![]() scaled.Į + stat_bin_2d(bins = 30, drop = T): x, y, fill |. density.Ĭ + stat_density(adjust = 1, kernel = "gaussian"): x, y |. ndensity.Ĭ + stat_count(width = 1): x, y |. ![]() is the variable created by stat.Ĭ + stat_bin(binwidth = 1, boundary = 10): x, y |. In this example, "polygon" is the geom to use, stat_density_2d() is the stat function, aes() contains the geom mappings, and. syntax to map stat variables to aesthetics. Visualize a stat by changing the default stat of a geom function, geom_bar(stat = "count"), or by using a stat function, stat_count(geom = "bar"), which calls a default geom to make a layer (equivalent to a geom function). aes() arguments: x, y, alpha, color, fill, linetype, size, width.Ī stat builds new variables to plot (e.g., count, prop). L + geom_tile(aes(fill = z)): Draw a tile plot. L + geom_raster(aes(fill = z), hjust = 0.5, vjust = 0.5, interpolate = FALSE): Draw a raster plot. aes() arguments: x, y, alpha, color, fill, group, linetype, size, subgroup. L + geom_contour_filled(aes(fill = z)): Draw 2D contour plot with the space between lines filled. aes() arguments: x, y, z, alpha, color, group, linetype, size, weight. L + geom_contour(aes(z = z)): Draw 2D contour plot. Seals $z <- with(seals, sqrt(delta_long ^ 2 + delta_lat ^ 2)) l <- ggplot(seals, aes(long, lat)) aes() arguments: x, ymax, ymin, alpha, color, fill, group, linetype, size.Ĭommon aesthetics: x, y, alpha, color, linetype, size.ī + geom_abline(aes(intercept = 0, slope = 1)): Draw a diagonal reference line with a given slope and intercept.ī + geom_hline(aes(yintercept = lat)): Draw a horizontal reference line with a given yintercept.ī + geom_vline(aes(xintercept = long)): Draw a vertical reference line with a given xintercept.ī + geom_segment(aes(yend = lat + 1, xend = long + 1)): Draw a straight line from (x, y) to (xend, yend).ī + geom_spoke(aes(angle = 1:1155, radius = 1)): Draw line segments using polar coordinates ( angle and radius). aes() arguments: xmax, xmin, ymax, ymin, alpha, color, fill, linetype, size.Ī + geom_ribbon(aes(ymin = unemploy - 900, ymax = unemploy + 900): For each x, plot an interval from ymin to ymax. aes() arguments: x, y, alpha, color, fill, group, subgroup, linetype, size.ī + geom_rect(aes(xmin = long, ymin = lat, xmax = long + 1, ymax = lat + 1)): Draw a rectangle by connecting four corners ( xmin, xmax, ymin, ymax). aes() arguments: x, y, alpha, color, group, linetype, size.Ī + geom_polygon(aes(alpha = 50)): Connect points into polygons. aes() arguments: x, xend, y, yend, alpha, angle, color, curvature, linetype, size.Ī + geom_path(lineend = "butt", linejoin = "round", linemitre = 1): Connect observations in the order they appear. ![]() Graphical PrimitivesĪ <- ggplot(economics, aes(date, unemploy)) b <- ggplot(seals, aes( x = long, y = lat))Ī + geom_blank() and a + expand_limits(): Ensure limits include values across all plots.ī + geom_curve(aes(yend = lat + 1, xend = long + 1), curvature = 1): Draw a curved line from (x, y) to (xend, yend). Use a geom function to represent data points, use the geom’s aesthetic properties to represent variables.
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