需求描述

上次内容讲述了在做好的图层中添加特定的阴影区，来显示着重突出的部分。本次内容学习一下在图层中添加特定斜率的直线并在图例中显示，我们知道添加特定斜率的直线一般分为水平线geom_hline，垂直线geom_vline和特定斜率的直线geom_abline，添加对应的图例诸如scale_shape_manual，scale_linetype_manual,scale_color_manual,...

1. 数据导入

本次内容以数据集mtcars为例，来演示图形绘制。

rm(list = ls(all=TRUE))#清除所有变量内存
library(ggplot2)#load packages
data(mtcars)
head(mtcars)
> head(mtcars)
                   mpg cyl disp  hp drat    wt  qsec vs am gear carb
Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

2. 图形绘制(散点图)

#设置斜率直线属性
df_abline <- data.frame(intercept=c(.2,1.05,2),slope=c(3, 1.5,.7),linetype=factor(c(1,3,5)))
#作图
p <- ggplot(data=mtcars, aes(x=wt, y=drat)) + 
  geom_point(aes(shape = factor(cyl),color = factor(cyl))) +#赋值给颜色或性状属性(分组因子变量)
  geom_abline(data=df_abline, aes(intercept=intercept,slope=slope, linetype=linetype)) +
  labs(color="",linetype="") +
  scale_shape_manual(name = "",
                     values=c(1,2,4),
                     labels=c("4","6","8")) +
  scale_linetype_manual(name = "",
                        values=c(1,3,2),
                        labels=c("a","b","c"))
p

geom_abline

2.1 添加水平或者垂直线

df_hline <- data.frame(yintercept=c(3,3.5,4),linetype=factor(c(1,3,5)))
#df_vline <- data.frame(xintercept=c(2,3.5,5),linetype=factor(c(1,3,5)))
p1 <- ggplot(data=mtcars, aes(x=wt, y=drat)) + 
  geom_point(aes(shape = factor(cyl),color = factor(cyl))) +
  geom_hline(data = df_hline, aes(yintercept = intercept, linetype = linetype)) +
  labs(color="",linetype="") +

  scale_shape_manual(name = "",
                     values=c(1,2,4),
                     labels=c("4","6","8")) +
  scale_linetype_manual(name = "",
                        values=c(1,3,2),
                        labels=c("a","b","c"))
p1

Rplot_hline
Rplot_vline

3. 散点图+趋势线

df_abline <- data.frame(intercept=c(.2,1.05,2),slope=c(3, 1.5,.7),linetype=factor(c(1,3,5)))

p2 <- ggplot(data=mtcars, aes(x=wt, y=drat)) + 
  geom_point(aes(shape = factor(cyl),color = factor(cyl))) +
  stat_smooth(aes(linetype="regression"),method = "lm",
              formula = y ~ x, se = TRUE, colour = 1, size = 0.5) +
  geom_abline(data = df_abline, aes(intercept = intercept,slope = slope, linetype = linetype)) +
  labs(color="",linetype="") +

  scale_shape_manual(name = "",
                     values=c(1,2,4),
                     labels=c("4","6","8")) +
  scale_linetype_manual(name = "",
                        values=c(1,3,2,4),
                        labels=c("a","b","c","regression"))
p2

Rplot_gression
可以看出当加入趋势线后，legend发生了一些变化

4. 条形图

(a) 将vline添加到现有绘图并使其出现在ggplot2图例中？
(b) 将一条线添加到ggplot2图并调整图例
(c) How to make geom_abline show_guide line types show up in legend correctly

set.seed(20200505)
df <- data.frame(val=rnorm(300, 75, 10))
cuts1 <- data.frame(Thresholds="Thresholds A", vals=c(43, 70, 90)) 
cuts2 <- data.frame(Thresholds="Thresholds B", vals=c(46, 79, 86)) 
cuts <- rbind(cuts1,cuts2) 

p3 <- ggplot(data=df, aes(x=val)) + 
  geom_histogram() + 
  geom_vline(data=cuts, 
             aes(xintercept=vals, 
                 linetype=Thresholds, 
                 colour = Thresholds), 
             show.legend = TRUE)
p3

Rplot_barplot
Rplot02_hline
Rplot02_xyz

后记

全是图，和移栽的代码是为总结记录

PS

2020/05/05 22:40
于疫情劳动节假期