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In parallel coordinates, each axis can have at most two neighboring axes (one on the left, and one on the right). For a d-dimensional data set, at most d-1 relationships can be shown at a time. In [[time series]] visualization, there exists a natural predecessor and successor; therefore in this special case, there exists a preferred arrangement. However, when the axes do not have a unique order, finding a good axis arrangement requires the use of heuristics and experimentation. In order to explore more complex relationships, axes must be reordered.
By arranging the axes in 3-dimensional space (however, still in parallel, like nails in a nail bed), an axis can have more than two neighbors in a circle around the central attribute, and the arrangement problem gets easier (for example by using a [[minimum spanning tree]]).<ref name="sigmod13">{{cite
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| chapter=Interactive data mining with 3D-parallel-coordinate-trees
▲| journal=Proceedings of the ACM International Conference on Management of Data (SIGMOD)
| date=2013
| pages=1009–1012
| ___location=New York City, NY | year=2013 | doi=10.1145/2463676.2463696| isbn=9781450320375
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