ggalt examples

Bob Rudis

2017-02-14

library(ggplot2)
library(gridExtra)
library(ggalt)
library(scales)

# 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]) +