从图例中删除特定标记

Question

很抱歉，如果这个问题已经得到解答，但我找不到我所追求的解决方案。我有一个同时使用 geom_line 和 geom_point 的绘图。这样做的结果是，在图例中，当它们应该有一个或另一个时，它却同时添加了一条线和一个点。我想保留数据 tg1 和 tg2 的圆圈并删除该行，然后执行与数据 full 相反的操作，即保留线但删除圆圈。我已经看到类似的方法可以在您想要从所有图例条目中删除点但只执行特定 Removing ggplot2's geom_point icons from the legend 的情况下起作用。有人可以帮忙吗？谢谢。

#绘图代码

library(ggplot2)
library(tidypaleo)

ggplot(LGRSL, aes(x =mmsl , y = Age))+
  coord_flip()+
  theme_classic(12)+
  geom_point(data=tg1,aes(x=mmslc,y=Year,col="Fort Denison 1"),pch=1,size=2)+
  geom_point(data=tg2,aes(x=mmslc,y=Year,col="Fort Denison 2"),pch=1,size=2)+
  geom_lineh(data = full, aes(x=Lutregalammslc,y=Year,col="Full budget"))+
  scale_colour_manual(values=c("grey15","grey50","black"))
  

## data

## tg1

structure(list(Year = 1886:1891, SLR = c(6919L, 6935L, 6923L, 
6955L, 6956L, 6957L), mmsl = c(-0.158, -0.142, -0.154, -0.122, 
-0.121, -0.12), m = c(6.919, 6.935, 6.923, 6.955, 6.956, 6.957
), GIA.correction = c(-0.02814, -0.02793, -0.02772, -0.02751, 
-0.0273, -0.02709), SLRc = c(6.89086, 6.90707, 6.89528, 6.92749, 
6.9287, 6.92991), mmslc = c(-0.19667, -0.18046, -0.19225, -0.16004, 
-0.15883, -0.15762)), row.names = c(NA, 6L), class = "data.frame")

##tg2

structure(list(Year = 1915:1920, SLR = c(7011L, 6929L, 6987L, 
6945L, 6959L, 6951L), mmsl = c(-0.066, -0.148, -0.09, -0.132, 
-0.118, -0.126), m = c(7.011, 6.929, 6.987, 6.945, 6.959, 6.951
), GIA.correction = c(-0.02205, -0.02184, -0.02163, -0.02142, 
-0.02121, -0.021), SLRc = c(6.98895, 6.90716, 6.96537, 6.92358, 
6.93779, 6.93), mmslc = c(-0.09858, -0.18037, -0.12216, -0.16395, 
-0.14974, -0.15753)), row.names = c(NA, 6L), class = "data.frame")

##full

structure(list(Year = 1900:1905, Lutregala = c(-0.103609677, 
-0.118603251, -0.134550791, -0.105553735, -0.103983082, -0.121731984
), Wapengo = c(-0.095213147, -0.096005337, -0.115700625, -0.097696891, 
-0.084444784, -0.109161066), Tarra = c(-0.106672829, -0.109537943, 
-0.135256365, -0.101357772, -0.089716518, -0.104258351), Lutregalammsl = c(-0.292863465, 
-0.307857039, -0.323804579, -0.294807523, -0.29323687, -0.310985772
), Wapengommsl = c(-0.257028279, -0.257820469, -0.277515756, 
-0.259512023, -0.246259916, -0.270976198), Tarrammsl = c(-0.30925682, 
-0.312121933, -0.337840355, -0.303941762, -0.292300508, -0.306842342
), LgGIAc = c(-0.01921, -0.01904, -0.01887, -0.0187, -0.01853, 
-0.01836), WapGIAc = c(-0.02486, -0.02464, -0.02442, -0.0242, 
-0.02398, -0.02376), TarGIAc = c(-0.02373, -0.02352, -0.02331, 
-0.0231, -0.02289, -0.02268), Lutregalammslc = c(-0.312073465, 
-0.326897039, -0.342674579, -0.313507523, -0.31176687, -0.329345772
), Wapmmslc = c(-0.281888279, -0.282460469, -0.301935756, -0.283712023, 
-0.270239916, -0.294736198), Tarmmslc = c(-0.33298682, -0.335641933, 
-0.361150355, -0.327041762, -0.315190508, -0.329522342)), row.names = c(NA, 
6L), class = "data.frame")

##LGRSL

structure(list(depths = c(0.5, 1.5, 2.5, 3.5, 4.5, 5.5), RSL = c(0.047746907, 
0.025564293, 0.021733558, 0.007855661, -0.004909879, 0.01747051
), RSLerror = c(0.058158556, 0.057902654, 0.057988654, 0.057957388, 
0.057905405, 0.057226072), Age = c(2017.456716, 2013.594255, 
2006.92838, 1999.675523, 1994.729181, 1990.518154), Ageerror = c(0.373138707, 
0.77640096, 1.430582242, 1.627131115, 3.222393394, 3.239674718
), mmsl = c(0.01993169, -0.002250924, -0.006081659, -0.019959556, 
-0.032725096, -0.010344707)), row.names = c(NA, 6L), class = "data.frame")

##LGRSLgp

structure(list(Age = 1892:1897, mean = c(-0.298147401, -0.304630597, 
-0.31023294, -0.315506983, -0.321225142, -0.327190675), error = c(0.051858047, 
0.04985084, 0.047760525, 0.045624121, 0.043505044, 0.041477551
), min = c(-0.246289354, -0.254779758, -0.262472416, -0.269882862, 
-0.277720098, -0.285713124), max = c(-0.350005447, -0.354481437, 
-0.357993465, -0.361131103, -0.364730186, -0.368668226), x = c(-0.02125, 
-0.02108, -0.02091, -0.02074, -0.02057, -0.0204), meangia = c(-0.276897401, 
-0.283550597, -0.28932294, -0.294766983, -0.300655142, -0.306790675
), rate = c(NA, -4.967327, -4.946326, -4.964493, -4.977451, -4.911859
), raterror = c(NA, 3.581013, 3.796417, 4.022157, 4.226762, 4.255126
), mmsl = c(-0.325962618, -0.332445814, -0.338048157, -0.3433222, 
-0.349040359, -0.355005892)), row.names = c(NA, 6L), class = "data.frame")

Answer 1

这是一个方法。
使用涉及每个美学的值向量列表覆盖指南图例，形状和线型。请注意指定要删除的内容的不同方法。

我还稍微简化了代码。

library(ggplot2)
library(dplyr)

colrs <- c("Fort Denison 1" = "grey15",
           "Fort Denison 2" = "grey50",
           "Full budget" = "black")
legnd <- list(shape = c(1, 1, NA), 
              linetype = c("blank", "blank", "solid"))

bind_rows(
  tg1 %>% mutate(col = "Fort Denison 1"),
  tg2 %>% mutate(col = "Fort Denison 2")
) %>%
ggplot(aes(x = mmslc, y = Year, colour = col)) +
  geom_point(pch = 1, size = 2) +
  geom_lineh(data = full, aes(x = Lutregalammslc, col = "Full budget"))+
  scale_colour_manual(values = colrs, 
                      guide = guide_legend(override.aes = legnd)) +
  coord_flip() +
  theme_classic(base_size = 12)