage of values to change. Must be
between 0 and 1. Default 0.1.</dd>


<dt>missing</dt>
<dd>A single value, vector, or list of what the
missing values will be replaced with. If length is greater
than 1, values will be replaced randomly.
Default <code>NA</code>.</dd>

</dl>

make_missing: Make missing

Description

Usage

Value

Arguments

Examples