plot_correlation

Correlation heatmap with optional labels and triangle filtering.

The natural increase in the complexity of current research experiments and data demands better tools to enhance productivity in Data Analytics. The package is a framework designed to address the modern challenges in data analytics workflows. The package is inspired by Experiment Line concepts. It aims to provide seamless support for users in developing their data mining workflows by offering a uniform data model and method API. It enables the integration of various data mining activities, including data preprocessing, classification, regression, clustering, and time series prediction. It also offers options for hyper-parameter tuning and supports integration with existing libraries and languages. Overall, the package provides researchers with a comprehensive set of functionalities for data science, promoting ease of use, extensibility, and integration with various tools and libraries. Information on Experiment Line is based on Ogasawara et al. (2009) <doi:10.1007/978-3-642-02279-1_20>.

Eduardo Ogasawara

daltoolbox

Leveraging Experiment Lines to Data Analytics

Ana Carolina Sá

Antonio Castro

Caio Santos

Diego Carvalho

Diego Salles

Eduardo Bezerra

Esther Pacitti

Fabio Porto

Janio Lima

Lucas Tavares

Rafaelli Coutinho

Rebecca Salles

Vinicius Saidy

CEFET/RJ 

plot_correlation function

<dl><dt>df</dt>
<dd>data.frame with numeric columns</dd>
<dt>vars</dt>
<dd>optional vector of column names to include</dd>
<dt>method</dt>
<dd>correlation method: "pearson", "spearman", or "kendall"</dd>
<dt>use</dt>
<dd>handling of missing values for <code><a href="/link/stats%3A%3Acor?package=daltoolbox&version=1.3.717" data-mini-rdoc="daltoolbox::stats::cor">stats::cor</a></code></dd>
<dt>triangle</dt>
<dd>which triangle to show: "full", "upper", or "lower"</dd>
<dt>reorder</dt>
<dd>reordering strategy: "none", "hclust", or "alphabetical"</dd>
<dt>digits</dt>
<dd>number of digits for labels</dd>
<dt>label_size</dt>
<dd>size of label text</dd>
<dt>tile_color</dt>
<dd>border color for tiles</dd>
<dt>show_diag</dt>
<dd>whether to show the diagonal</dd>
<dt>title</dt>
<dd>optional plot title</dd></dl>

Arguments

Plot correlation — plot_correlation

<dl>

<dt>df</dt>
<dd>data.frame with numeric columns</dd>


<dt>vars</dt>
<dd>optional vector of column names to include</dd>


<dt>method</dt>
<dd>correlation method: "pearson", "spearman", or "kendall"</dd>


<dt>use</dt>
<dd>handling of missing values for <code><a href='https://rdrr.io/r/stats/cor.html'>stats::cor</a></code></dd>


<dt>triangle</dt>
<dd>which triangle to show: "full", "upper", or "lower"</dd>


<dt>reorder</dt>
<dd>reordering strategy: "none", "hclust", or "alphabetical"</dd>


<dt>digits</dt>
<dd>number of digits for labels</dd>


<dt>label_size</dt>
<dd>size of label text</dd>


<dt>tile_color</dt>
<dd>border color for tiles</dd>


<dt>show_diag</dt>
<dd>whether to show the diagonal</dd>


<dt>title</dt>
<dd>optional plot title</dd>

</dl>

Plot correlation

plot_correlation: Plot correlation

Description

Usage

Value

Arguments

Details

Examples