Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Visualizing Categorical Data

  • Ali ÜnlüEmail author
  • Anatol Sargin
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1379


Graphics for discrete data; Plots for qualitative information; Visual displays of nonnumerical data; Visualizing categorical data


Categorical data are data recorded about units on variables which take values in a discrete set of categories. Examples of categorical variables are gender, citizenship, or number of children. Categorical variables can be dichotomous (two categories; e.g., gender) or polytomous (more than two categories; e.g., citizenship), and nominal (unordered categories; e.g., gender) or ordinal (ordered categories; e.g., number of children). Categorical data can be in case form (individual raw data vector recorded about each unit) or frequency form (tabulated data counting over the categories of the variables), and univariate or multivariate (including bivariate). Quantitative variables can be discretized to become categorical variables (e.g., using child and adult instead of exact age). Strictly speaking, all data may be considered categorical...

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Recommended Reading

  1. 1.
    Friendly M. Visualizing categorical data. Cary: SAS Institute; 2000.zbMATHGoogle Scholar
  2. 2.
    Hofmann H. Mosaic plots and their variants. In: Chen CH, Haerdle W, Unwin AR, editors. Handbook of data visualization. Berlin: Springer; 2008.Google Scholar
  3. 3.
    Unwin AR, Theus M, Hofmann H. Graphics of large datasets. Berlin: Springer; 2006.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of AugsburgAugsburgGermany

Section editors and affiliations

  • Hans Hinterberger
    • 1
  1. 1.Inst. of Scientific ComputingETH ZürichZurichSwitzerland