Binned ggplot2 color scales using the color palettes generated by
scale_colour_binned_divergingx( palette = "Geyser", c1 = NULL, c2 = NULL, c3 = NULL, l1 = NULL, l2 = NULL, l3 = NULL, h1 = NULL, h2 = NULL, h3 = NULL, p1 = NULL, p2 = NULL, p3 = NULL, p4 = NULL, cmax1 = NULL, cmax2 = NULL, alpha = 1, rev = FALSE, mid = 0, na.value = "grey50", guide = "coloursteps", n_interp = 11, aesthetics = "colour", ... ) scale_color_binned_divergingx( palette = "Geyser", c1 = NULL, c2 = NULL, c3 = NULL, l1 = NULL, l2 = NULL, l3 = NULL, h1 = NULL, h2 = NULL, h3 = NULL, p1 = NULL, p2 = NULL, p3 = NULL, p4 = NULL, cmax1 = NULL, cmax2 = NULL, alpha = 1, rev = FALSE, mid = 0, na.value = "grey50", guide = "coloursteps", n_interp = 11, aesthetics = "colour", ... ) scale_fill_binned_divergingx(..., aesthetics = "fill")
The name of the palette to be used.
Parameters to customize the scale. See
divergingx_hcl for details.
Numeric vector of values in the range
[0, 1] for alpha transparency channel (0 means transparent and 1 means opaque).
TRUE, reverses the order of the colors in the color scale.
Data value that should be mapped to the mid-point of the diverging color scale.
Color to be used for missing data points.
Type of legend. Use
"coloursteps" for color bar with discrete steps.
Number of discrete colors that should be used to interpolate the binned color scale. For diverging scales, it is important to use an odd number to capture the color at the midpoint.
The ggplot2 aesthetics to which this scale should be applied.
common binned scale parameters: `name`, `breaks`, `labels`, and `limits`. See
binned_scale for more details.
Available CARTO palettes: ArmyRose, Earth, Fall, Geyser, TealRose, Temps, Tropic.
Available ColorBrewer.org palettes: Spectral, PuOr, RdYlGn, RdYlBu, RdGy, BrBG, PiYG, PRGn, RdBu.
If both a valid palette name and palette parameters are provided then the provided palette parameters overwrite the parameters in the named palette. This enables easy customization of named palettes.
library("ggplot2") # volcano plot (difference from mean height) nx = 87 ny = 61 df <- data.frame(diff = c(volcano) - mean(volcano), x = rep(1:nx, ny), y = rep(1:ny, each = nx)) ggplot(df, aes(x, y, fill=diff)) + geom_raster() + scale_fill_binned_divergingx(palette = "Fall", rev = TRUE) + coord_fixed(expand = FALSE) # adapted from stackoverflow: https://stackoverflow.com/a/20127706/4975218 # generate dataset and base plot set.seed(100) df <- data.frame(country = LETTERS, V = runif(26, -40, 40)) df$country = factor(LETTERS, LETTERS[order(df$V)]) # reorder factors gg <- ggplot(df, aes(x = country, y = V, fill = V)) + geom_bar(stat = "identity") + labs(y = "Under/over valuation in %", x = "Country") + coord_flip() + theme_minimal() # plot with diverging scale "Geyser" gg + scale_fill_binned_divergingx(palette = "Geyser", n.breaks = 6)