Contingency table (tac) of all columns in a dataframe for control purposes

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

tac function

<dl><dt>df</dt>
<dd>Input data.frame</dd>
<dt>values</dt>
<dd>Vector of columns that serve as measures (amounts, counts, etc.)</dd>
<dt>sample_rate</dt>
<dd>Sampling rate, if df is a remote table</dd>
<dt>num_but_discrete</dt>
<dd>Vector of names of numeric columns with discrete modalities (not continuous)</dd>
<dt>strates</dt>
<dd>Vector of column names by which to stratify the contingency tables</dd></dl>

Arguments

Computes a contingency table (tac) of all columns in a dataframe for control purposes — tac

<dl>

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


<dt>values</dt>
<dd>Vector of columns that serve as measures (amounts, counts, etc.)</dd>


<dt>sample_rate</dt>
<dd>Sampling rate, if df is a remote table</dd>


<dt>num_but_discrete</dt>
<dd>Vector of names of numeric columns with discrete modalities (not continuous)</dd>


<dt>strates</dt>
<dd>Vector of column names by which to stratify the contingency tables</dd>

</dl>

tac: Computes a contingency table (tac) of all columns in a dataframe for control purposes

Description

Usage

Value

Arguments

Examples