You can override the legend aesthetics, e.g.,

ggplot(df,aes(x=Importance,y=Performance,fill=PBF,size=gapsize))+
    geom_point(shape=21,colour="black")+
    scale_size_area(max_size=pointsizefactor) +
    scale_fill_discrete(guide = guide_legend(override.aes = list(size = 4)))

Best,
Ista

On Thu, Oct 31, 2013 at 4:08 PM, Conklin, Mike (GfK)
<mike.conk...@gfk.com> wrote:
> I am creating a scatterplot with the following code.
>
>   pl<-ggplot(df,aes(x=Importance,y=Performance,fill=PBF,size=gapsize))+
>       
> geom_point(shape=21,colour="black")+scale_size_area(max_size=pointsizefactor)
>
> points are plotted where the size of the point is related to a metric 
> variable gapsize and the fill color on the point is related to the variable 
> PBF which is a 4 level factor.  This works exactly as I want with the points 
> varying in size based on the metric and being color coded.  I get 2 legends 
> on the side of the plot, one related to the size of the dot and the other 
> showing the color coding. The problem is that the dots on the color coding 
> legend are so small that it is impossible to discern what color they are. The 
> dots in the plot are large, so it is clear what colors they are, but the 
> legend is useless.  How can I increase the size of the points in the color 
> legend.
>
> pointsizefactor<-5
>
> df
>
>         Importance Performance gapsize labels       PBF
> q50451   0.7079463  -0.7213622       2      a         W
> q50452   0.4489164  -0.5552116       1      b         G
> q50453   0.7714138  -0.6940144       5      c         F
> q50454   0.6284830  -0.6011352       3      d         S
> q50455   0.7131063  -0.6800826       4      e         G
> q50456   0.7038184  -0.6026832       6      f         S
> q50457   0.5201238  -0.3539732       8      g         G
> q50458   0.9195046  -0.8214654       2      h         F
> q50459   0.3797730  -0.4184727       1      i         W
> q504510  0.8065015  -0.6305470       7      j         G
> q504511  0.6062951  -0.4442724       6      k         S
> q504512  0.6253870  -0.4478844       8      l         G
> q504513  0.3813209  -0.4102167       2      m         W
> q504514  0.3813209  -0.3436533       3      n         F
> q504515  0.5185759  -0.4365325       5      o         G
> q504516  0.5872033  -0.4556244       6      p         S
> q504518  0.5397317  -1.0000000       1      q         S
> q504519  0.5882353  -0.4674923       9      r         S
> q504520  0.4205366  -0.4164087       4      s         W
> q504521  0.7616099  -0.3323013      10      t         F
> q504522  0.7213622  -0.6088751       7      u         G
> q504523  0.6780186  -0.6130031       8      v         G
> q504524  0.6904025  -0.3937049      10      w         W
> q504525  0.4143447  -0.4669763       4      x         W
> q504526  0.5779154  -0.2982456       9      y         F
> q504527  0.6718266  -0.3457172      10      z         G
>
>
> Thanks all
>
> //Mike
>
> W. Michael Conklin
> Executive Vice President | Marketing Science
> GfK Custom Research, LLC | 8401 Golden Valley Road | Minneapolis, MN, 55427
> T +1 763 417 4545 | M +1 612 567 8287
> www.gfk.com<http://www.gfk.com/>
>
>
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