I have put a new release of the WVPlots
package up on CRAN. This release adds palette and/or color controls to most of the plotting functions in the package.
WVPlots
was originally a catch-all package of ggplot2
visualizations that we at Win-Vector tended to use repeatedly, and wanted to turn into “one-liners.” A consequence of this is that the older visualizations had our preferred color schemes hard-coded in. More recent additions to the package sometimes had palette or color controls, but not in a consistent way. Making color controls more consistent has been a “todo” for a while—one that I’d been putting off. A recent request from user Brice Richard (thanks Brice!) has pushed me to finally make the changes.
Most visualizations in the package that color-code by group now have a palette
argument that takes the name of a Brewer palette for the graph; Dark2
is usually the default. To use the ggplot2
default palette, or to set an alternative palette, such as viridis or a manually specified color scheme, set palette=NULL
. Here’s some examples:
library(WVPlots)
library(ggplot2)
mpg = ggplot2::mpg
mpg$trans = gsub("\(.*$", '', mpg$trans)
# default palette: Dark2
DoubleDensityPlot(mpg, "cty", "trans", "City driving mpg by transmission type")
# set a different Brewer color palette
DoubleDensityPlot(mpg, "cty", "trans",
"City driving mpg by transmission type",
palette = "Accent")
# set a custom palette
cmap = c("auto" = "#7b3294", "manual" = "#008837")
DoubleDensityPlot(mpg, "cty", "trans",
"City driving mpg by transmission type",
palette=NULL) +
scale_color_manual(values=cmap) +
scale_fill_manual(values=cmap)
For other plots, the user can now specify the desired color for different elements of the graph.
title = "Count of cars by number of carburetors and cylinders"
# default fill: darkblue
ShadowPlot(mtcars, "carb", "cyl",
title = title)
# specify fill
ShadowPlot(mtcars, "carb", "cyl",
title = title,
fillcolor = "#a6611a")
We hope that these changes make WVPlots
even more useful to our users. For examples of several of the visualizations in WVPlots
, see this example vignette. For the complete list of visualizations, see the reference page.
Categories: Pragmatic Data Science Tutorials
Nina Zumel
Data scientist with Win Vector LLC. I also dance, read ghost stories and folklore, and sometimes blog about it all.