Data Loss Aversion II - R Lattice Plot

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This post continues Jorges Camoes discussion on data loss aversion.  In my first post on this topic,  I used a dot plot to show the 1967 and 2005 values to summarize relative shifts in households by total household income bracket.   Derek, giving in to data loss aversion, used a logarithmic axis technique to show all data in intervening years between 1967 and 2005. Andreas Lipphardt used small multiples to show 1967 and 2005 values as well as the overall change by bracket. We can combine Dereks “giving into loss aversion” and Andreas’s “small multiples” approaches to show all data for the 9 series in a compact trellis chart by using the R Lattice package. I have a brief discussion on using R  for advanced charting here. This R lattice plot has several advantages:

• Shows all data  
• All plots share common X and Y axes, reducing axis labeling
• Plot uses banking to 45 to enhance visualization

The terms trellis, lattice and panel charts seem to be used interchangably, depending on which software was used to develop the chart. Small multiples is a more generic term that applies to Tufte’s approach of making a series of small, similar charts.
 

Excel has limited tools for effective multivariate charts, no trellis or lattice charts and no built-in small multiples capabilities.  While we can use clever Excel workarounds like panel charts or manually generated small mutiples,  I find that it is wise to move beyond Excel’s chart limits for multivariate charts.
 

R, a powerful and free statistical analysis and graphing package, has excellent multivariate charting tools. The R learning curve is well worth it for those Excel charters who want to move beyond Excel to the wider world of advanced charting.               

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