miss

Get a synthetic table of missing values for all columns of a data.frame

A set of concise and efficient tools for statistical production. Can also be used for data management.
In statistical production, you deal with complex data and need to control your process at each step of your work.
Concise functions are very helpful, because you do not hesitate to use them.
The following functions are included in the package.
'dup'  checks duplicates.
'miss' checks missing values.
'tac' computes contingency table of all columns.
'toc' compares two tables, spotting significant deviations.
'chi2_find' compares columns within a data.frame, spotting related categories of (a more complex function).

Vincent Reduron

ProduceR

Concise and Efficient Tools for Everyday Statistical Production

miss function

<dl><dt>df</dt>
<dd>data.frame: Input data.frame</dd>
<dt>values</dt>
<dd>column: Variable (~weight) to measure the number of missing values (otherwise, count of rows)</dd>
<dt>view</dt>
<dd>boolean: Display a glimpse of cases with NA values</dd></dl>

Arguments

Missing: Generate a synthetic table of missing values for all columns of a data.frame — miss

<dl>

<dt>df</dt>
<dd>data.frame: Input data.frame</dd>


<dt>values</dt>
<dd>column: Variable (~weight) to measure the number of missing values (otherwise, count of rows)</dd>


<dt>view</dt>
<dd>boolean: Display a glimpse of cases with NA values</dd>

</dl>

miss: Missing: Generate a synthetic table of missing values for all columns of a data.frame

Description

Usage

Value

Arguments

Examples