Encyclopedia of Database Systems

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

Visualizing Quantitative Data

  • Anatol SarginEmail author
  • Ali ÜnlüEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1378


Graphics for continuous data; Visual displays of numerical data; Visualizing quantitative data


Quantitative data are data that can be measured on a numerical scale. Examples of such data are length, height, volume, speed, temperature, or cost.

A quantitative variable can be transformed into a categorical variable by grouping, for example, weight can be divided into underweight, normal weight, and overweight. The inverse transformation may not be possible.

Quantitative data can be categorical or continuous. This entry only concentrates on continuous data. Visualization in general means the graphical or visual display of data or relations.

Key Points

Univariate graphics are the most basic ones and display exactly one variable. There are three plot types that are commonly used: dotplots, boxplots, and histograms.

Dotplots draw every data point along one axis. This graphic shows clusters and gaps in the data. Overplotting can be a serious problem, because many points...

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Recommended Reading

  1. 1.
    Cleveland W. Visualizing data. Summit: Hobert; 1993.Google Scholar
  2. 2.
    Unwin A, 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