Ordinal data

As explained in D3.js in Action, Third Edition

An ordinal value is a categorical value whose labels have a meaningful order or rank.

Ordinal data is qualitative, nonnumerical data whose categories have a meaningful order or rank. Unlike nominal data, ordinal labels are not interchangeable: XS, S, M, L, and XL follow an ascending size sequence. section 3.1.2 section 14.2

Use the ordering of ordinal categories when planning a visualization:

• List dataset attributes and classify ordinal variables separately from quantitative and nominal variables. section 14.2
• Choose an encoding that preserves or communicates rank; sequential or diverging color palettes can represent ordered categories. section 3.1.2
• Select a D3 scale suited to qualitative data rather than treating the labels as continuous numerical measurements. section 3.1.2

Coffee sizes

Coffee sizes such as short, tall, grande, and venti form an ordinal variable because their order matters. That ordering can guide the visual channel chosen for a chart. section 14.2

Figure 3.4 A classification of data types

Use the data-type classification figure to distinguish ordinal categories from nominal, discrete, and continuous data. section 3.1.2

How D3.js in Action, Third Edition covers it

How deep it goes

Defines ordered qualitative categories and connects them to palettes and scales, while deferring detailed scale treatment.

Examples

Uses T-shirt sizes and coffee-order sizes to demonstrate meaningful category order.

What it assumes

Distinguishes ordinal data from nominal, discrete, and continuous data through basic data-type classification.

What you can do after

Apply ordinal classifications when organizing attributes and choosing visual encodings or D3 scales.

How it connects

Connects ordinal data with qualitative data, nominal data, quantitative data, color scales, and D3 scales.

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Also explained in

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  Machine Learning for Tabular Data: XGBoost, Deep Learning, and AICategorical data whose values have a meaningful order or rank.
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  The Well-Grounded Data AnalystOrdinal data consists of categorical values whose categories have a meaningful natural order.
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  Effective Data AnalysisOrdinal data consists of observations assigned to categories with a meaningful order but without necessarily equal spacing between categories.
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  Starting Data Analytics with Generative AI and PythonAn ordinal variable is a categorical variable whose values have a meaningful order but not necessarily equal intervals.
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  Ensemble Methods for Machine LearningAn ordinal feature is a categorical input variable whose categories have an inherent ordering.
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  Tiny Python Projects: Learn coding and testing with puzzles and gamesAn ordinal value is a representation that identifies the position of an item in an ordered sequence, such as first or second.
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  Data Without LabelsOrdinal data consists of categories that have an inherent order but not necessarily meaningful numeric spacing.

Compare how 8 books explain ordinal data →

Related concepts

• categorical datakind of · Categorical data consists of values representing membership in a discrete set of named or ordered categories rather than measured numerical magnitudes.
• data typekind of · A data type classifies values and specifies their representation or interpretation and the operations applicable to them.
• qualitative datakind of · Qualitative data is descriptive, nonnumeric information representing characteristics, categories, meanings, experiences, opinions, or context rather than measured quantities.
• Likert scaleproduced by · A Likert scale is an ordered response scale whose labeled categories express degrees of agreement, quality, intensity, preference, or another evaluated property.

This explainer was generated by Manning's knowledge graph from the text of D3.js in Action, Third Edition. The section links point to the parts of the book it draws on.