Extra Coordinate Systems, 'Geoms', Statistical Transformations, Scales and Fonts for 'ggplot2'

A compendium of new geometries, coordinate systems, statistical transformations, scales and fonts for 'ggplot2', including splines, 1d and 2d densities, univariate average shifted histograms, a new map coordinate system based on the 'PROJ.4'-library along with geom_cartogram() that mimics the original functionality of geom_map(), formatters for "bytes", a stat_stepribbon() function, increased 'plotly' compatibility and the 'StateFace' open source font 'ProPublica'. Further new functionality includes lollipop charts, dumbbell charts, the ability to encircle points and coordinate-system-based text annotations.


Project Status: Active - The project has reached a stable, usable state and is being actively developed. Travis-CI Build Status CRAN_Status_Badge downloads

ggalt : Extra Coordinate Systems, Geoms, Statistical Transformations, Scales & Fonts for 'ggplot2'

A compendium of 'geoms', 'coords', 'stats', scales and fonts for 'ggplot2', including splines, 1d and 2d densities, univariate average shifted histograms, a new map coordinate system based on the 'PROJ.4'-library and the 'StateFace' open source font 'ProPublica'.

The following functions are implemented:

  • coord_proj : Like coord_map, only better (prbly shld use this with geom_cartogram as geom_map's new defaults are ugh)
  • geom_xspline : Connect control points/observations with an X-spline
  • stat_xspline : Connect control points/observations with an X-spline
  • geom_bkde : Display a smooth density estimate (uses KernSmooth::bkde)
  • geom_stateface: Use ProPublica's StateFace font in ggplot2 plots- stat_bkde : Display a smooth density estimate (uses KernSmooth::bkde)
  • geom_bkde2d : Contours from a 2d density estimate. (uses KernSmooth::bkde2D)
  • stat_bkde2d : Contours from a 2d density estimate. (uses KernSmooth::bkde2D)
  • stat_ash : Compute and display a univariate averaged shifted histogram (polynomial kernel) (uses ash::ash1/ash::bin1)
  • geom_encircle: Automatically enclose points in a polygon
  • byte_format: + helpers. e.g. turn 10000 into 10 Kb
  • geom_lollipop(): Dead easy lollipops (horizontal or vertical)
  • geom_dumbbell() : Dead easy dumbbell plots
  • stat_stepribbon() : Step ribbons
  • plotly integration for a few of the ^^ geoms
# you'll want to see the vignettes, trust me
install.packages("ggplot2")
install.packages("ggalt")
# OR: devtools::install_github("hrbrmstr/ggalt")

Usage

library(ggplot2)
library(gridExtra)
library(ggalt)
 
# current verison
packageVersion("ggalt")
## [1] '0.4.0'
 
set.seed(1492)
dat <- data.frame(x=c(1:10, 1:10, 1:10),
                  y=c(sample(15:30, 10), 2*sample(15:30, 10), 3*sample(15:30, 10)),
                  group=factor(c(rep(1, 10), rep(2, 10), rep(3, 10)))
)

Splines!

ggplot(dat, aes(x, y, group=group, color=group)) +
  geom_point() +
  geom_line()
 
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
  geom_point() +
  geom_line() +
  geom_smooth(se=FALSE, linetype="dashed", size=0.5)
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
 
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
  geom_point(color="black") +
  geom_smooth(se=FALSE, linetype="dashed", size=0.5) +
  geom_xspline(size=0.5)
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
 
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
  geom_point(color="black") +
  geom_smooth(se=FALSE, linetype="dashed", size=0.5) +
  geom_xspline(spline_shape=-0.4, size=0.5)
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
 
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
  geom_point(color="black") +
  geom_smooth(se=FALSE, linetype="dashed", size=0.5) +
  geom_xspline(spline_shape=0.4, size=0.5)
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
 
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
  geom_point(color="black") +
  geom_smooth(se=FALSE, linetype="dashed", size=0.5) +
  geom_xspline(spline_shape=1, size=0.5)
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
 
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
  geom_point(color="black") +
  geom_smooth(se=FALSE, linetype="dashed", size=0.5) +
  geom_xspline(spline_shape=0, size=0.5)
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
 
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
  geom_point(color="black") +
  geom_smooth(se=FALSE, linetype="dashed", size=0.5) +
  geom_xspline(spline_shape=-1, size=0.5)
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'

Alternate (better) density plots

# bkde
 
data(geyser, package="MASS")
 
ggplot(geyser, aes(x=duration)) + 
  stat_bkde(alpha=1/2)
## Bandwidth not specified. Using '0.14', via KernSmooth::dpik.
 
ggplot(geyser, aes(x=duration)) +
  geom_bkde(alpha=1/2)
## Bandwidth not specified. Using '0.14', via KernSmooth::dpik.
 
ggplot(geyser, aes(x=duration)) + 
  stat_bkde(bandwidth=0.25)
 
ggplot(geyser, aes(x=duration)) +
  geom_bkde(bandwidth=0.25)
 
set.seed(1492)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), 
                   rating = c(rnorm(200),rnorm(200, mean=.8)))
 
ggplot(dat, aes(x=rating, color=cond)) + geom_bkde(fill="#00000000")
## Bandwidth not specified. Using '0.36', via KernSmooth::dpik.
## Bandwidth not specified. Using '0.31', via KernSmooth::dpik.
 
ggplot(dat, aes(x=rating, fill=cond)) + geom_bkde(alpha=0.3)
## Bandwidth not specified. Using '0.36', via KernSmooth::dpik.
## Bandwidth not specified. Using '0.31', via KernSmooth::dpik.
 
# ash
 
set.seed(1492)
dat <- data.frame(x=rnorm(100))
grid.arrange(ggplot(dat, aes(x)) + stat_ash(),
             ggplot(dat, aes(x)) + stat_bkde(),
             ggplot(dat, aes(x)) + stat_density(),
             nrow=3)
## Estimate nonzero outside interval ab.
## Bandwidth not specified. Using '0.43', via KernSmooth::dpik.
 
cols <- RColorBrewer::brewer.pal(3, "Dark2")
ggplot(dat, aes(x)) + 
  stat_ash(alpha=1/3, fill=cols[3]) + 
  stat_bkde(alpha=1/3, fill=cols[2]) + 
  stat_density(alpha=1/3, fill=cols[1]) + 
  geom_rug() +
  labs(x=NULL, y="density/estimate") +
  scale_x_continuous(expand=c(0,0)) +
  theme_bw() +
  theme(panel.grid=element_blank()) +
  theme(panel.border=element_blank())
## Estimate nonzero outside interval ab.
## Bandwidth not specified. Using '0.43', via KernSmooth::dpik.

Alternate 2D density plots

m <- ggplot(faithful, aes(x = eruptions, y = waiting)) +
       geom_point() +
       xlim(0.5, 6) +
       ylim(40, 110)
 
m + geom_bkde2d(bandwidth=c(0.5, 4))
 
m + stat_bkde2d(bandwidth=c(0.5, 4), aes(fill = ..level..), geom = "polygon")

coord_proj LIVES! (still needs a teensy bit of work)

world <- map_data("world")
world <- world[world$region != "Antarctica",]
 
gg <- ggplot()
gg <- gg + geom_cartogram(data=world, map=world,
                    aes(x=long, y=lat, map_id=region))
gg <- gg + coord_proj("+proj=wintri")
gg

ProPublica StateFace

# Run show_stateface() to see the location of the TTF StateFace font
# You need to install it for it to work
 
set.seed(1492)
dat <- data.frame(state=state.abb,
                  x=sample(100, 50),
                  y=sample(100, 50),
                  col=sample(c("#b2182b", "#2166ac"), 50, replace=TRUE),
                  sz=sample(6:15, 50, replace=TRUE),
                  stringsAsFactors=FALSE)
gg <- ggplot(dat, aes(x=x, y=y))
gg <- gg + geom_stateface(aes(label=state, color=col, size=sz))
gg <- gg + scale_color_identity()
gg <- gg + scale_size_identity()
gg

Encircling points automagically

d <- data.frame(x=c(1,1,2),y=c(1,2,2)*100)
 
gg <- ggplot(d,aes(x,y))
gg <- gg + scale_x_continuous(expand=c(0.5,1))
gg <- gg + scale_y_continuous(expand=c(0.5,1))
 
gg + geom_encircle(s_shape=1, expand=0) + geom_point()
 
gg + geom_encircle(s_shape=1, expand=0.1, colour="red") + geom_point()
 
gg + geom_encircle(s_shape=0.5, expand=0.1, colour="purple") + geom_point()
 
gg + geom_encircle(data=subset(d, x==1), colour="blue", spread=0.02) +
  geom_point()
 
gg +geom_encircle(data=subset(d, x==2), colour="cyan", spread=0.04) + 
  geom_point()
 
gg <- ggplot(mpg, aes(displ, hwy))
gg + geom_encircle(data=subset(mpg, hwy>40)) + geom_point()
 
ss <- subset(mpg,hwy>31 & displ<2)
 
gg + geom_encircle(data=ss, colour="blue", s_shape=0.9, expand=0.07) +
  geom_point() + geom_point(data=ss, colour="blue")

Step ribbons

x <- 1:10
df <- data.frame(x=x, y=x+10, ymin=x+7, ymax=x+12)
 
gg <- ggplot(df, aes(x, y))
gg <- gg + geom_ribbon(aes(ymin=ymin, ymax=ymax),
                      stat="stepribbon", fill="#b2b2b2")
gg <- gg + geom_step(color="#2b2b2b")
gg
 
gg <- ggplot(df, aes(x, y))
gg <- gg + geom_ribbon(aes(ymin=ymin, ymax=ymax),
                      stat="stepribbon", fill="#b2b2b2",
                      direction="vh")
gg <- gg + geom_step(color="#2b2b2b")
gg

Lollipop charts

df <- read.csv(text="category,pct
Other,0.09
South Asian/South Asian Americans,0.12
Interngenerational/Generational,0.21
S Asian/Asian Americans,0.25
Muslim Observance,0.29
Africa/Pan Africa/African Americans,0.34
Gender Equity,0.34
Disability Advocacy,0.49
European/European Americans,0.52
Veteran,0.54
Pacific Islander/Pacific Islander Americans,0.59
Non-Traditional Students,0.61
Religious Equity,0.64
Caribbean/Caribbean Americans,0.67
Latino/Latina,0.69
Middle Eastern Heritages and Traditions,0.73
Trans-racial Adoptee/Parent,0.76
LBGTQ/Ally,0.79
Mixed Race,0.80
Jewish Heritage/Observance,0.85
International Students,0.87", stringsAsFactors=FALSE, sep=",", header=TRUE)
 
library(ggplot2)
library(ggalt)
library(scales)
 
gg <- ggplot(df, aes(y=reorder(category, pct), x=pct))
gg <- gg + geom_lollipop(point.colour="steelblue", point.size=2, horizontal=TRUE)
gg <- gg + scale_x_continuous(expand=c(0,0), labels=percent,
                              breaks=seq(0, 1, by=0.2), limits=c(0, 1))
gg <- gg + labs(x=NULL, y=NULL, 
                title="SUNY Cortland Multicultural Alumni survey results",
                subtitle="Ranked by race, ethnicity, home land and orientation\namong the top areas of concern",
                caption="Data from http://stephanieevergreen.com/lollipop/")
gg <- gg + theme_minimal(base_family="Arial Narrow")
gg <- gg + theme(panel.grid.major.y=element_blank())
gg <- gg + theme(panel.grid.minor=element_blank())
gg <- gg + theme(axis.line.y=element_line(color="#2b2b2b", size=0.15))
gg <- gg + theme(axis.text.y=element_text(margin=margin(r=0, l=0)))
gg <- gg + theme(plot.margin=unit(rep(30, 4), "pt"))
gg <- gg + theme(plot.title=element_text(face="bold"))
gg <- gg + theme(plot.subtitle=element_text(margin=margin(b=10)))
gg <- gg + theme(plot.caption=element_text(size=8, margin=margin(t=10)))
gg
library(dplyr)
library(tidyr)
library(scales)
library(ggplot2)
library(ggalt) # devtools::install_github("hrbrmstr/ggalt")
 
health <- read.csv("https://rud.is/dl/zhealth.csv", stringsAsFactors=FALSE, 
                   header=FALSE, col.names=c("pct", "area_id"))
 
areas <- read.csv("https://rud.is/dl/zarea_trans.csv", stringsAsFactors=FALSE, header=TRUE)
 
health %>% 
  mutate(area_id=trunc(area_id)) %>% 
  arrange(area_id, pct) %>% 
  mutate(year=rep(c("2014", "2013"), 26),
         pct=pct/100) %>% 
  left_join(areas, "area_id") %>% 
  mutate(area_name=factor(area_name, levels=unique(area_name))) -> health
 
setNames(bind_cols(filter(health, year==2014), filter(health, year==2013))[,c(4,1,5)],
         c("area_name", "pct_2014", "pct_2013")) -> health
 
gg <- ggplot(health, aes(x=pct_2014, xend=pct_2013, y=area_name, group=area_name))
gg <- gg + geom_dumbbell(colour="#a3c4dc", size=1.5, colour_xend="#0e668b", 
                         dot_guide=TRUE, dot_guide_size=0.15)
gg <- gg + scale_x_continuous(label=percent)
gg <- gg + labs(x=NULL, y=NULL)
gg <- gg + theme_bw()
gg <- gg + theme(plot.background=element_rect(fill="#f7f7f7"))
gg <- gg + theme(panel.background=element_rect(fill="#f7f7f7"))
gg <- gg + theme(panel.grid.minor=element_blank())
gg <- gg + theme(panel.grid.major.y=element_blank())
gg <- gg + theme(panel.grid.major.x=element_line())
gg <- gg + theme(axis.ticks=element_blank())
gg <- gg + theme(legend.position="top")
gg <- gg + theme(panel.border=element_blank())
gg
library(hrbrthemes)
 
df <- data.frame(trt=LETTERS[1:5], l=c(20, 40, 10, 30, 50), r=c(70, 50, 30, 60, 80))
 
ggplot(df, aes(y=trt, x=l, xend=r)) + 
  geom_dumbbell(size=3, color="#e3e2e1", 
                colour_x = "#5b8124", colour_xend = "#bad744",
                dot_guide=TRUE, dot_guide_size=0.25) +
  labs(x=NULL, y=NULL, title="ggplot2 geom_dumbbell with dot guide") +
  theme_ipsum_rc(grid="X") +
  theme(panel.grid.major.x=element_line(size=0.05))

Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

News

0.4.0

  • Fixed coord_proj()
  • Removed pokemon colors (et al)
  • Added dotted-gridline guide for geom\_dumbbell()
  • Complete parameter re-write to geom\_dumbbell()
  • New geoms & stats by Ben Bolker, Jan Schulz and Carson Sievert
  • Ben Marwick also did his best to keep up with my fat-fingering but I'm snuck a few in before the release

0.3.0

  • Added geom_lollipop() to make it easer to create lollipop charts

0.2.0

  • Incorporated ProPublica StateFace font
  • geom_encircle() contributed by Ben Bolker

0.1.5

  • Pokemon discrete color scales!
  • byte_format (et al) scales (e.g. 10000 => 10 Kb)

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("ggalt")

0.4.0 by Bob Rudis, a year ago


https://github.com/hrbrmstr/ggalt


Report a bug at https://github.com/hrbrmstr/ggalt/issues


Browse source code at https://github.com/cran/ggalt


Authors: Bob Rudis [aut, cre], Ben Bolker [aut, ctb] (Encircling & additional splines), Ben Marwick [ctb] (General codebase cleanup), Jan Schulz [aut, ctb] (Annotations), Rosen Matev [ctb] (Original annotate_textp implementation on stackoverflow), ProPublica [dtc] (StateFace font)


Documentation:   PDF Manual  


AGPL + file LICENSE license


Imports utils, graphics, grDevices, dplyr, RColorBrewer, KernSmooth, proj4, scales, grid, gtable, ash, maps, MASS, extrafont, tibble, plotly

Depends on ggplot2

Suggests testthat, gridExtra, knitr, rmarkdown, ggthemes, reshape2


Imported by ArchaeoPhases.

Suggested by evaluator.


See at CRAN