e_cat

Barplot for categoric variable by clusters.

Performs an exploratory data analysis through a 'shiny' interface. It includes basic methods such as the mean, median, mode, normality test, among others. It also includes clustering techniques such as Principal Components Analysis, Hierarchical Clustering and the K-Means Method.

Oldemar Rodriguez

discoveR

Exploratory Data Analysis System

Diego Jiménez

e_cat function

<dl><dt>clusters</dt>
<dd>a vector specifying the cluster of each individual.</dd>
<dt>var</dt>
<dd>a factor column of a data.frame.</dd>
<dt>colores</dt>
<dd>a vector of color for each cluster.</dd>
<dt>escalar</dt>
<dd>a boolean value specifying if use percentage or real values.</dd></dl>

Arguments

Diego Jimenez &lt;diego.jimenez@promidat.com&gt;

Author

Barplot for categoric variable by clusters. — e_cat

<dl>

<dt>clusters</dt>
<dd>a vector specifying the cluster of each individual.</dd>


<dt>var</dt>
<dd>a factor column of a data.frame.</dd>


<dt>colores</dt>
<dd>a vector of color for each cluster.</dd>


<dt>escalar</dt>
<dd>a boolean value specifying if use percentage or real values.</dd>

</dl>

e_cat: Barplot for categoric variable by clusters.

Description

Usage

Value

Arguments

Author

Examples