Heat map
A two-dimensional data visualization technique that represents magnitude as color, from 1873 shaded matrices to modern digital heat maps.
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Source 1: Own work based on: Basemap.png , Source 2: Copernicus programme · CC BY-SA 4.0
A heat map (or heatmap) is a two-dimensional data visualization technique that represents the magnitude of individual values within a dataset as a color. The variation in color may be by hue or intensity. In some applications such as crime analytics or website click-tracking, color is used to represent the density of data points rather than a value associated with each point. 'Heat map' is a relatively new term, but the practice of shading matrices has existed for over a century.
History
The earliest known example dates to 1873, when Toussaint Loua produced a hand-drawn and colored shaded matrix to visualize social statistics across Parisian districts. The technique evolved through the introduction of seriation—reordering rows and columns to reveal structure—by Flinders Petrie in 1899, and Louis Guttman’s Scalogram method for ordering binary matrices in 1950. In 1957, Peter Sneath displayed cluster analysis results by permuting matrix rows and columns to group similar values. Robert Ling implemented this idea in 1973 with the SHADE computer program, which used overstruck printer characters to represent gray shades.
The first high-resolution color cluster heat map program was created by Leland Wilkinson in 1994 for SYSTAT. The well-known Eisen et al. display replicates this earlier SYSTAT design. The term 'heat map' itself was trademarked in 1991 by software designer Cormac Kinney for a program displaying real-time financial market data; the trademark was acquired by SS&C Technologies in 1998 but lapsed in 2006.
Types
Heat maps fall into two primary categories: spatial and grid. Spatial heat maps display the magnitude of a phenomenon as color over a map, with colors varying continuously.
Grid heat maps display magnitude as color in a fixed-size, equal-cell matrix, where each dimension represents a category and the color reflects a measurement on combined traits. Grid heat maps include clustered heat maps and correlograms, the latter having identical traits on both axes and typically displayed as a triangle to avoid duplication. Uses range from business analysis and website analytics—including mouse tracking, eye tracking, and click tracking—to scientific fields like climatology, where warming stripes graphics use one-dimensional heat maps to show yearly temperature changes.
Lore & Background
Heat maps originated in 2D displays of the values in a data matrix. Larger values were represented by small dark gray or black squares (pixels) and smaller values by lighter squares. The earliest known example dates to 1873, when Toussaint Loua used a hand-drawn and colored shaded matrix to visualize social statistics across the districts of Paris. The idea of reordering rows and columns to reveal structure in a data matrix, known as seriation, was introduced by Flinders Petrie in 1899.
In 1950, Louis Guttman developed the Scalogram, a method for ordering binary matrices to expose a one-dimensional scale structure. In 1957, Peter Sneath displayed the results of a cluster analysis by permuting the rows and the columns of a matrix to place similar values near each other according to the clustering. This idea was implemented by Robert Ling in 1973 with a computer program called SHADE. Ling used overstruck printer characters to represent different shades of gray, one character-width per pixel.
Leland Wilkinson developed the first computer program in 1994 (SYSTAT) to produce cluster heat maps with high-resolution color graphics. The Eisen et al. display shown in the figure is a replication of the earlier SYSTAT design. Software designer Cormac Kinney trademarked the term 'heat map' in 1991 to describe computer software used to display real-time financial market information. In 1998 the trademark was acquired by SS&C Technologies, Inc., but the company did not extend the license, so it was annulled in 2006.
Reader's Guide
There are two primary categories of heat maps: spatial and grid. Additionally, there are over ten various types of heat maps. A spatial heat map displays the magnitude of a spatial phenomenon as color, usually cast over a map.
A grid heat map displays magnitude as color in a two-dimensional matrix, with each dimension representing a category of trait and the color representing the magnitude of some measurement on the combined traits from each of the two categories. Grid heat maps are further categorized into two different types of matrices: clustered, and correlogram. A clustered heat map is exemplified by monthly temperature by year.
A correlogram is a clustered heat map that has the same trait for each axis in order to display how the traits in the set of traits interact with each other; it is a triangle instead of a square because the combination of A-B is the same as the combination of B-A. In a grid heat map, colors are presented in a grid of a fixed size, with every cell in the grid also being an equal size and shape. The goal is to detect clustering, or suggest the presence of clusters. A spatial heat map is often used on maps or satellite imagery, where there is no concept of cells, and instead the colors vary continuously.
Frequently Asked Questions
Who is Heat map?
Heat map is a two-dimensional data visualization method that translates the magnitude of values in a dataset into color. It can vary by hue or intensity to convey differences in magnitude across the matrix.
What is Heat map known for?
Its core function is encoding data magnitude as color, but in fields like crime analytics or website click-tracking it shifts to representing the density of data points rather than a single value per cell.
Also in the Codexery
More in Maps & Their Symbols
Sources
Compiled from Wikipedia and the sources listed below. Text from Wikipedia is available under CC BY-SA 4.0; this entry is adapted from it.
- Wikipedia: Heat map (CC BY-SA 4.0).
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