AssociationExplorer: an easy-to-use glossy application for exploring associations and visual patterns | R bloggers

Why AssociationExplorer?

Exploring multivariate datasets is now central to the social sciences, data journalism and education. However, identifying and interpreting relationships between variables often requires programming skills and a solid background in statistics, which can be a significant barrier for many users.

AssociationExplorer is designed to lower this barrier by providing an interactive, visual, and statistically based tool for exploring associations between quantitative and qualitative variables, without requiring users to write code.

The application is primarily intended for:

• journalists and data journalism practitioners,
• teachers and students,
• researchers in the exploratory phase of an analysis,
• engaged citizens interested in understanding public or survey data.

What does the app do?

AssociationExplorer follows a simple and guided workflow:

• Import data (CSV or Excel files)
• Interactively select variables of interest
• Automatically calculate association measures adapted to variable types:
  • Pearson’s \(R\) correlation for numeric-numeric pairs,
  • Cramer’s V for categorical-categorical pairs,
  • the correlation ratio \(\And\) for mixed numerical-categorical pairs
• Filter associations using user-defined thresholds
• Visualize results by:
  • an interactive correlation network,
  • contextual bivariate visualizations (scatter plots, mean plots and colored crosstabs)

This workflow is designed to support transparent, reactive, and interpretable exploratory data analysis.

An article published in SoftwareX

The SoftwareX paper provides a detailed description of:

• the motivation and intended audience of the tool,
• the software architecture,
• the methodological choices underlying the association measures,
• an illustrative case study based on the European Social Survey,
• and prospects for future development.

Link to the paper: https://doi.org/10.1016/j.softx.2025.102483

In accordance with the journal’s standards, the code, documentation, and sample data are fully open and reproducible.

The R package is also on CRAN

In addition to the paper, an R package is also available on CRAN, making installation and use easy:

install.packages("AssociationExplorer2")
library(AssociationExplorer2)
run_associationexplorer()

The CRAN release ensures:

• standardized installation,
• better integration with existing R workflows,
• clearer version control and dependency management.

Who is it for and how can it be used?

AssociationExplorer is especially useful for:

• exploratory analysis prior to formal modeling,
• educational concepts related to association and dependence,
• data storytelling and journalistic exploration,
• the analysis of survey data and public datasets.

The goal is not to replace confirmatory statistical analysis, but to provide a robust tool for understanding the structure of the data before modeling.

Acknowledgments

This work was carried out in collaboration with Cédric Heuchenne, Arnaud Claes and Antonin Descampe, to whom I would like to thank.

The project is supported by the Walloon Region and SPW Recherche within the ODALON research project.

Useful links

As always, feedback, bug reports and suggestions are very welcome.

Thanks for reading!

References

Soetewey, A., Heuchenne, C., Claes, A. and Descampe, A. (2026). AssociationExplorer: an easy-to-use glossy application for exploring associations and visual patterns. SoftwareX, 33(102483). https://doi.org/10.1016/j.softx.2025.102483

Soetewey, A., Heuchenne, C., Claes, A. and Descampe, A. (2025). AssociationExplorer2: an easy-to-use ‘shiny’ application for exploring associations and visual patterns. R package version 0.1.4, https://github.com/AntoineSoetewey/AssociationExplorer2