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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 ''n''-dimensional data set, at most ''n''-1 relationships can be shown at a time without altering the approach. 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 experimentation and feature engineering. To explore more relationships, axes may be reordered or restructured.
One approach arranges axes in 3-dimensional space (still in parallel, forming a [[Lattice graph]]), an axis can have more than two neighbors in a circle around the central attribute, and the arrangement problem can be improve by using a [[minimum spanning tree]].<ref name="sigmod13">{{cite book
| title=Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
| chapter=Interactive data mining with 3D-parallel-coordinate-trees
|