Data and Information Visualization
Data and information visualization represents data or information visually to reveal patterns, communicate findings, and support understanding.
Visual encoding: A mapping from data values to visual properties such as position, color, size, or shape. It specifies how abstract values become marks and visual differences.
Grammar of Graphics: A framework that constructs graphics by combining data, mappings, scales, and visual layers. It makes chart construction explicit as a system of composable design decisions.
Exploratory data analysis: An approach to analyzing data through flexible summaries and visual inspection before formal modeling. Visual displays help expose unexpected structure and generate hypotheses.
Data table: An arrangement of data in rows and columns, with values organized by variables and observations. Tables preserve precise values, while visualizations emphasize patterns and comparisons.
William Playfair: A Scottish engineer and political economist who introduced influential statistical charts in the late eighteenth century. His line, bar, and pie charts helped establish familiar forms of quantitative display.
Data types: Categories that distinguish kinds of values, such as nominal, ordinal, interval, and ratio data. The measurement type constrains which visual comparisons are meaningful.
Scatter plot: A chart that places observations as points according to two quantitative variables. Position encodes paired values, making association, clusters, and outliers visible.
Statistical graphics: Visual methods for exploring and communicating statistical data and results. This tradition connects charts directly to statistical reasoning and evidence.
Textual description: A verbal account that conveys facts, relationships, or findings in written language. Prose can state a takeaway directly, unlike a chart that requires visual decoding.
John Tukey: An American statistician who developed exploratory data analysis and several influential statistical graphics. His box plot and emphasis on visual exploration shaped modern data analysis.