Matrices

Square Matrix

Description:

Any two dimensional set of numbers, colors, intensities, sized dots, or other glyphs.

Data Types:

Nominal, ordinal and interval-ratio types are all good fits for this visualization.

Comparisons:

They are used to give a quick overview of the distribution and proportions of each sample in a data set and also to compare distribution and proportion across other datasets, in order to discover patterns.

i.e. When two items are being compared against one another in a the D' table.

Pre-processing:

Given the richness and potential variegation of the data in each cell (Ex: a number within a variable sized and colored circle) a mapping methodology needs to be determined which is intuitively understandable and expresses the importance of each cell attribute relative to all others. Ex: An income range might be better suited to a color or size intensity rather than a glyph. If a zip code is a relevant but less important attribute of a cell, it should not be mapped in a way where it is the first thing noticed.

Mapping:

Color

• Completely different colors can be used for nominal samples.
• Intensities of colors can be used to express ranges of ordinal or interval-ratio samples.

Size

• Completely different sizes can be used for nominal samples. (Not recommended for datasets with many potential nominal values)
• Variations in size can be used to express ranges of ordinal or interval-ratio samples.

Glyphs

• Best suited to nominal samples.
• Can be used for ordinal but not recommended for datasets with many potential ordinal values.

Half Matrix

This is a special case of a square matrix wherein the samples above the main diagonal are reflections of those below or are zero.

Images:

Good

Bad

Mapping choice could allow one cell to obscure or overlap another.

Redundant data shown. A half matrix might have been better suited.

Group designations on axes are unnecessarily opaque.