New Approaches in Visualization of Categorical Data: R Package extracat

被引:0
|
作者
Pilhoefer, Alexander [1 ]
Unwin, Antony [1 ]
机构
[1] Univ Augsburg, Inst Math, Dept Comp Oriented Stat & Data Anal, D-86135 Augsburg, Germany
来源
JOURNAL OF STATISTICAL SOFTWARE | 2013年 / 53卷 / 07期
关键词
categorical data; multiple barcharts; parallel coordinates; R; DISPLAYS;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The R package extracat provides two new graphical methods for displaying categorical data extending the concepts of multiple barcharts and parallel coordinates plots. The first method called rmb plot uses a crossover of mosaicplots and multiple barcharts to display the frequencies of a data table split up into conditional relative frequencies of one target variable and the absolute frequencies of the corresponding combinations of the remaining explanatory variables. It provides a well-structured representation of the data which is easy to interpret and allows precise comparisons. The graphic can additionally be used as a generalization of spineplots or with barcharts for the conditional relative frequencies. Several options, including ceiling censored zooming, residual shadings and a choice of color palettes, are provided. An interactive version based on the R package iWidgets is also presented. The second graphic cpcp uses the interactive parallel coordinates plots in the iplots package to visualize categorical data. Sequences of points are used to represent each of the variable categories, while ordering algorithms are applied to represent a hierarchical structure in the data and keep the arrangement clear. This interactive graphic is well-suited for exploratory analysis and allows a visual interpretation even for a higher number of variables and a mixture of categorical and numeric scales.
引用
收藏
页码:1 / 25
页数:25
相关论文
共 50 条
  • [31] Multiple-Table Data in R with the multitable Package
    Walker, Steven C.
    Guenard, Guillaume
    Solymos, Peter
    Legendre, Pierre
    JOURNAL OF STATISTICAL SOFTWARE, 2012, 51 (08): : 1 - 38
  • [32] Analyzing Remote Sensing Data in R: The landsat Package
    Goslee, Sarah C.
    JOURNAL OF STATISTICAL SOFTWARE, 2011, 43 (04):
  • [33] Simulating Survival Data Using the simsurv R Package
    Brilleman, Samuel L.
    Wolfe, Rory
    Moreno-Betancur, Margarita
    Crowther, Michael J.
    JOURNAL OF STATISTICAL SOFTWARE, 2021, 97 (03): : 1 - 27
  • [34] An R package for the integrated analysis of metabolomics and spectral data
    Costa, Christopher
    Maraschin, Marcelo
    Rocha, Miguel
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2016, 129 : 117 - 124
  • [35] openair - An R package for air quality data analysis
    Carslaw, David C.
    Ropkins, Karl
    ENVIRONMENTAL MODELLING & SOFTWARE, 2012, 27-28 : 52 - 61
  • [36] Visualization of proteomics data using R and Bioconductor
    Gatto, Laurent
    Breckels, Lisa M.
    Naake, Thomas
    Gibb, Sebastian
    PROTEOMICS, 2015, 15 (08) : 1375 - 1389
  • [37] AMR: An R Package for Working with Antimicrobial Resistance Data
    Berends, Matthijs S.
    Sinha, Bhanu N. M.
    Luz, Christian F.
    Albers, Casper J.
    Friedrich, Alexander W.
    Glasner, Corinna
    JOURNAL OF STATISTICAL SOFTWARE, 2022, 104 (03):
  • [38] Data Visualization Using R for Researchers Who Do Not Use R
    Nordmann, Emily
    McAleer, Phil
    Toivo, Wilhelmiina
    Paterson, Helena
    DeBruine, Lisa M.
    ADVANCES IN METHODS AND PRACTICES IN PSYCHOLOGICAL SCIENCE, 2022, 5 (02)
  • [39] FHtest: An R Package for the Comparison of Survival Curves with Censored Data
    Oller, Ramon
    Langohr, Klaus
    JOURNAL OF STATISTICAL SOFTWARE, 2017, 81 (15): : 1 - 25
  • [40] R Package clickstream: Analyzing Clickstream Data with Markov Chains
    Scholz, Michael
    JOURNAL OF STATISTICAL SOFTWARE, 2016, 74 (04):