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R可视化05|ggplot2图层-注释图层（Annotation layer）
"pythonic生物人"的第103篇分享
本文介绍ggplt2如何给图形添加注释图层（Annotation layer）。
建议：左右上下对照来阅读，查看修改带来的变动。
续前篇：
目录
1、添加文本（Text labels）
2、 添加注释（Building custom annotations）
3、分面图中添加注释（Annotation across facets）
1、添加文本（Text labels）
geom_text()添加文本及其在图中的横纵坐标，可修改文本字体（family）、磅值（fontface）、水平位置hjust (“left”, “center”, “right”, “inward”, “outward”)、垂直位置vjust (“bottom”, “middle”, “top”, “inward”, “outward”)、大小（size）、倾斜度（angle）、文字距原坐标点的距离（nudge）、防文本重叠（check_overlap）；防文本重叠（ggrepel::geom_text_repel）
options(repr.plot.width = 8, repr.plot.height = 10, repr.plot.res = 300)
df <- data.frame(x = 1, y = 3:1, family = c("sans", "serif", "mono"))
#文本字体family aesthetic
p1 <- ggplot(df, aes(x, y)) +
geom_text(aes(label = family, family = family))
#文本磅值（fontface）
df <- data.frame(x = 1, y = 3:1, face = c("plain", "bold", "italic"))
p2 <- ggplot(df, aes(x, y)) +
geom_text(aes(label = face, fontface = face))
#文本水平位置hjust (“left”, “center”, “right”, “inward”, “outward”)、
#垂直位置vjust (“bottom”, “middle”, “top”, “inward”, “outward”)
df <- data.frame(
x = c(1, 1, 2, 2, 1.5),
y = c(1, 2, 1, 2, 1.5),
text = c(
"bottom-left", "bottom-right",
"top-left", "top-right", "center"
)
)
p3 <- ggplot(df, aes(x, y)) +
geom_text(aes(label = text))
p4 <- ggplot(df, aes(x, y)) +
geom_text(aes(label = text), vjust = "inward", hjust = "inward")#设置水平垂直位置
#文字距原坐标点的距离（nudge）
df <- data.frame(trt = c("a", "b", "c"), resp = c(1.2, 3.4, 2.5))
p5 <- ggplot(df, aes(resp, trt)) +
geom_point() +
geom_text(aes(label = paste0("(", resp, ")")), nudge_y = -0.25) +
xlim(1, 3.6)
#防文本重叠（check_overlap）
p6 <- ggplot(mpg, aes(displ, hwy)) +
geom_text(aes(label = model)) +
xlim(1, 8)
p7 <- ggplot(mpg, aes(displ, hwy)) +
geom_text(aes(label = model), check_overlap = TRUE) +
xlim(1, 8)
#防文本重叠（ggrepel::geom_text_repel）
library('ggrepel')
mini_mpg <- mpg[sample(nrow(mpg), 20),]
p8 <- ggplot(mpg, aes(displ, hwy)) + geom_point(colour = "red") +
ggrepel::geom_text_repel(data = mini_mpg, aes(label = class))
#添加文本背景框
label <- data.frame(
waiting = c(55, 80),
eruptions = c(2, 4.3),
label = c("peak one", "peak two")
)
p9 <- ggplot(faithfuld, aes(waiting, eruptions)) +
geom_tile(aes(fill = density)) +
geom_label(data = label, aes(label = label))
p10 <- grid.arrange(p1,p2,p3,p4,p5,p6,p7,p8,p9,nrow = 5)
ggsave("plot1.png", p10, width = 8, height = 5)
2、 添加注释（Building custom annotations）
ggplot2 package provides several other tools to annotate plots using the same geoms you would use to display data.
geom_text()、geom_label()添加文本 text, 见part1。geom_rect()：用一个矩形圈出感兴趣的区域，指定xmin，xmax，ymin，ymax。geom_line()、geom_path()、``geom_segment()：在图形中添加线条、arrow()可以用来添加箭头，可指定a``ngle,length,endsandtype。geom_vline()、geom_hline()、geom_abline()：添加垂直线、水平线、添加任意斜率和截距地直线。directlabels::geom_dl：directlabels直接加标签。 ggforce::geom_mark_ellipse：ggforce突出某部分。 gghighlight::gghighlight：gghighlight突出某部分。 annotate：annotate添加文本。
以实例介绍各函数的使用
options(repr.plot.width = 8, repr.plot.height = 13, repr.plot.res = 300)
#添加折线geom_line()
p1 <- ggplot(economics, aes(date, unemploy)) +
geom_line()
#添加矩形区域线geom_rect()，指定xmin，xmax，ymin，ymax
presidential <- subset(presidential, start > economics$date[1])
p2 <- ggplot(economics) +
geom_rect(
aes(xmin = start, xmax = end, fill = party),
ymin = -Inf, ymax = Inf, alpha = 0.2,
data = presidential
) +
geom_vline(#添加垂直线geom_vline()
aes(xintercept = as.numeric(start)),
data = presidential,
colour = "grey50", alpha = 0.5
) +
geom_text(#添加文本geom_text()
aes(x = start, y = 2500, label = name),
data = presidential,
size = 3, vjust = 0, hjust = 0, nudge_x = 50
) +
geom_line(aes(date, unemploy)) +
scale_fill_manual(values = c("blue", "red")) +
xlab("date") +
ylab("unemployment")
#geom_text左上侧添加文本方法一【略显复杂】
yrng <- range(economics$unemploy)
xrng <- range(economics$date)
caption <- paste(strwrap("Unemployment rates in the US have
varied a lot over the years", 40), collapse = "\n")
p3 <- ggplot(economics, aes(date, unemploy)) +
geom_line() +
geom_text(
aes(x, y, label = caption),
data = data.frame(x = xrng[1], y = yrng[2], caption = caption),
hjust = 0, vjust = 1, size = 4
)
#annotate左上侧添加文本方法二【推荐】
p4 <- ggplot(economics, aes(date, unemploy)) +
geom_line() +
annotate(
geom = "text", x = xrng[1], y = yrng[2],
label = caption, hjust = 0, vjust = 1, size = 4
)
##给某一类点上色
library('dplyr')
p5 <- ggplot(mpg, aes(displ, hwy)) +
geom_point(data = filter(mpg, manufacturer == "subaru"),
colour = "orange",
size = 3
) +
geom_point()
#右上角添加图例
p6 <- p5 +
annotate(geom = "point", x = 5.5, y = 40, colour = "orange", size = 3) +
annotate(geom = "point", x = 5.5, y = 40) +
annotate(geom = "text", x = 5.6, y = 40, label = "subaru", hjust = "left")
p7 <- p5 +
annotate(#添加箭头
geom = "curve", x = 4, y = 35, xend = 2.65, yend = 27,
curvature = .3, arrow = arrow(length = unit(2, "mm"))
) +
annotate(geom = "text", x = 4.1, y = 35, label = "subaru", hjust = "left")#添加文本
#按class添加颜色
p8 <- ggplot(mpg, aes(displ, hwy, colour = class)) +
geom_point()
#directlabels::geom_dl直接加标签
library("directlabels")
p9 <- ggplot(mpg, aes(displ, hwy, colour = class)) +
geom_point(show.legend = FALSE) +
directlabels::geom_dl(aes(label = class), method = "smart.grid")
#ggforce扩展包突出某部分
library('ggforce')
p9 <- ggplot(mpg, aes(displ, hwy)) +
geom_point() +
ggforce::geom_mark_ellipse(aes(label = cyl, group = cyl))
#gghighlight扩展包突出某部分
library('gghighlight')
data(Oxboys, package = "nlme")
p10 <- ggplot(Oxboys, aes(age, height, group = Subject)) +
geom_line() +
geom_point() +
gghighlight::gghighlight(Subject %in% 1:3)
grid.arrange(p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,nrow = 5)
3、分面图中添加注释（Annotation across facets）
直接看代码。
options(repr.plot.width = 5, repr.plot.height = 7, repr.plot.res = 300)
p1 <- ggplot(diamonds, aes(log10(carat), log10(price))) +
geom_bin2d() +
facet_wrap(vars(cut), nrow = 1)
#分面图添加参考线
mod_coef <- coef(lm(log10(price) ~ log10(carat), data = diamonds))
p2 <- ggplot(diamonds, aes(log10(carat), log10(price))) +
geom_bin2d() +
geom_abline(intercept = mod_coef[1], slope = mod_coef[2],
colour = "white", size = 1) +
facet_wrap(vars(cut), nrow = 1)
#gghighlight::gghighlight高亮某类
p3 <- ggplot(mpg, aes(displ, hwy, colour = factor(cyl))) +
geom_point() +
gghighlight::gghighlight() +
facet_wrap(vars(cyl))
grid.arrange(p1,p2,p3,nrow = 3)
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