datavisualizations

Data visualizations are graphical representations of data designed to communicate information clearly and efficiently. They convert numerical or categorical data into visual encodings—such as points, bars, lines, and regions—to reveal patterns, comparisons, trends, and relationships. They support analysis, decision making, and storytelling across disciplines.

Common forms include bar charts, line graphs, scatter plots, histograms, pie charts, box plots, heat maps, choropleth maps, tree maps, network diagrams, and dashboards. Interactive visualizations enable exploration through filtering, sorting, zooming, and brushing.

Effective visualization rests on appropriate encoding choices, accurate scales, and legible labeling. Perceptual research guides how people read position, length, angle, and color, while avoiding misleading distortions. Accessibility considerations include color palettes accessible to color-impaired users and sufficient contrast, plus textual descriptions.

Data visualization has roots in early statistical graphics and has grown with computer graphics and software. It serves science, journalism, business, and public policy, supporting exploratory data analysis and communicating results in dashboards and reports. Ethical practice emphasizes honesty about uncertainty and avoidance of misleading representations.