heatmapping

A heatmap is a graphical representation of data where individual values contained in a matrix are represented as colors. The color intensity or hue corresponds to the magnitude of the value, allowing patterns and outliers to be detected at a glance. Heatmaps are used to visualize quantitative information across two dimensions or to show spatial density in geographic or point data.

Common forms include 2D grid heatmaps for tabular data, density heatmaps for point datasets, and geographic heatmaps on maps. Time can be incorporated by panels, animation, or a time axis, producing temporal heatmaps.

Construction involves binning data into a grid or assigning colors to spatially located measurements, normalizing values, and mapping them to a color scale. Color schemes are typically sequential for single-valued data, diverging when a critical midpoint is meaningful, or qualitative for categorical data. A legend is usually provided to relate color to magnitude.

Applications span many fields: website analytics with user interaction heatmaps showing clicks or scroll depth, eye-tracking studies, genomics or proteomics to show expression or correlation matrices, neuroscience research, meteorology for precipitation intensity, and GIS for hotspot analysis of events.

Limitations include potential misinterpretation due to color choice, the effect of bin size and data smoothing, and the need for appropriate normalization to allow fair comparisons. Careful design and accompanying statistics or annotations enhance interpretability.