Geoms - Use a geom to represent data points, use the geom's aesthetic properties to represent variables. Each function returns a layer. One Variable Two Variables
Cheatsheet f ^Studio
ggplot2 is based on the grammar of graphics, the
idea that you can build every graph from the same few components: a data set, a set of geoms—visual marks that represent data points, and a coordinate
system.
			
•			
data    geom coordinate »;f system
plot
To display data values, map variables in the data set to aesthetic properties of the geom like size, color, and x and y locations.
data    geom coordinate x=f system
Build a graph with qplot() orggplot()
aesthetic mappings
		
		
		
plot		
qplot(x = cty, y = hwy, color = cyl, data = mpg, geom = "point") Creates a complete plotwith given data, geom, and mappings. Supplies many useful defaults.
ggplot(data = mpg, aes(x = cty, y = hwy))
Begins a plot that you finish by adding layers to. No defaults, but provides more control than qplotfj.
ggplottmpg, aeslhwy, cty)) geom_point(aes( color = cyU) geom_smootfi (method ="lm") + coord_cartesian() + scale_color_gradient() + theme_bw()
Add a new layer to a plotwith a geom_*() orstat_*() function. Each provides a geom, a set of aesthetic mappings, and a default stat and position adjustment.
last_plot()
Returns the last plot
ggsavef'plot.png", width = 5, height = 5)
Saves last plot as 5' x 5' file named "plot.png" in working directory. Matches file type to file extension.
A
□
Continuous
a <- ggplot(mpg, aes(hwy))
geom_area(stat= "bin")
x, y, alpha, color, fill, linetype, size
b + geom_area(aes(y = ..density..), stat = "bin")
geom_density(kernel = "gaussian") x, y, alpha, color, fill, linetype, size, weight b + geom_density(aes(y = ..county..))
geom_dotplot() x, y, alpha, color, fill
geom_freqpoly()
x, y, alpha, color, linetype, size o + geom_freqpoly(aes(y = ..density..)) geom_histogram(binwidth = 5)
x, y, alpha, color, fill, linetype, size, weight b + geom_histogram(aes(y = ..density..))
Discrete
b <- ggplotfmpg, aes(fl))
geom_bar()
x, alpha, color, fill, linetype, size, weight
Graphical Primitives
c <- ggplot(map, aes(long, lat)) geom_poIygon(aes(group = group)) x, y, alpha, color, fill, linetype, size
d <- ggplotfeconomics, acs(date, unemploy))
geom_path(lineend=,,buttM,
linejoin-'round', linemitre=l)
x, y, alpha, color, linetype, size geom_ribbon(aes(ymin=unemploy-900;
ymax=unemploy + 900)) x, ymax, ymin, alpha, color, fill, linetype, size
e <- ggplot(seals, aes(x = long, y = lat))
geom_segment(aes(
xend = long + deltajong, yend = lat + delta_lat))
x, xend, y, yend, alpha, color, linetype, size
geom_rect(aes(xmin = long, ymin = lat, xmax= long + deltajong, ymax = lat + deltajat))
xmax, xmin, ymax, ymin, alpha, color, fill, .inetype, size
Continuous X, Continuous Y
f <- ggplotfmpg, aesfcty, hwy))
geom_blank()
geomJitterO
x, y, alpha, color, fill, shape, size
geom_point()
x, y, alpha, color, fill, shape, size
geom_quantile()
x, y, alpha, color, linetype, size, weight
geom_rug(sides = "bl")
alpha, color, linetype, size
geom_smooth(model = Im)
x, y, alpha, color, fill, linetype, size, weight
geom_text(aes(label = cty))
x, y, label, alpha, angle, color, family, fontface, hjust, lineheight, size, vjust
Discrete X, Continuous Y
g <- ggplotl mpg. acslclass, hwy))
geom_bar(stat = "identity")
x, y, alpha, color, fill, linetype, size, weight
geom_boxplot()
.ower, middle, upper, x, ymax, ymin, alpha, color, fill, linetype, shape, size, weight geom_dotplot(binaxis = "y",
stackdir = "center") x, y, alpha, color, fill geom_vioIin(scale = "area")
x, y, alpha, color, fill, linetype, size, weight
Discrete X, Discrete Y
h <- ggplotfdiamonds, aesfcut, color))
mi
geomJitterQ
x, y, alpha, color, fill, shape, size
Continuous Bivariate Distribution
i <- ggplotfmovies, aesfyear, rating))
geom_bin2d(binwidth = c(5, 0.5)) xmax, xmin, ymax, ymin, alpha, color, fill linetype, size, weight i + geom_density2d()
x, y, alpha, colour, linetype, size
geom_hex()
x, y, alpha, colour, fill size
Continuous Function
j <- ggplotfeconomics, aes(date, unemploy))
geom_area()
x, y, alpha, color, fill, linetype, size
j + geom_line()
at       x, y, alpha, color, linetype, size
_ geom_step(direction = "hv") nJl"      x, y, alpha, color, linetype, size
Visualizing error
df <- data.frame(grp = c("A", "B"), fit = 4:5, se = 1:2) k <- ggplot(df, aes(grp, fit, ymin = fit-se, ymax = fit+se))
geom_crossbar(fatten = 2)
x, y, ymax, ymin, alpha, color, fill, linetype,
size
geom_errorbar()
x, ymax, ymin, alpha, color, linetype, size, width (also geom_errorbarh()) geom_Iinerange()
x, ymin, ymax, alpha, color, linetype, size
geom_pointrange()
x, y, ymin, ymax, alpha, color, fill, linetype. shape, size
Maps
data <- data.frame(murder= USArrests$Murder,
state = tolower(rownames(USArrests))) map <- map_data("state") I <- ggplot(data, aes(fill = murder))
geom_map(aes(map_id = state), map = map) + expand_limits(x = map$long, y = mapSlat) map_id, alpha, color, fill, linetype, size
Three Variables				
seals$z<-with (seals, sqrt(delta_longA2 + delta_latA2)) m <- ggplot(seals, aes(long, lat))		r		geom_raster(aes(fill =z), hjust=0.5, vjust=0.5, interpolate=FALSE) x, y, alpha, fill geom_tiIe(aes(fill = z)) x, y, alpha, color, fill, linetype, size
	geom_contour(aes(z = z)) x, y, z, alpha, colour, linetype, size, weight	r	i	
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Stats - An alternative way to build a layer
Scales
Some plots visualize a transformation of the original data set.    Scales control how a plot maps data values to the visual
Use a stat to choose a common transformation to visualize, e.g. a + geom_bar(stat = "bin") ED El EE
data stat      geom   coordinate plot
y = *count System
Each stat creates additional variables to map aesthetics to. These variables use a common ..name., syntax.
stat functions and geom functions both combine a stat with a geom to make a layer, i.e. stat_bin(geom="bar") does the same asgeom_bar(stat="bin")
layer specific T variable created stat function \    mappings    g_ by transformation
values of an aesthetic. To change the mapping, add a custom scale.
geom_bar(aes(fi II = fl))
scale   ! aestnetic I prepackaged [ scale specific ~ 1 to adjust 1 scale to use 1 arguments
n + scale_fill_manual(
values = c("skyblue", "royalblue", "blue", "navy") limits = c("d", "e", "p", "r"), breaks =c("d", "e", "p", name = "fuel", labels = c("D", "E", "P", "R")) 1
stat_density2d(aes(fill = ..level., "polygon", n = 100)
geom =
eom for layer
a + stat_bin(binwjdth = 1, origin = 10) x, y | ..count.., ..ncount.., ..density.., ..ndensity..
a + stat_bindot(binwidth = 1, binaxis = "x") x, y, | ..count.., ..ncount..
a + stat_density(adjust = 1, kernel = "gaussian") x, y, | ..count.., ..density.., ..scaled..
f + stat_bin2d(bins = 30, drop = TRU E)
x, y, fill | ..count.., ..density., f+ stat_binhex(bins = 30)
x, y, fill | ..count.., ..density., f+ stat_density2d(contour = TRUE, n = 100)
x, y, color, size | ..level..
2D distributions
n+stat_contour(aes(z = z))
x, y, z, order | ..level.. m+ stat_spoke(aes(radius= z, angle = z))
angle, radius, x, xend, y, yend | ..x.., ..xend.., ..y.., ..yend.. n + stat_summary_hex(aes(z = z), bins = 30, fun = mean)
x, y, z, fill | ..value.. stat_summary2d(aes(z = z), bins = 30, fun = mean)
x, y, z, fill | ..value..
rangeofvaluesto include in mapping I
General Purpose scales
Use with any aesthetic: alpha, color, fill, linetype, shape, size
scale_*_continuous{) - map cont' values to visual values scale_*_discrete{) - map discrete values to visual values scale_*_identity{) - use data values as visual values scale_*_manual{values = c()) - map discrete values to manually chosen visual values
X and Y location scales
Use with x ory aesthetics (x shown here)
scale_x_date{labels = date_format("%m/%d"), breaks = date_breaks("2 weeks")) - treat x values as dates. See ?strptimefor label formats.
scale_x_datetime{) - treat x values as date times. Use same arguments asscale_x_date().
scale_x_loglO{) - Plot x on loglO scale
scale_x_reverse{) - Reverse direction of x axis
scale_x_sqrt{) - Plot x on square root scale
Color and fill scales
Discrete
Continuous
geom_bar(
aes(fill = fl))
I scale_fill_brewer(
palette = "Blues") '    For palette choices: library(RcolorBrewer) display.brewer.allQ
I n + scale_fill_grey(
start = 0.2, end =0.8, I   na.value = "red")
g + stat_boxplot(coef=1.5)
x,y | ..lower.., ..middle.., ..upper.., ..outliers., g + stat_ydensity(adjust= 1, kernel = "gaussian", scale = "area") x,y | ..density.., ..scaled.., ..count.., ..n.., ..violinwidth.., ..width..
stat_ecdf(n=40) x,y| ..x.., ..y..
f + stat_quantile(quantiles = c(0.25, 0.5, 0.75), formula =y - log(x),
method = "rq")
x, y | ..quantile.., ..x.., ..y.. f + stat_smooth(method = "auto", formula =y - x, se = TRUE, n = 80,
fullrange = FALSE, level = 0.95)
x, y | ..se.., ..x.., ..y.., ..ymin.., ..ymax..
stat_function(aes(x = -3:3), fun = dnorm, n = 101, args= list(sd =0.5)) x| ..y.. f+ stat_identity()
() + stat_qq(aes(sample=l:100), distribution = qt, dparams = list(df=5)) sample, x, y | ..x.., ..y.. stat_sum() x, y, size | ..size..
stat_summary(fun.data = "mean_cl_boot") f+ stat_unique()
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o <- a + geom_dotplot(
aes(fill = ..x..))
scale_fill_gradient(
low = "red", high = "yellow") scale_fill_gradient2(
low= "red", hight = "blue", mid = "white", midpoint = 25) o + scale_fill_gradientn(
colours = terrain. colors(6)) Also: rainbowQ, heat.colors(), topo.colorsQ, cm.colors(), RColorBrewer::brewer.pal()
4v
f + geom_point(
aes(shape = fl))
p +scale_shape(
solid = FALSE)
scale_shape_manual(
values = c(3:7)) Shape values shown in chart on right
Shape scales
Manual shape values
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Size scales
f + geom_point(
aes(size = cylj)
scale_size_area(max = 6)
Value mapped to area of circle (not radius)
.ill
Coordinate Systems
r<- b + geom_bar() ' + coord_cartesian(xlim = c(0,5)) xlim, ylim
The default cartesian coordinate system coord_fixed(ratio = 1/2)
ratio, xlim, ylim
Cartesian coordinates with fixed aspect ratio between x and y units
' + coord_flip()
xlim, ylim
Flipped Cartesian coordinates ' + coord_polar(theta = "x", direction=l)
theta, start, direction Polar coordinates ' + coord_trans(ytrans = "sqrt")
xtrans, ytrans, limx, limy Transformed cartesian coordinates. Set extras and strains to the name of a window function.
ortho",
coord_map(projection
orientation=c(41,-74, 0))
projection, orientation, xlim, ylim Map projections from the mapproj package (mercator (default), azequalarea, lagrange, etc.]
Position Adjustments
Position adjustments determine how to arrange geoms that would otherwise occupy the same space, s <- ggplotfmpg, aes(fl, fill = drv))
s + geom_bar(position = "dodge")
Arrange elements side by side
s + geom_bar(position = "fill")
Stack elements on top of one another, normalize height
ar(position = "stack")
Stack elements on top of one another
position = "jitter")
Add random noise to X and Y position of each element to avoid overplotting
Each position adjustment can be recast as a function with manual width and height arguments
i_bar(position = position_dodge(width = 1))
Themes
LJ
r + theme_bw{)
White background with grid lines r + theme_grey{)
Grey background (default theme)
LJ
Package with additional ggplot2 themes
Facetin
Facets divide a plot into subplots based on the values of one or more discrete variables, t <- ggplotfmpg, aesfcty, hwy)) + geom_point()
t + facet_grid(. ~f[)
facet into columns based on fl facet_grid(year~.)
facet into rows based on year
facet_grid(year~ fl)
facet into both rows and columns t + facet_wrap(~ fl)
wrap facets into a rectangular layout
Set scales to let axis limits vary across facets <~x, scales = "free")
x and y axis limits adjust to individual facets
• "free_x" - x axis limits adjust
• "free_y" - y axis limits adjust
Set labeller to adjust facet labels
fl, labeller = label_both) fl: c fl: d fl: e fl: p fl: r
■id(. - fl, labeller = label_bquote(alpha A (x)))
ac ad ae op ar
t + facet_grid(. - fl, labeller = label_parsed)
Labels
ggtitle("New Plot Title")
Add a main title above the plot t + xlab("NewX label")
Change the label on the X axis t + ylab("NewY label")
Change the label on the Y axis : + labs(title =" New title", x = "New x", y = "New y")
All of the above
Use scale functions to update legend
theme_classic{)
White background no gridlines
h theme_minimal{)
Minimal theme
Legends
themeflegend.position = "bottom")
Place legend at "bottom", "top", "left", or "right"
t + guidesfcolor = "none")
Set legend type for each aesthetic: colorbar, legend, or none (no legend)
scale_fill_discrete(name = "Title", labels = c("A", "B", "C")) Set legend title and labels with a scale function.
Zoomin
Without clipping (preferred) t + coord_cartesian(
xlim = c(0,100), ylim = c(10,20))
With clipping (removes unseen data points) t + xlim(0,100) + ylim(10, 20)
^ scale_x_continuous(limits = c(0,100)) + scale_y_continuous(limits = c(0,100))
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