IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2009i9p3259-3270.html
   My bibliography  Save this article

Escaping RGBland: Selecting colors for statistical graphics

Author

Listed:
  • Zeileis, Achim
  • Hornik, Kurt
  • Murrell, Paul

Abstract

Statistical graphics are often augmented by the use of color coding information contained in some variable. When this involves the shading of areas (and not only points or lines)--e.g., as in bar plots, pie charts, mosaic displays or heatmaps--it is important that the colors are perceptually based and do not introduce optical illusions or systematic bias. Based on the perceptually-based Hue-Chroma-Luminance (HCL) color space suitable color palettes are derived for coding categorical data (qualitative palettes) and numerical variables (sequential and diverging palettes).

Suggested Citation

  • Zeileis, Achim & Hornik, Kurt & Murrell, Paul, 2009. "Escaping RGBland: Selecting colors for statistical graphics," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3259-3270, July.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:9:p:3259-3270
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00554-9
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Meyer, David & Zeileis, Achim & Hornik, Kurt, 2006. "The Strucplot Framework: Visualizing Multi-way Contingency Tables with vcd," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i03).
    2. Tenenhaus, Arthur & Giron, Alain & Viennet, Emmanuel & Bera, Michel & Saporta, Gilbert & Fertil, Bernard, 2007. "Kernel logistic PLS: A tool for supervised nonlinear dimensionality reduction and binary classification," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4083-4100, May.
    3. Harezlak, Jaroslaw & Coull, Brent A. & Laird, Nan M. & Magari, Shannon R. & Christiani, David C., 2007. "Penalized solutions to functional regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4911-4925, June.
    4. Kneib, Thomas, 2006. "Mixed model-based inference in geoadditive hazard regression for interval-censored survival times," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 777-792, November.
    5. A. Azzalini & A.W. Bowman, 1990. "A Look at Some Data on the Old Faithful Geyser," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 39(3), pages 357-365, November.
    6. Gelfand, Alan E. & Banerjee, Sudipto & Sirmans, C.F. & Tu, Yong & Eng Ong, Seow, 2007. "Multilevel modeling using spatial processes: Application to the Singapore housing market," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3567-3579, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Seiler, Johannes & Harttgen, Kenneth & Kneib, Thomas & Lang, Stefan, 2021. "Modelling children's anthropometric status using Bayesian distributional regression merging socio-economic and remote sensed data from South Asia and sub-Saharan Africa," Economics & Human Biology, Elsevier, vol. 40(C).
    2. Pilhöfer, Alexander & Unwin, Antony, 2013. "New Approaches in Visualization of Categorical Data: R Package extracat," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 53(i07).
    3. MacDonald, Blake & Ranjan, Pritam & Chipman, Hugh, 2015. "GPfit: An R Package for Fitting a Gaussian Process Model to Deterministic Simulator Outputs," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i12).
    4. Ben Jann, 2022. "ColrSpace: A Mata class for color management," University of Bern Social Sciences Working Papers 42, University of Bern, Department of Social Sciences, revised 03 Jun 2022.
    5. repec:jss:jstsof:38:i07 is not listed on IDEAS
    6. Emura, Takeshi & Lin, Yi-Shuan, 2013. "A comparison of normal approximation rules for attribute control charts," MPRA Paper 51029, University Library of Munich, Germany.
    7. Matthias Templ & Andreas Alfons & Peter Filzmoser, 2012. "Exploring incomplete data using visualization techniques," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(1), pages 29-47, April.
    8. Stanislav Katina & Liberty Vittert & Adrian W. Bowman, 2021. "Functional data analysis and visualisation of three‐dimensional surface shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 691-713, June.
    9. de Wreede, Liesbeth C. & Fiocco, Marta & Putter, Hein, 2011. "mstate: An R Package for the Analysis of Competing Risks and Multi-State Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 38(i07).
    10. repec:jss:jstsof:32:i01 is not listed on IDEAS
    11. Anette Fasang & Marcel Raab, 2014. "Beyond Transmission: Intergenerational Patterns of Family Formation Among Middle-Class American Families," Demography, Springer;Population Association of America (PAA), vol. 51(5), pages 1703-1728, October.
    12. Tseng, George C., 2010. "Quantile map: Simultaneous visualization of patterns in many distributions with application to tandem mass spectrometry," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1124-1137, April.
    13. Reto Stauffer & Georg J. Mayr & Markus Dabernig & Achim Zeileis, 2013. "Somewhere over the Rainbow: How to Make Effective Use of Colors in Meteorological Visualizations," Working Papers 2013-37, Faculty of Economics and Statistics, Universität Innsbruck.
    14. Ben Jann, 2023. "Color palettes for Stata graphics: An update," Stata Journal, StataCorp LP, vol. 23(2), pages 336-385, June.
    15. Jonas Schöley, 2021. "The centered ternary balance scheme: A technique to visualize surfaces of unbalanced three-part compositions," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(19), pages 443-458.
    16. Fox, John & Hong, Jangman, 2009. "Effect Displays in R for Multinomial and Proportional-Odds Logit Models: Extensions to the effects Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i01).
    17. Meyer, Sebastian & Held, Leonhard & Höhle, Michael, 2017. "Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i11).
    18. Shannon P McPherron, 2018. "Additional statistical and graphical methods for analyzing site formation processes using artifact orientations," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-21, January.
    19. Anette Eva Fasang & Tim Futing Liao, 2014. "Visualizing Sequences in the Social Sciences," Sociological Methods & Research, , vol. 43(4), pages 643-676, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Yang & Zhao, Shishun & Hu, Tao & Sun, Jianguo, 2021. "Variable selection for generalized odds rate mixture cure models with interval-censored failure time data," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    2. Hirukawa, Masayuki, 2010. "Nonparametric multiplicative bias correction for kernel-type density estimation on the unit interval," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 473-495, February.
    3. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
    4. Fred Huffer & Cheolyong Park, 2000. "A test for multivariate structure," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(5), pages 633-650.
    5. Yee, Thomas W., 2010. "The VGAM Package for Categorical Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i10).
    6. Riccardo, Borgoni & Alessandra, Michelangeli & Nicola, Pontarollo, 2016. "How Does a City Benefit from Culture? Evidence from Milan," Working Papers 335, University of Milano-Bicocca, Department of Economics, revised 16 May 2016.
    7. Branislav Panić & Marko Nagode & Jernej Klemenc & Simon Oman, 2022. "On Methods for Merging Mixture Model Components Suitable for Unsupervised Image Segmentation Tasks," Mathematics, MDPI, vol. 10(22), pages 1-22, November.
    8. Yigong Hu & Binbin Lu & Yong Ge & Guanpeng Dong, 2022. "Uncovering spatial heterogeneity in real estate prices via combined hierarchical linear model and geographically weighted regression," Environment and Planning B, , vol. 49(6), pages 1715-1740, July.
    9. Ohtsuka, Yoshihiro & Oga, Takashi & Kakamu, Kazuhiko, 2010. "Forecasting electricity demand in Japan: A Bayesian spatial autoregressive ARMA approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2721-2735, November.
    10. Nadia Lakhal & Asma Guizani & Asma Sghaier & Mohammed El َamine Abdelli & Imen Ben Slimene, 2021. "The impact of CSR performance on Efficiency of Investments using Machine Learning," Post-Print hal-03375264, HAL.
    11. Yana Melnykov & Xuwen Zhu & Volodymyr Melnykov, 2021. "Transformation mixture modeling for skewed data groups with heavy tails and scatter," Computational Statistics, Springer, vol. 36(1), pages 61-78, March.
    12. Congdon, Peter, 2009. "Modelling the impact of socioeconomic structure on spatial health outcomes," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3047-3056, June.
    13. repec:cte:wsrepe:ws1450804 is not listed on IDEAS
    14. Liu, Nan & Zhao, Yuan & Ge, Jiaqi, 2018. "Do renters skimp on energy efficiency during economic recessions? Evidence from Northeast Scotland," Energy, Elsevier, vol. 165(PA), pages 164-175.
    15. Ruiyan Luo & Xin Qi, 2022. "Restricted function‐on‐function linear regression model," Biometrics, The International Biometric Society, vol. 78(3), pages 1031-1044, September.
    16. José E. Chacón, 2020. "The Modal Age of Statistics," International Statistical Review, International Statistical Institute, vol. 88(1), pages 122-141, April.
    17. Chen, Haitao & Zhang, Bin & Liu, Hua & Cao, Jiguo, 2024. "The inequality in household electricity consumption due to temperature change: Data driven analysis with a function-on-function linear model," Energy, Elsevier, vol. 288(C).
    18. Jernigan, Robert W. & Baran, Robert H., 2003. "Testing lumpability in Markov chains," Statistics & Probability Letters, Elsevier, vol. 64(1), pages 17-23, August.
    19. José E. Chacón, 2019. "Mixture model modal clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(2), pages 379-404, June.
    20. O’Hagan, Adrian & Murphy, Thomas Brendan & Gormley, Isobel Claire & McNicholas, Paul D. & Karlis, Dimitris, 2016. "Clustering with the multivariate normal inverse Gaussian distribution," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 18-30.
    21. Paul Harris & Bruno Lanfranco & Binbin Lu & Alexis Comber, 2020. "Influence of Geographical Effects in Hedonic Pricing Models for Grass-Fed Cattle in Uruguay," Agriculture, MDPI, vol. 10(7), pages 1-17, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:53:y:2009:i:9:p:3259-3270. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.