Qualitative data
Qualitative data is descriptive, nonnumeric information representing characteristics, categories, meanings, experiences, opinions, or context rather than measured quantities.
Design for Developers
Qualitative data consists of descriptive, non-numeric information about people’s attitudes, behaviors, needs, or experiences.
- How it is used
- Guides design decisions by revealing the reasons, needs, attitudes, and behaviors behind user actions.
- How deep it goes
- Defines qualitative data and explains collection methods, complementary validation, and investigation of conflicting findings.
- Examples
- Uses potential-user conversations, focus groups, competitor opinions, and unexpected Google Analytics click patterns as examples.
- What you can do after
- Apply it via interviews, focus groups, observation, and follow-up questions to explain and validate design evidence.
D3.js in Action, Third Edition
Qualitative data consists of categorical or descriptive values that represent types or qualities rather than measured amounts.
- How it is used
- Guides visual-channel and D3-scale choices when datasets contain categories or descriptive attributes.
- How deep it goes
- Defines nominal and ordinal values, then connects them to discrete scales and categorical encodings without detailing scale implementation.
- Examples
- Uses city names, movie genres, clothing sizes, coffee sizes, TV platforms, and painting subjects as categorical examples.
- What you can do after
- Apply it via D3 by classifying attributes and mapping qualitative domains to categorical or discrete visual encodings.
Read how D3.js in Action, Third Edition explains qualitative data →
Data Without Labels
Qualitative data consists of nonnumeric observations or categories that are not measured or weighed directly.
- How it is used
- Classifies observed categories for organizing data alongside quantitative measurements.
- How deep it goes
- Defines qualitative data and distinguishes binary, nominal, and ordinal categories with examples.
- Examples
- Uses taste, color, odor, names, cities, product quality, gender, languages, and service types as examples.
- What you can do after
- Evaluate whether observations belong to binary, nominal, or ordinal qualitative categories.
Related concepts
- ordinal dataincludes · Ordinal data consists of categorical values with a meaningful order or rank, without necessarily having equal intervals between categories.
- categorical dataequivalent to · Categorical data consists of values representing membership in a discrete set of named or ordered categories rather than measured numerical magnitudes.
- qualitative researchproduced by · Qualitative research is systematic inquiry into experiences, meanings, behaviors, or perspectives using non-numerical evidence.
- quantitative dataproduces · Quantitative data is information represented numerically as quantities, measurements, counts, or other values suitable for numerical interpretation or analysis.
- nominal dataincludes · Nominal data consists of categorical values whose labels have no inherent or meaningful ordering.
- datakind of · Data is represented information, observations, measurements, or other values that can be stored, processed, transmitted, analyzed, or interpreted.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.