GGobi

GGobi is a free statistical software tool for interactive data visualization. GGobi allows extensive exploration of the data with Interactive dynamic graphics. It is also a tool for looking at multivariate data. R can be used in sync with GGobi (through rggobi). The GGobi software can be embedded as a library in other programs and program packages using an application programming interface (API) (integration into a stand-alone application) or as an add-on to existing languages and scripting environments, e.g., with the R command line or from a Perl or Python scripts. GGobi prides itself on its ability to link multiple graphs together.^[2]

GGobi was created to look at data matrices. The designers were interested in exploring multi-dimensional data. The program developers went through many name changes before settling on GGobi (A combination of the words GTK+ and the Gobi Desert). The original concept, Dataviewer, began in the mid-80s, and a predecessor, XGobi, began in 1989. Work began on the current version of GGobi in 1999. The main reason for the different versions was the change in technology.^[3] Current version for MS Windows is 2.1.10a (12 March 2010) with an update for 64 bit usage from 10 June 2012.

Released under a combination of three free software licenses, GGobi is free software.^[1]

Looking at data through various graphs can reveal more information about the distribution than just looking at the numbers or a summary of them. Using the different tools within GGobi, clusters, non-linear distributions, outliers, and other important variations in the data can be discovered. GGobi is a program which allows exploratory data analysis to occur for multi-dimensional data.

GGobi can read CSV and XML file types.^[4]

• 1D: Average shifted histogram, textured dot plot, barchart, spineplot
• 2D: Scatterplot
• High-D:
  • Scatterplot matrix
  • Parallel coordinates
  • Grand tour, projection pursuit guided tour, manual tour
• Time series plot

These tools can be used to pick out special points or clusters of data.

• Brushing

As the brush moves over a point, the point will be highlighted.

If "persistent" is selected, the points the brush has moved over will remain "painted".

• Identify

As the cursor moves over a point, a label, or variable value will appear at the top of the graphic screen.

• Linking

Multiple plots are linked so identifying one point in one plot will identify the same point on all other graphs, and brushing a group of points in one plot will highlight the same points in other plots. The linking can be one-to-one, or according to the values of a categorical variable in the data set.

• Moving points

Points in a plot can be moved interactively, e.g. to gauge results from multidimensional scaling.

• Add/remove points or edges.

• Data visualization
• Mondrian data analysis

• Buja, A., D. Cook, and D.F. Swayne (March 1998). "XGobi: Interactive Dynamic Data Visualization in the X Window System". in: Journal of Computational and Graphical Statistics 7 (1): 113–130.
• Buja, A., D.T. Lang, and D.F. Swayne (August 28, 2003). "GGobi: Evolving From XGobi into an Extensible Framework for Interactive Data Visualization". In: Journal of Computational Statistics and Data Analysis 43 (4): 423–444.
• Cook, D. and D.F. Swayne (2007), with contributions from Andreas Buja, Duncan Temple Lang, Heike Hofmann, Hadley Wickham, and Michael Lawrence. Interactive and Dynamic Graphics for Data Analysis: With R and GGobi. DOI: 10.1007/978-0-387-71762-3, Springer-Verlag New York.

• GGobi Data Visualization System
• rggobi is an R package that interfaces R and GGobi.
• GGobi blog
• References to GGobi on the web include links at Humboldt University [1] Archived 2008-04-10 at the Wayback Machine, Ubuntu [2], Debian [3], Freshmeat [4], Hugh-Public [5], Softpedia [6].