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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: Likecoord_map, only better 😜
-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 (usesKernSmooth::bkde) –geom_stateface: Use ProPublica’s StateFace font in ggplot2 plots-stat_bkde: Display a smooth density estimate (usesKernSmooth::bkde)
-geom_bkde2d: Contours from a 2d density estimate. (usesKernSmooth::bkde2D)
-stat_bkde2d: Contours from a 2d density estimate. (usesKernSmooth::bkde2D)
-stat_ash: Compute and display a univariate averaged shifted histogram (polynomial kernel) (usesash::ash1/ash::bin1) –geom_encircle: Automatically enclose points in a polygonscale_color_pokemon:
-scale_fill_pokemon: discrete pokemon scales (data taken from the hard work by the http://www.pokegraphs.com/)
-byte_format: + helpers. e.g. turn10000into10 Kb
-geom_lollipop(): Dead easy lollipops (horizontal or vertical)
-geom_dumbberll(): Dead easy dumbbell plots
-
-
-Installation
-# 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] '0.3.0.9000'
-
-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)
-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)
-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)
-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)
-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)
-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)
-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)
-
-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")
-#>
-#> # ATTENTION: maps v3.0 has an updated 'world' map. #
-#> # Many country borders and names have changed since 1990. #
-#> # Type '?world' or 'news(package="maps")'. See README_v3. #
-world <- world[world$region != "Antarctica",]
-
-gg <- ggplot()
-gg <- gg + geom_map(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")
-
-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=3, 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=-5, 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)
-#>
-#> Attaching package: 'dplyr'
-#> The following objects are masked from 'package:stats':
-#>
-#> filter, lag
-#> The following objects are masked from 'package:base':
-#>
-#> intersect, setdiff, setequal, union
-library(tidyr)
-library(scales)
-library(ggplot2)
-library(ggalt) # devtools::install_github("hrbrmstr/ggalt")
-
-health <- read.csv("https://gist.githubusercontent.com/hrbrmstr/0d206070cea01bcb0118/raw/0ea32190a8b2f54b5a9770cb6582007132571c98/zhealth.csv", stringsAsFactors=FALSE,
- header=FALSE, col.names=c("pct", "area_id"))
-
-areas <- read.csv("https://gist.githubusercontent.com/hrbrmstr/0d206070cea01bcb0118/raw/0ea32190a8b2f54b5a9770cb6582007132571c98/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_2013, xend=pct_2014, y=area_name, group=area_name))
-gg <- gg + geom_dumbbell(color="#a3c4dc", size=0.75, point.colour.l="#0e668b")
-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
-
-
-
-
-
-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.
-
-```r
+``` r
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
geom_point() +
@@ -80,7 +67,7 @@ ggplot(dat, aes(x, y, group=group, color=factor(group))) +
-```r
+``` r
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
geom_point(color="black") +
@@ -90,7 +77,7 @@ ggplot(dat, aes(x, y, group=group, color=factor(group))) +
-```r
+``` r
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
geom_point(color="black") +
@@ -100,7 +87,7 @@ ggplot(dat, aes(x, y, group=group, color=factor(group))) +
-```r
+``` r
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
geom_point(color="black") +
@@ -110,7 +97,7 @@ ggplot(dat, aes(x, y, group=group, color=factor(group))) +
-```r
+``` r
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
geom_point(color="black") +
@@ -120,7 +107,7 @@ ggplot(dat, aes(x, y, group=group, color=factor(group))) +
-```r
+``` r
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
geom_point(color="black") +
@@ -130,7 +117,7 @@ ggplot(dat, aes(x, y, group=group, color=factor(group))) +
-```r
+``` r
ggplot(dat, aes(x, y, group=group, color=factor(group))) +
geom_point(color="black") +
@@ -142,8 +129,7 @@ ggplot(dat, aes(x, y, group=group, color=factor(group))) +
#### Alternate (better) density plots
-
-```r
+``` r
# bkde
data(geyser, package="MASS")
@@ -155,7 +141,7 @@ ggplot(geyser, aes(x=duration)) +
-```r
+``` r
ggplot(geyser, aes(x=duration)) +
geom_bkde(alpha=1/2)
@@ -164,7 +150,7 @@ ggplot(geyser, aes(x=duration)) +
-```r
+``` r
ggplot(geyser, aes(x=duration)) +
stat_bkde(bandwidth=0.25)
@@ -172,7 +158,7 @@ ggplot(geyser, aes(x=duration)) +
-```r
+``` r
ggplot(geyser, aes(x=duration)) +
geom_bkde(bandwidth=0.25)
@@ -180,7 +166,7 @@ ggplot(geyser, aes(x=duration)) +
-```r
+``` r
set.seed(1492)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)),
@@ -193,7 +179,7 @@ ggplot(dat, aes(x=rating, color=cond)) + geom_bkde(fill="#00000000")
-```r
+``` r
ggplot(dat, aes(x=rating, fill=cond)) + geom_bkde(alpha=0.3)
#> Bandwidth not specified. Using '0.36', via KernSmooth::dpik.
@@ -202,7 +188,7 @@ ggplot(dat, aes(x=rating, fill=cond)) + geom_bkde(alpha=0.3)
-```r
+``` r
# ash
@@ -218,7 +204,7 @@ grid.arrange(ggplot(dat, aes(x)) + stat_ash(),
-```r
+``` r
cols <- RColorBrewer::brewer.pal(3, "Dark2")
ggplot(dat, aes(x)) +
@@ -239,8 +225,7 @@ ggplot(dat, aes(x)) +
### Alternate 2D density plots
-
-```r
+``` r
m <- ggplot(faithful, aes(x = eruptions, y = waiting)) +
geom_point() +
xlim(0.5, 6) +
@@ -251,7 +236,7 @@ m + geom_bkde2d(bandwidth=c(0.5, 4))
-```r
+``` r
m + stat_bkde2d(bandwidth=c(0.5, 4), aes(fill = ..level..), geom = "polygon")
```
@@ -260,8 +245,7 @@ m + stat_bkde2d(bandwidth=c(0.5, 4), aes(fill = ..level..), geom = "polygon")
### `coord_proj` LIVES! (still needs a teensy bit of work)
-
-```r
+``` r
world <- map_data("world")
#>
#> # ATTENTION: maps v3.0 has an updated 'world' map. #
@@ -280,8 +264,7 @@ gg
### ProPublica StateFace
-
-```r
+``` r
# Run show_stateface() to see the location of the TTF StateFace font
# You need to install it for it to work
@@ -303,8 +286,7 @@ gg
### Encircling points automagically
-
-```r
+``` r
d <- data.frame(x=c(1,1,2),y=c(1,2,2)*100)
gg <- ggplot(d,aes(x,y))
@@ -316,21 +298,21 @@ gg + geom_encircle(s_shape=1, expand=0) + geom_point()
-```r
+``` r
gg + geom_encircle(s_shape=1, expand=0.1, colour="red") + geom_point()
```
-```r
+``` r
gg + geom_encircle(s_shape=0.5, expand=0.1, colour="purple") + geom_point()
```
-```r
+``` r
gg + geom_encircle(data=subset(d, x==1), colour="blue", spread=0.02) +
geom_point()
@@ -338,7 +320,7 @@ gg + geom_encircle(data=subset(d, x==1), colour="blue", spread=0.02) +
-```r
+``` r
gg +geom_encircle(data=subset(d, x==2), colour="cyan", spread=0.04) +
geom_point()
@@ -346,7 +328,7 @@ gg +geom_encircle(data=subset(d, x==2), colour="cyan", spread=0.04) +
-```r
+``` r
gg <- ggplot(mpg, aes(displ, hwy))
gg + geom_encircle(data=subset(mpg, hwy>40)) + geom_point()
@@ -354,7 +336,7 @@ gg + geom_encircle(data=subset(mpg, hwy>40)) + geom_point()
-```r
+``` r
ss <- subset(mpg,hwy>31 & displ<2)
@@ -366,8 +348,7 @@ gg + geom_encircle(data=ss, colour="blue", s_shape=0.9, expand=0.07) +
### Lollipop charts
-
-```r
+``` r
df <- read.csv(text="category,pct
Other,0.09
South Asian/South Asian Americans,0.12
@@ -417,17 +398,8 @@ gg
-
-```r
+``` r
library(dplyr)
-#>
-#> Attaching package: 'dplyr'
-#> The following objects are masked from 'package:stats':
-#>
-#> filter, lag
-#> The following objects are masked from 'package:base':
-#>
-#> intersect, setdiff, setequal, union
library(tidyr)
library(scales)
library(ggplot2)
@@ -470,5 +442,4 @@ gg
### Code of Conduct
-Please note that this project is released with a [Contributor Code of Conduct](CONDUCT.md).
-By participating in this project you agree to abide by its terms.
+Please note that this project is released with a [Contributor Code of Conduct](CONDUCT.md). By participating in this project you agree to abide by its terms.