如何在R中的ggplot中為geom_point手動添加圖例？-兩個秤具有相同的美感

我正在嘗試將圖例添加到幾個 geom_point。雖然，因為我有三個 geom_points 標簽只出現一個變數（“結果”）。

除了“結果”變數之外，我還想顯示兩個菱形的標簽：藍色菱形（“TStartTime”）和綠色（“指標”）。

# Code for numbers reproduction
df <- data.frame(subjectID = factor(1:10, 10:1),
                   stage = rep(c("treated"), times = c(10)),
                   endTime = c(6, 8, 3, 5, 10, 14, 2, 12, 6, 6),
                   Outcome = rep(c("healthy", "disability", "healthy", "disability", NA, NA, NA, NA, "healthy", "disability"), 1),
                   TStartTime=c(1.0, 1.5, 0.3, 0.9, NA, NA, NA, NA, NA, NA),
                   TEndTime=c(6.0, 7.0, 1.2, 1.4, NA, NA, NA, NA, NA, NA),
                   TimeZero=c(0,0,0,0,0,0,0,0,0,0),
                   ind=rep(c(!0, !0, !0, !0, !0), times = c(2, 2, 2, 2, 2)),
                   Garea=c(1.0, 1.5, 0.3, 0.9, 2, 2, NA, NA, NA, NA),
                   indicator=c(NA, NA, NA, NA, 4, 1, 5, 2, NA, NA))

# Code for the plot
gg <- ggplot(df, aes(subjectID, endTime))   
  scale_fill_manual(values = c("khaki", "orange"))    
  geom_col(aes(fill = factor(stage)))   
  
  geom_point(data=df, aes(subjectID, TStartTime), colour = c("blue"), fill =alpha(c("#FAFAFA"), 0.2), shape=18, size=4)  
  coord_flip()   # blue diamond
  
  geom_point(data=df, aes(subjectID, indicator), colour = c("green"), shape=18, size=4)  
  coord_flip()   # green diamond for indicator
  
  
  geom_point(aes(colour = Outcome, shape = Outcome),  size = 4)  
  coord_flip()  
  scale_colour_manual(values = c('purple','gray'), na.translate=FALSE)   
  scale_y_continuous(limits = c(-0.2, 15), breaks = 0:15)   
  labs(labels= "",
       x       = "ID ", 
       fill    = "Status",
       y       = "Days",
       title   = "Plot")  
  theme_classic() 
  theme(plot.title   = element_text(hjust = 0.5),
        plot.caption = element_text(size = 7, hjust = 0))

uj5u.com熱心網友回復：

您基本上是在為相同的美學尋找第二個尺度。ggnewscale 是你的朋友。代碼中的許多其他注釋。特別是，您已經多次呼叫 coord_flip，這不是必需的，甚至可能很危險。我會完全避免 coord_flip （請參閱我在代碼中的評論如何做到這一點）。

除了所有這些技術方面 - 你的可視化對我來說似乎并不理想，而且相當混亂。我想知道是否可能沒有更直觀的方式來呈現您的各種變數 - 也許考慮方面。下面給個建議。

library(tidyverse)
library(ggnewscale)

df <- data.frame(
  subjectID = factor(1:10, 10:1),
  stage = rep(c("treated"), times = c(10)),
  endTime = c(6, 8, 3, 5, 10, 14, 2, 12, 6, 6),
  Outcome = rep(c("healthy", "disability", "healthy", "disability", NA, NA, NA, NA, "healthy", "disability"), 1),
  TStartTime = c(1.0, 1.5, 0.3, 0.9, NA, NA, NA, NA, NA, NA),
  TEndTime = c(6.0, 7.0, 1.2, 1.4, NA, NA, NA, NA, NA, NA),
  TimeZero = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
  ind = rep(c(!0, !0, !0, !0, !0), times = c(2, 2, 2, 2, 2)),
  Garea = c(1.0, 1.5, 0.3, 0.9, 2, 2, NA, NA, NA, NA),
  indicator = c(NA, NA, NA, NA, 4, 1, 5, 2, NA, NA)
)

# pivot longer so you can combine tstarttime and indicator into one legend easily
df %>%
  pivot_longer(cols = c(TStartTime, indicator)) %>%
  # remove all the coord_flip calls (you only need one, if not none!)
  ggplot()  
  scale_fill_manual(values = c("khaki", "orange"))  
  # just change the x/y aesthetic in geom_col
  # geom_col would add all values together, so you need to use the un-pivoted data
  geom_col(data = df, mapping = aes(y = subjectID, x = endTime, fill = factor(stage)))  
  # now you only need one geom_point for the new scale, but use the variable in aes()
  geom_point(aes(y = subjectID, x = value, colour = name), shape = 18, size = 4)  
  scale_color_manual(values = c("blue", "green"))  
  # now add a new scale for the same aesthetic (color)
  new_scale_color()  
  geom_point(aes(y = subjectID, x = endTime, colour = Outcome, shape = Outcome), size = 4)  
  ## removing na.translate = FALSE avoids the duplicate legend for outcome
  scale_colour_manual(values = c("purple", "gray"))
#> Warning: Removed 12 rows containing missing values (geom_point).
#> Warning: Removed 8 rows containing missing values (geom_point).

可視化更少的維度/變數有時會更好。這里有一個建議，如何避免雙重比例以獲得相同的美感，并使用你的顏色可能更令人信服。我覺得使用條形可能也不理想，但這實際上取決于變數“indicator/ttimestart”是什么以及它與結束時間的關系。一個好的目標是顯示這兩個變數之間的關系。

df %>%
  pivot_longer(cols = c(TStartTime, indicator)) %>%
  ggplot()  
  ## all of them are treated, so I am using Outcome as fill variable
  # this removes the need for second geom-point and second scale
  geom_col(data = df, mapping = aes(y = subjectID, x = endTime, fill = Outcome))  
  scale_fill_manual(values = c("purple", "gray"))  
  geom_point(aes(y = subjectID, x = value, colour = name), shape = 18, size = 4)  
  scale_color_manual(values = c("blue", "green"))  
## if you have untreated people, show them in a new facet, e.g., add 
  facet_grid(~stage)
#> Warning: Removed 12 rows containing missing values (geom_point).

^{由reprex 包于 2022-05-05 創建(v2.0.1)}

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