library(ggplot2)
To display values, map variables in the data to visual properties of the geom (aesthetics) like size, color, and x and y locations.
Complete the template below to build a graph.
ggplot(data = <Data>) +
<Geom_Function>(mapping = aes(<Mappings>),
stat = <Stat>,
position = <Position>) +
<Coordinate_Function> +
<Facet_Function> +
<Scale_Function> +
<Theme_Function>
Data, a Geom Function, and Aes Mappings are required. Stat, Position, and the Coordinate, Facet, Scale, and Theme functions are not required and will supply sensible defaults.
ggplot(data = mpg, aes(x = cty, y = hwy)): Begins a plot that you finish by adding layers to. Add one geom function per layer.last_plot(): Returns the last plot.ggsave("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.
Aes¶
Common aesthetic values.
colorandfill: String ("red","#RRGGBB").linetype: Integer or string (0 ="blank", 1 ="solid", 2 ="dashed", 3 ="dotted", 4 ="dotdash", 5 ="longdash", 6 ="twodash").size: Integer (line width in mm for outlines).linewidth: Integer (line width in mm for lines).shape: Integer/shape name or a single character ("a").shapeinteger/name pairs: 0 ="square open", 1 ="circle open", 2 ="triangle open", 3 ="plus", 4 ="cross", 5 ="diamond open", 6 ="triangle down open", 7 ="square cross", 8 ="asterisk", 9 ="diamond plus", 10 ="circle plus", 11 ="star", 12 ="square plus", 13 ="circle cross", 14 ="square triangle", 15 ="square", 16 ="circle", 17 ="triangle", 18 ="diamond", 19 ="circle small", 20 ="bullet", 21 ="circle filled", 22 ="square filled", 23 ="diamond filled", 24 ="triangle filled", 25 ="triangle down filled"
Geoms¶
Use a geom function to represent data points, use the geom’s aesthetic properties to represent variables. Each function returns a layer.
Graphical Primitives¶
a <- ggplot(economics, aes(date, unemploy))
b <- ggplot(seals, aes(x = long, y = lat))
a + geom_blank()anda + expand_limits(): Ensure limits include values across all plots.b + geom_curve(aes(yend = lat + 1, xend = long + 1), curvature = 1): Draw a curved line from(x, y)to(xend, yend).aes()arguments:x,xend,y,yend,alpha,angle,color,curvature,linetype,size.a + geom_path(lineend = "butt", linejoin = "round", linemitre = 1): Connect observations in the order they appear.aes()arguments:x,y,alpha,color,group,linetype,size.a + geom_polygon(aes(alpha = 50)): Connect points into polygons.aes()arguments:x,y,alpha,color,fill,group,subgroup,linetype,size.b + 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:xmax,xmin,ymax,ymin,alpha,color,fill,linetype,size.a + geom_ribbon(aes(ymin = unemploy - 900, ymax = unemploy + 900): For eachx, plot an interval fromymintoymax.aes()arguments:x,ymax,ymin,alpha,color,fill,group,linetype,size.
Line Segments¶
Common aesthetics: x, y, alpha, color, linetype, size, linewidth.
b + geom_abline(aes(intercept = 0, slope = 1)): Draw a diagonal reference line with a givenslopeandintercept.b + geom_hline(aes(yintercept = lat)): Draw a horizontal reference line with a givenyintercept.b + geom_vline(aes(xintercept = long)): Draw a vertical reference line with a givenxintercept.b + geom_segment(aes(yend = lat + 1, xend = long + 1)): Draw a straight line from(x, y)to(xend, yend).b + geom_spoke(aes(angle = 1:1155, radius = 1)): Draw line segments using polar coordinates (angleandradius).
One Variable - Continuous¶
c <- ggplot(mpg, aes(hwy))
c2 <- ggplot(mpg)
c + geom_area(stat = "bin"): Draw an area plot.aes()arguments:x,y,alpha,color,fill,linetype,linewidth.c + geom_density(kernel = "gaussian"): Compute and draw kernel density estimates.aes()arguments:x,y,alpha,color,fill,group,linetype,linewidth,weight.c + geom_dotplot(): Draw a dot plot.aes()arguments:x,y,alpha,color,fill.c + geom_freqpoly(): Draw a frequency polygon.aes()arguments:x,y,alpha,color,group,linetype,linewidth.c + geom_histogram(binwidth = 5): Draw a histogram.aes()arguments:x,y,alpha,color,fill,linetype,linewidth,weight.c2 + geom_qq(aes(sample = hwy)): Draw a quantile-quantile plot.aes()arguments:x,y,alpha,color,fill,linetype,size,weight.
One Variable - Discrete¶
d <- ggplot(mpg, aes(fl))
d + geom_bar(): Draw a bar chart.aes()arguments:x,alpha,color,fill,linetype,linewidth,weight.
Two Variables - Both Continuous¶
e <- ggplot(mpg, aes(cty, hwy))
e + geom_label(aes(label = cty), nudge_x = 1, nudge_y = 1): Add text with a rectangle background.aes()arguments: -x,y,label,alpha,angle,color,family,fontface,hjust,lineheight,size,vjust.e + geom_point(): Draw a scatter plot.aes()arguments:x,y,alpha,color,fill,shape,size,stroke.e + geom_quantile(): Fit and draw quantile regression for the plot data.aes()arguments:x,y,alpha,color,group,linetype,linewidth,weight.e + geom_rug(sides = "bl"): Draw a rug plot.aes()arguments:x,y,alpha,color,linetype,linewidth.e + geom_smooth(method = lm): Plot smoothed conditional means.aes()arguments:x,y,alpha,color,fill,group,linetype,linewidth,weight.e + geom_text(aes(label = cty), nudge_x = 1, nudge_y = 1): Add text to a plot.aes()arguments:x,y,label,alpha,angle,color,family,fontface,hjust,lineheight,size,vjust.
Two Variables - One Discrete, One Continuous¶
f <- ggplot(mpg, aes(class, hwy))
f + geom_col(): Draw a bar plot.aes()arguments:x,y,alpha,color,fill,group,linetype,linewidth.f + geom_boxplot(): Draw a box plot.aes()arguments:x,y,lower,middle,upper,ymax,ymin,alpha,color,fill,group,linetype,shape,linewidth,weight.f + geom_dotplot(binaxis ="y", stackdir = "center"): Draw a dot plot.aes()arguments:x,y,alpha,color,fill,group.f + geom_violin(scale = "area"): Draw a violin plot.aes()arguments:x,y,alpha,color,fill,group,linetype,linewidth,weight.
Two Variables - Both Discrete¶
g <- ggplot(diamonds, aes(cut, color))
g + geom_count(): Plot a count of points in an area to address over plotting.aes()arguments:x,y,alpha,color,fill,shape,size,stroke.e + geom_jitter(height = 2, width = 2): Jitter points in a plot.aes()arguments:x,y,alpha,color,fill,shape,size.
Two Variables - Continuous Bivariate Distribution¶
h <- ggplot(diamonds, aes(carat, price))
h + geom_bin2d(binwidth = c(0.25, 500)): Draw a heatmap of 2D rectangular bin counts.aes()arguments:x,y,alpha,color,fill,linetype,size,weight.h + geom_density_2d(): Plot contours from 2D kernel density estimation.aes()arguments:x,y,alpha,color,group,linetype,linewidth.h + geom_hex(): Draw a heatmap of 2D hexagonal bin counts.aes()arguments:x,y,alpha,color,fill,linewidth.
Two Variables - Continuous Function¶
i <- ggplot(economics, aes(date, unemploy))
i + geom_area(): Draw an area plot.aes()arguments:x,y,alpha,color,fill,linetype,linewidth.i + geom_line(): Connect data points, ordered by the x axis variable.aes()arguments:x,y,alpha,color,group,linetype,linewidth.i + geom_step(direction = "hv": Draw a stairstep plot.aes()arguments:x,y,alpha,color,group,linetype,linewidth.
Two Variables - Visualizing Error¶
df <- data.frame(grp = c("A", "B"), fit = 4:5, se = 1:2)
j <- ggplot(df, aes(grp, fit, ymin = fit - se, ymax = fit + se))
j + geom_crossbar(fatten = 2): Draw a crossbar.aes()arguments:x,y,ymax,ymin,alpha,color,fill,group,linetype,linewidth.j + geom_errorbar(): Draw an errorbar. Alsogeom_errorbarh().aes()arguments:x,ymax,ymin,alpha,color,group,linetype,linewidth,width.j + geom_linerange(): Draw a line range.aes()arguments:x,ymin,ymax,alpha,color,group,linetype,linewidth.j + geom_pointrange(): Draw a point range.aes()arguments:x,y,ymin,ymax,alpha,color,fill,group,linetype,shape,linewidth.
Two Variables - Maps¶
murder_data <- data.frame(
murder = USArrests$Murder,
state = tolower(rownames(USArrests))
)
map <- map_data("state")
k <- ggplot(murder_data, aes(fill = murder))
k + geom_map(aes(map_id = state), map = map) + expand_limits(x = map$long, y = map$lat): Draw polygons as a map.aes()arguments:map_id,alpha,color,fill,linetype,linewidth.
Three Variables¶
seals$z <- with(seals, sqrt(delta_long^2 + delta_lat^2))
l <- ggplot(seals, aes(long, lat))
l + geom_contour(aes(z = z)): Draw 2D contour plot.aes()arguments:x,y,z,alpha,color,group,linetype,linewidth,weight.l + geom_contour_filled(aes(fill = z)): Draw 2D contour plot with the space between lines filled.aes()arguments:x,y,alpha,color,fill,group,linetype,linewidth,subgroup.l + geom_raster(aes(fill = z), hjust = 0.5, vjust = 0.5, interpolate = FALSE): Draw a raster plot.aes()arguments:x,y,alpha,fill.l + geom_tile(aes(fill = z)): Draw a tile plot.aes()arguments:x,y,alpha,color,fill,linetype,linewidth,width.
Stats¶
An alternative way to build a layer.
A stat builds new variables to plot (e.g., count, prop).
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). Use after_stat(name) syntax to map the stat variable name to an aesthetic.
i + stat_density_2d(aes(fill = after_stat(level)), geom = "polygon")
In this example, "polygon" is the geom to use, stat_density_2d() is the stat function, aes() contains the geom mappings, and level is the variable created by stat.
c + stat_bin(binwidth = 1, boundary = 10):x,y|count,ncount,density,ndensityc + stat_count(width = 1):x,y|count,densityc + stat_density(adjust = 1, kernel = "gaussian"):x,y|count,density,scalede + stat_bin_2d(bins = 30, drop = T):x,y,fill|count,densitye + stat_bin_hex(bins =30):x,y,fill|count,densitye + stat_density_2d(contour = TRUE, n = 100):x,y,color,linewidth|levele + stat_ellipse(level = 0.95, segments = 51, type = "t")l + stat_contour(aes(z = z)):x,y,z,order|levell + stat_summary_hex(aes(z = z), bins = 30, fun = max):x,y,z,fill|valuel + stat_summary_2d(aes(z = z), bins = 30, fun = mean):x,y,z,fill|valuef + stat_boxplot(coef = 1.5):x,y|lower,middle,upper,width,ymin,ymaxf + stat_ydensity(kernel = "gaussian", scale = "area"):x,y|density,scaled,count,n,violinwidth,widthe + stat_ecdf(n = 40):x,y|x,ye + stat_quantile(quantiles = c(0.1, 0.9), formula = y ~ log(x), method = "rq"):x,y|quantilee + stat_smooth(method = "lm", formula = y ~ x, se = T, level = 0.95):x,y|se,x,y,ymin,ymaxggplot() + xlim(-5, 5) + stat_function(fun = dnorm, n = 20, geom = "point"):x|x,yggplot() + stat_qq(aes(sample = 1:100)):x,y,sample|sample,theoreticale + stat_sum():x,y,size|n,prope + stat_summary(fun.data = "mean_cl_boot")h + stat_summary_bin(fun = "mean", geom = "bar")e + stat_identity()e + stat_unique()
Scales¶
Override defaults with scales package.
Scales map data values to the visual values of an aesthetic. To change a mapping, add a new scale.
n <- d + geom_bar(aes(fill = fl))
n + scale_fill_manual(
value = c(),
limits = c(),
breaks = c(),
name = "fuel",
labels = c("D", "E", "P", "R")
)
In this example, scale_ specifies a scale function, fill is the aesthetic to adjust, and manual is the prepackaged scale to use.
values contains scale-specific arguments, limits specifies the range of values to include in mappings, breaks specifies the breaks to use in legend/axis, and name and labels specify the title and labels to use in the legend/axis.
General Purpose Scales¶
Use with most aesthetics.
scale_*_continuous(): Map continuous values to visual ones.scale_*_discrete(): Map discrete values to visual ones.scale_*_binned(): Map continuous values to discrete bins.scale_*_identity(): Use data values as visual ones.scale_*_manual(values = c()): Map discrete values to manually chosen visual ones.scale_*_date(date_labels = "%m/%d", date_breaks = "2 weeks"): Treat data values as dates.scale_*_datetime(): Treat data values as date times. Same asscale_*_date(). See?strptimefor label formats.
X & Y Location Scales¶
Use with x or y aesthetics (x shown here).
scale_x_log10(): Plotxon log10 scale.scale_x_reverse(): Reverse the direction of the x axis.scale_x_sqrt(): Plotxon square root scale.
Color and Fill Scales (Discrete)¶
n + scale_fill_brewer(palette = "Blues"): Use color scales from ColorBrewer. For palette choicesRColorBrewer::display.brewer.all().n + scale_fill_grey(start = 0.2, end = 0.8, na.value = "red"): Use a grey gradient color scale.
Color and Fill Scales (Continuous)¶
o <- c + geom_dotplot(aes(fill = ..x..))
o + scale_fill_distiller(palette = "Blues"): Interpolate a palette into a continuous scale.o + scale_fill_gradient(low = "red", high = "yellow"): Create a two color gradient.o + scale_fill_gradient2(low = "red", high = "blue", mid = "white", midpoint = 25): Create a diverging color gradient.o + scale_fill_gradientn(colors = topo.colors(6)): Create a n-color gradient. Alsorainbow(),heat.colors(),terrain.colors(),cm.colors(),RColorBrewer::brewer.pal().
Shape and Size Scales¶
p <- e + geom_point(aes(shape = fl, size = cyl))
p + scale_shape() + scale_size(): Map discrete values to shape and size aesthetics.p + scale_shape_manual(values = c(3:7)): Map discrete values to specified shape values.p + scale_radius(range = c(1,6)): Map values to a shape’s radius.p + scale_size_area(max_size = 6): Likescale_size()but maps zero values to zero size.
Shapes used here are the same as the ones listed in the Aes section.
Coordinate Systems¶
u <- d + geom_bar()
u + coord_cartesian(xlim = c(0, 5)):xlim,ylim. The default Cartesian coordinate system.u + coord_fixed(ratio = 1/2):ratio,xlim,ylim. Cartesian coordinates with fixed aspect ration between x and y units.ggplot(mpg, aes(y = fl)) + geom_bar(): Flip Cartesian coordinates by switching x and y aesthetic mappings.u + coord_polar(theta = "x", direction = 1):theta,start,direction. Polar coordinates.u + coord_trans(y = "sqrt"):x,y,xlim,ylim. Transformed Cartesian coordinates. Setxtransandytransto the name of a window function.π + coord_quickmap(); π + coord_map(projection = "ortho", orientation = c(41, -74, 0)):projection,xlim,ylim. Map projections from the mapproj packages (mercator(default),azequalarea,lagrange, etc.).
Position Adjustments¶
Position adjustments determine how to arrange geoms that would otherwise occupy the same space.
s <- ggplot(mpg, 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.e + geom_point(position = "jitter"): Add random noise to X and Y position of each element to avoid over plotting.e + geom_label(position = "nudge"): Nudge labels away from points.s + geom_bar(position = "stack"): Stack elements on top of one another.
Each position adjustment can be recast as a function with manual width and height arguments:
s + geom_bar(position = position_dodge(width = 1))
Themes¶
u + theme_bw(): White background with grid lines.u + theme_gray(): Grey background with white grid lines (default theme).u + theme_dark(): Dark grey background and grid lines for contrast.u + theme_classic(): No grid lines.u + theme_light(): Light grey axes and grid lines.u + theme_linedraw(): Uses only black lines.u + theme_minimal(): Minimal theme.u + theme_void(): Empty theme.u + theme(): Customize aspects of the theme such as axis, legend, panel, and facet properties.
r + ggtitle("Title") + theme(plot.title.postion = "plot")
r + theme(panel.background = element_rect(fill = "blue"))
Faceting¶
Facets divide a plot into subplots based on the values of one or more discrete variables.
t <- ggplot(mpg, aes(cty, hwy)) + geom_point()
t + facet_grid(. ~ fl): Facet into a column based on fl.t + facet_grid(year ~ .): Facet into rows based on year.t + facet_grid(year ~ fl): Facet into both rows and columns.t + facet_wrap(~ fl): Wrap facets into a rectangular layout.t + facet_grid(drv ~ fl, scales = "free"): Set scales to let axis limits vary across facets. Also"free_x"for x axis limits adjust to individual facets and"free_y"for y axis limits adjust to individual facets.
Set labeller to adjust facet label:
t + facet_grid(. ~ fl, labeller = label_both): Labels each facet as “fl: c”, “fl: d”, etc.t + facet_grid(fl ~ ., labeller = label_bquote(alpha ^ .(fl))): Labels each facet as “𝛼c”, “𝛼d”, etc.
Labels and Legends¶
Use labs() to label elements of your plot.
t + labs(x = "New x axis label",
y = "New y axis label",
title ="Add a title above the plot",
subtitle = "Add a subtitle below title",
caption = "Add a caption below plot",
alt = "Add alt text to the plot",
<Aes> = "New <Aes> legend title")
t + annotate(geom = "text", x = 8, y = 9, label = "A"): Places a geom with manually selected aesthetics.p + guides(x = guide_axis(n.dodge = 2)): Avoid crowded or overlapping labels withguide_axis(n.dodge or angle).n + guides(fill = "none"): Set legend type for each aesthetic:colorbar,legend, ornone(no legend).n + theme(legend.position = "bottom"): Place legend at “bottom”, “top”, “left”, or “right”.n + scale_fill_discrete(name = "Title", labels = c("A", "B", "C", "D", "E")): Set legend title and labels with a scale function.
Zooming¶
t + coord_cartesian(xlim = c(0, 100), ylim = c(10,20)): Zoom without clipping (preferred).t + xlim(0, 100) + ylim(10, 20)ort + scale_x_continuous(limits = c(0, 100)) + scale_y_continuous(limits = c(0, 100)): Zoom with clipping (removes unseen data points).