Automatic dotplots, dots + intervals, and quantile dotplots (ggplot geom)
Geoms and stats for creating dotplots that automatically determines a bin width that
ensures the plot fits within the available space. Also ensures dots do not overlap, and allows
generation of quantile dotplots using the quantiles argument to stat_dotsinterval/stat_dots
and stat_dist_dotsinterval/stat_dist_dots. Generally follows the naming scheme and
arguments of the geom_slabinterval() and stat_slabinterval() family of
geoms and stats.
geom_dotsinterval( mapping = NULL, data = NULL, stat = "identity", position = "identity", ..., dotsize = 1, stackratio = 1, binwidth = NA, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE ) geom_dots( mapping = NULL, data = NULL, stat = "identity", position = "identity", ..., na.rm = FALSE, show.legend = NA, inherit.aes = TRUE ) stat_dotsinterval( mapping = NULL, data = NULL, geom = "dotsinterval", position = "identity", ..., quantiles = NA, point_interval = median_qi, na.rm = FALSE, show.legend = c(size = FALSE), inherit.aes = TRUE ) stat_dots( mapping = NULL, data = NULL, geom = "dots", position = "identity", ..., show.legend = NA, inherit.aes = TRUE ) stat_dist_dotsinterval( mapping = NULL, data = NULL, geom = "dotsinterval", position = "identity", ..., quantiles = 100, na.rm = FALSE, show.legend = c(size = FALSE), inherit.aes = TRUE ) stat_dist_dots( mapping = NULL, data = NULL, geom = "dots", position = "identity", ..., show.legend = NA, inherit.aes = TRUE )
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
stat |
The statistical transformation to use on the data for this layer, as a string. |
position |
Position adjustment, either as a string, or the result of a call to a position adjustment function. |
... |
Arguments passed on to
|
dotsize |
The size of the dots relative to the bin width. The default, |
stackratio |
The distance between the center of the dots in the same stack relative to the bin height. The
default, |
binwidth |
The bin width to use for drawing the dotplots. The default value, |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
geom |
Use to override the default connection between
|
quantiles |
For the |
point_interval |
A function from the |
The dots geoms are similar to geom_dotplot() but with a number of differences:
Dots geoms act like slabs in geom_slabinterval() and can be given x positions (or y positions when
in a horizontal orientation).
Given the available space to lay out dots, the dots geoms will automatically determine how many bins to use to fit the available space.
Dots geoms use a dynamic layout algorithm that lays out dots from the center out if the input data are symmetrical, guaranteeing that symmetrical data results in a symmetrical plot. The layout algorithm also prevents dots from overlapping each other.
The shape of the dots in a in these geoms can be changed using the slab_shape aesthetic (when using the
dotsinterval family) or the shape or slab_shape aesthetic (when using the dots family)
The stat_... and stat_dist_... versions of the stats when used with the quantiles argument
are particularly useful for constructing quantile dotplots, which can be an effective way to communicate uncertainty
using a frequency framing that may be easier for laypeople to understand (Kay et al. 2016, Fernandes et al. 2018).
A ggplot2::Geom or ggplot2::Stat representing a dotplot or combined dotplot+interval geometry which can
be added to a ggplot() object.
These stats support the following aesthetics:
x
y
datatype
thickness
size
group
In addition, in their default configuration (paired with geom_dotsinterval()) the following aesthetics are supported by the underlying geom:
x
y
slab_shape
datatype
alpha
colour
colour_ramp
linetype
fill
shape
stroke
point_colour
point_fill
point_alpha
point_size
size
interval_colour
interval_alpha
interval_size
interval_linetype
slab_size
slab_colour
slab_fill
slab_alpha
slab_linetype
fill_ramp
ymin
ymax
xmin
xmax
width
height
thickness
group
See examples of some of these aesthetics in action in vignette("slabinterval").
Learn more about the sub-geom aesthetics (like interval_color) in the scales documentation.
Learn more about basic ggplot aesthetics in vignette("ggplot2-specs").
Matthew Kay
Kay, M., Kola, T., Hullman, J. R., & Munson, S. A. (2016). When (ish) is My Bus? User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems. Conference on Human Factors in Computing Systems - CHI '16, 5092–5103. doi: 10.1145/2858036.2858558.
Fernandes, M., Walls, L., Munson, S., Hullman, J., & Kay, M. (2018). Uncertainty Displays Using Quantile Dotplots or CDFs Improve Transit Decision-Making. Conference on Human Factors in Computing Systems - CHI '18. doi: 10.1145/3173574.3173718.
See stat_sample_slabinterval() and stat_dist_slabinterval() for families of other
stats built on top of geom_slabinterval().
See vignette("slabinterval") for a variety of examples of use.
library(dplyr) library(ggplot2) data(RankCorr_u_tau, package = "ggdist") # orientation is detected automatically based on # which axis is discrete RankCorr_u_tau %>% ggplot(aes(x = u_tau)) + geom_dots() RankCorr_u_tau %>% ggplot(aes(y = u_tau)) + geom_dots() # stat_dots can summarize quantiles, creating quantile dotplots RankCorr_u_tau %>% ggplot(aes(x = u_tau, y = factor(i))) + stat_dots(quantiles = 100) # color and fill aesthetics can be mapped within the geom # dotsinterval adds an interval RankCorr_u_tau %>% ggplot(aes(x = u_tau, y = factor(i), fill = stat(x > 6))) + stat_dotsinterval(quantiles = 100)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.