Discrete variable

As explained in D3.js in Action, Third Edition

A discrete value belongs to a predetermined finite or otherwise distinct set of possible values.

A discrete variable takes values from a distinct, predetermined set. In quantitative data, its values are whole numbers that can be counted but not subdivided; employee counts are discrete, whereas temperature is continuous. section 3.1.2

Use the distinction to plan visualizations and scales:

• Treat counts such as employees, students, or monthly letters as discrete quantitative values. section 3.1.2 section 14.2
• Treat categories such as genres, coffee sizes, or genders as discrete values when each item belongs to one defined group. section 14.2 section 6.4.2
• Choose visual encodings deliberately: discrete categories commonly use categorical colors, while discrete domains can map to continuous positions. section 3.1.2 section 6.4.2

Genres mapped to colors

A D3 scale can map the discrete genre domain ["Drama", "Action", "Crime", "Comedy"] to the discrete color range ["purple", "blue", "green", "yellow"]. section 3.4.1

Figure 3.4 A classification of data types

The classification diagram places discrete data inside quantitative data and contrasts it with continuous data. section 3.1.2

How D3.js in Action, Third Edition covers it

How deep it goes

Defines countable whole numbers, contrasts them with continuous measurements, and extends the idea to discrete scale inputs and outputs.

Examples

Uses employee counts, coffee sizes, TV genres, and gender categories as discrete values in charts and scales.

What it assumes

Builds the distinction from familiar numerical and categorical examples rather than assuming mathematical formalism.

What you can do after

Apply it via D3 scales to choose discrete domains, categorical outputs, or continuous positions for chart variables.

How it connects

Connects quantitative data, continuous data, qualitative data, categorical color scales, and D3 scales.

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Also explained in

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  Everyday Data VisualizationA data dimension whose values are separate, distinct, and individually identifiable rather than varying continuously across a range.
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  Causal AIA discrete outcome is one of a finite or countable set of distinct values that a discrete random variable can take.
• 

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  Data Without LabelsDiscrete data consists of distinct countable values, typically represented as integers.
• 

  liveBookmanning.com
  Statistics Every Programmer NeedsDiscrete data are observations whose possible values are separate, countable outcomes rather than values throughout a continuous interval.

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Related concepts

• continuous datacontrasts with · Continuous data consists of numerical measurements that can take arbitrarily fine-grained values across a range or interval.
• categorical dataequivalent to · Categorical data consists of values representing membership in a discrete set of named or ordered categories rather than measured numerical magnitudes.
• quantitative datakind of · Quantitative data is information represented numerically as quantities, measurements, counts, or other values suitable for numerical interpretation or analysis.
• bar chartused by · A bar chart is a visualization that compares quantitative values for discrete categories using rectangular bars whose lengths or heights encode magnitude.
• integerincludes · An integer is a whole-number value with no fractional part, including negative numbers, zero, and positive numbers.
• random variablekind of · A random variable is a function that assigns numerical values to outcomes of a random process and is characterized by a probability distribution.

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.