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Scale_colour_brewer() scale_fill_brewer() scale_colour_distiller() scale_fill_distiller() scale_colour_fermenter() scale_fill_fermenter() Positional scales for binning continuous data (x & y) Scale_alpha() scale_alpha_continuous() scale_alpha_binned() scale_alpha_discrete() scale_alpha_ordinal() labs() and lims() are convenient helpers for the most common adjustments to the labels and limits. Override the default scales to tweak details like the axis labels or legend keys, or to use a completely different translation from data to aesthetic. Scales control the details of how data values are translated to visual properties. Position related aesthetics: x, y, xmin, xmax, ymin, ymax, xend, yend The following help topics give a broad overview of some of the ways you can use each aesthetic.Ĭolour related aesthetics: colour, fill, and alphaĭifferentiation related aesthetics: linetype, size, shape They are used to add fixed reference data to plots.Īnnotation: high-performance rectangular tiling Stack overlapping objects on top of each anotherĪnnotations are a special type of layer that don’t inherit global settings from the plot. Override the default by using the position argument to the geom_ or stat_ function. The computed variables can be mapped using after_stat().Ĭompute empirical cumulative distributionīin and summarise in 2d (rectangle & hexagons)Īll layers have a position adjustment that resolves overlapping geoms. Line segments parameterised by location, direction and distanceĬoord_sf() geom_sf() geom_sf_label() geom_sf_text() stat_sf()Ī handful of layers are more easily specified with a stat_ function, drawing attention to the statistical transformation rather than the visual appearance. Geom_qq_line() stat_qq_line() geom_qq() stat_qq() Vertical intervals: lines, crossbars & errorbars Geom_crossbar() geom_errorbar() geom_linerange() geom_pointrange() Geom_freqpoly() geom_histogram() stat_bin() Geom_density_2d() geom_density_2d_filled() stat_density_2d() stat_density_2d_filled() Geom_contour() geom_contour_filled() stat_contour() stat_contour_filled() Reference lines: horizontal, vertical, and diagonalĪ box and whiskers plot (in the style of Tukey) Typically, you will create layers using a geom_ function, overriding the default position and stat if needed. Save a ggplot (or other grid object) with sensible defaultsĪ layer combines data, aesthetic mapping, a geom (geometric object), a stat (statistical transformation), and a position adjustment. You then add layers, scales, coords and facets with +. All ggplot2 plots begin with a call to ggplot(), supplying default data and aesthethic mappings, specified by aes().