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GGobi
Statistical software package From Wikipedia, the free encyclopedia
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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]
![]() | This article includes a list of general references, but it lacks sufficient corresponding inline citations. (January 2011) |
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Overview
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]
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GGobi Topics
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Importance of graphics
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.
Supported data sources
Types of graphics
- 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
Interactions
These tools can be used to pick out special points or clusters of data.
- 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.
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See also
References
Further reading
External links
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