如何为ggplot2中的图形数据子集创建回归线？

Question

我有一个不同属的测量数据集。其中一些属有多个数据点，其他属只有一个。我编写了以下代码来生成包含Measurement_A 和Measurement_B 的measurements 表的散点图。

# Load ggplot2 and ggpmisc
library(ggplot2)
library(ggpmisc)
measurements <- read.csv("measurements.csv")
# Define colours and shapes for each genus (which I've called A, B, C and D)
colour_specifications <- c("A"="green", "B"="red", "C"="yellow",  "D"="blue")
shape_specifications <- c("A"=15, "B"=16, "C"=17, "D"=18)

# Create scatterplot of data from each genus
# and plot a regression line for each genus and show the R^2 value for each line
scatterplot <- ggplot(measurements, aes(x=Measurement_A, y=Measurement_B,     
colour=Genus, shape=Genus))+
+   geom_point()+theme_classic()+
+   scale_color_manual(values = colour_specifications)+
+   scale_shape_manual(values= shape_specifications)+
+   geom_smooth(method=lm, se=FALSE)+
+   stat_poly_eq(formula = y ~ x, eq.with.lhs=FALSE, parse = TRUE)
> scatterplot

尽管属 C 和 D 只有一个数据点，但图例显示了回归线和符号。我想找到一种方法来为那些具有多个数据点的属子集（属 A 和 B）绘制回归线。我试过subset函数如下，

scatterplot <- ggplot(measurements, aes(x=Measurement_A, y=Measurement_B,
    colour=Genus, shape=Genus))+
  geom_point()+theme_classic()+
  scale_color_manual(values = colour_specifications)+
  scale_shape_manual(values= shape_specifications)+
  geom_smooth(data=subset(measurements, Genus="A"),
          method='lm', se=FALSE)+
  geom_smooth(method=lm, se=FALSE)+
  stat_poly_eq(formula = y ~ x, eq.with.lhs=FALSE, parse = TRUE)

但这对传说没有任何影响，这让我觉得我做错了什么。

有没有办法只为 A 属和 B 属而不是 C 和 D 属绘制回归线？

预计到达时间：

这是我为此使用的数据：

Genus <- c("A", "A", "A", "A", "A", "A", "A", "A", "B", "B", "B", "B", "C",     "D") 
Specimen <- c("Aa","Ab","Ac","Ad","Ae","Af","Ag","Ah","Ba", "Bb", "Bc", "Bd", "Ca", "Da") 
Measurement_A <- c(60, 80, 100, 105, 120, 130, 140, 95, 70, 80, 90, 100, 170, 55) 
Measurement_B <- c(10, 15, 30, 30, 35, 40, 40, 27, 10, 17, 20, 27, 15, 5)             
measurements <- data.frame(Genus, Specimen, Measurement_A, Measurement_B)

我想要做的就是用一个图例创建一个我的数据图，但 A 和 B 类显示回归线和 R^2 值。上面的两组代码都给了我一个图例，其中包含所有符号的回归线，而不仅仅是 A 和 B。正如我上面解释的，我尝试了 subset 函数，但它不会改变图例。当我尝试时

scatterplot <- ggplot(measurements, aes(x=Measurement_A, y=Measurement_B,     
                                        colour=Genus, shape=Genus))+
geom_point()+theme_classic()+
scale_color_manual(values = colour_specifications)+
scale_shape_manual(values= shape_specifications)+
geom_smooth(method=lm, se=FALSE)+
scale_color_manual(values = c("green","red"),limits = c("A","B"))+
stat_poly_eq(formula = y ~ x, eq.with.lhs=FALSE, parse = TRUE)
scatterplot

我收到一条错误消息说"Scale for 'colour' is already present. Adding another scale for 'colour', which will replace the existing scale"，然后我得到两个图例，一个带有预设符号，但所有属均为黑色，另一个带有颜色，但只是 A 属和 B 属的圆形符号。

预计到达时间： 我找到了答案，我只需要在geom_smooth括号中添加show.legend=FALSE即可。

Answer 1

为什么不直接通过subset 指定两个因子水平？

scatterplot <- ggplot(measurements, aes(x=Measurement_A, y=Measurement_B,
colour=Genus, shape=Genus)) 
+ geom_point() 
+ geom_smooth(data=subset(measurements, Genus== "A" | Genus == "B"), method='lm', se=FALSE)