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Calendar-based Graphics for Visualizing People's Daily Schedules

Author

Listed:
  • Earo Wang
  • Dianne Cook
  • Rob J Hyndman

Abstract

Calendars are broadly used in society to display temporal information and events. This paper describes a new calendar display for plotting data, that includes a layout algorithm with many options, and faceting functionality. The functions use modulus algebra on the date variable to restructure the data into a calendar format. The user can apply the grammar of graphics to create plots inside each calendar cell, and thus the displays synchronize neatly with ggplot2 graphics. The motivating application is studying pedestrian behavior in Melbourne, Australia, based on counts which are captured at hourly intervals by sensors scattered around the city. Faceting by the usual features such as day and month, is insufficient to examine the behavior. Making displays on a monthly calendar format helps to understand pedestrian patterns relative to events such as work days, weekends, holidays, and special events. The functions for the calendar algorithm are available in the R package sugrrants.

Suggested Citation

  • Earo Wang & Dianne Cook & Rob J Hyndman, 2019. "Calendar-based Graphics for Visualizing People's Daily Schedules," Monash Econometrics and Business Statistics Working Papers 11/19, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2019-11
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    File URL: https://www.monash.edu/business/ebs/research/publications/ebs/wp11-2019.pdf
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    References listed on IDEAS

    as
    1. Peter Guttorp & Stephan R. Sain & Christopher K. Wikle & Hadley Wickham & Heike Hofmann & Charlotte Wickham & Dianne Cook, 2012. "Glyph‐maps for visually exploring temporal patterns in climate data and models," Environmetrics, John Wiley & Sons, Ltd., vol. 23(5), pages 382-393, August.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    data visualization; statistical graphics; time series; grammar of graphics; R;
    All these keywords.

    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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