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I like the Dark2 palette from colorbrewer for scatterplotscatter plots. We used this in the ggobi book, www.ggobi.org/bookwww.ggobi.org/book. But otherwise the color palettes are meant for geographic areas rather than data plots. Good color choice is still an issue for point based-based plots.

The R packages colorspace,colorspace and dichromatdichromat are useful. colorspacecolorspace allows selection of colors around the wheel,: you can spend hours/days fine tuning. dichromatdichromat helps check for colorblindness.

ggplot2ggplot2 generally has good defaults, although not necessarily color blind-blind proof.

The diverging red to blue scheme looks good on your computer but does not project well.

I like the Dark2 palette from colorbrewer for scatterplot plots. We used this in the ggobi book, www.ggobi.org/book. But otherwise the color palettes are meant for geographic areas rather than data plots. Good color choice is still an issue for point based plots.

The R packages colorspace, and dichromat are useful. colorspace allows selection of colors around the wheel, you can spend hours/days fine tuning. dichromat helps check for colorblindness.

ggplot2 generally has good defaults, although not necessarily color blind proof.

The diverging red to blue scheme looks good on your computer but does not project well.

I like the Dark2 palette from colorbrewer for scatter plots. We used this in the ggobi book, www.ggobi.org/book. But otherwise the color palettes are meant for geographic areas rather than data plots. Good color choice is still an issue for point-based plots.

The R packages colorspace and dichromat are useful. colorspace allows selection of colors around the wheel: you can spend hours/days fine tuning. dichromat helps check for colorblindness.

ggplot2 generally has good defaults, although not necessarily color-blind proof.

The diverging red to blue scheme looks good on your computer but does not project well.

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source | link

I like the Dark2 palette from colorbrewer for scatterplot plots. We used this in the ggobi book, www.ggobi.org/book. But otherwise the color palettes are meant for geographic areas rather than data plots. Good color choice is still an issue for point based plots.

The R packages colorspace, and dichromat are useful. colorspace allows selection of colors around the wheel, you can spend hours/days fine tuning. dichromat helps check for colorblindness.

ggplot2 generally has good defaults, although not necessarily color blind proof.

The diverging red to blue scheme looks good on your computer but does not project well.