Open main menu

Mondrian is a general-purpose statistical data-visualization system, for interactive data visualization. All plots in Mondrian are fully linked, and offer various interactions and queries. Any case selected in a plot in Mondrian is highlighted in all other plots.

DeveloperMartin Theus
First appeared1997
Stable release
1.2 / January 11, 2011; 8 years ago (2011-01-11)
OSWindows, macOS, Linux
LicenseGNU GPL 3+

Currently implemented plots comprise Mosaic Plot, Scatterplots and SPLOM, Maps, Barcharts, Histograms, Missing Value Plot, Parallel Coordinates/Boxplots and Boxplots y by x.[1]

Mondrian works with data in standard tab-delimited or comma-separated ASCII files and can load data from R workspaces. There is basic support for working directly on data in databases.

Mondrian links to R and offers statistical procedures like interactive density estimation, scatterplot smoothers, multidimensional scaling (MDS) and principal component analysis (PCA).



Starting in 1997, Mondrian was first developed with a focus on visualization techniques for categorical data and enhanced selection techniques. Over the years, a complete suite of visualizations for univariate and multivariate data measured on any scale were added. The link to R offers well tested statistical procedures, which integrate seamlessly into the interactive graphics. Today, even geographical data is supported with highly interactive maps.

Mondrian detailsEdit

Last stable and beta versions, help and documentations are available on the developer web site, Martin Theus

Supported data sourcesEdit

Mondrian works on plain text files with tab-separated columns with variable header, as exported from Microsoft Excel as ".txt". If the Rserve link and R are present, Mondrian also reads data directly from R workspace files (.RData files).


Interaction techniquesEdit

  • Query
  • Select
  • Modifiy

See alsoEdit


  1. ^ Theus, Martin (August 29, 2013). "Mondrian - Interactive Statistical Data Visualization in JAVA". Martin Theus. Retrieved January 3, 2015.

Further readingEdit

  • Theus, M. (2002). Interactive Data Visualization using Mondrian, in Journal of Statistical Software 7 (11): 1–9.
  • Theus, M. and Urbanek, S. (2008). Interactive Graphics for Data Analysis: Principles and Examples (Computer Science and Data Analysis), Chapman & Hall / CRC.

External linksEdit