如何用不同颜色的geom_errorbar绘制ggplot？

Adrian 发表于 Dev

阿德里安

library(tidyverse)
mydata <- structure(list(Index = c(1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 
2L, 3L, 3L), Gender = c("Male", "Female", "Male", "Female", "Male", 
"Female", "Male", "Female", "Male", "Female", "Male", "Female"
), Height = c(NA, NA, 0.740339097715042, 0.758196660530606, 0.218048382364689, 
0.329217343894418, NA, NA, 0.749669793529369, 0.7445564572896, 
0.273171513372133, 0.452720902980308), Lo = c(NA, NA, 0.729682349457229, 
0.739120997850057, 0.20316516805848, 0.311224922583981, NA, NA, 
0.718886931624498, 0.708069014803844, 0.233670719484927, 0.402244911750405
), Up = c(NA, NA, 0.755735601081241, 0.778557403161694, 0.237068004398738, 
0.349859894992744, NA, NA, 0.786845227603324, 0.786837817718618, 
0.314042083915779, 0.499544458312984), Score = c(0.075, 0.075, 
0.075, 0.075, 0.075, 0.075, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3)), row.names = c(NA, 
-12L), class = c("tbl_df", "tbl", "data.frame"))


> mydata
# A tibble: 12 × 6
   Index Gender Height     Lo     Up Score
   <int> <chr>   <dbl>  <dbl>  <dbl> <dbl>
 1     1 Male   NA     NA     NA     0.075
 2     1 Female NA     NA     NA     0.075
 3     2 Male    0.740  0.730  0.756 0.075
 4     2 Female  0.758  0.739  0.779 0.075
 5     3 Male    0.218  0.203  0.237 0.075
 6     3 Female  0.329  0.311  0.350 0.075
 7     1 Male   NA     NA     NA     0.3  
 8     1 Female NA     NA     NA     0.3  
 9     2 Male    0.750  0.719  0.787 0.3  
10     2 Female  0.745  0.708  0.787 0.3  
11     3 Male    0.273  0.234  0.314 0.3  
12     3 Female  0.453  0.402  0.500 0.3

我有一个包含男女学生身高数据的数据集。这些学生被分成两组Score。在的每个级别内Score，有 3 个Indexes。

dplyr::rename(mydata, Gender = "Gender") %>%  ggplot(aes(x = Index, y = Height, color = Gender, ymin = Lo, ymax = Up)) +
  geom_errorbar(position = position_dodge(width = 0.2),  width = 0.2) +
  geom_point(position = position_dodge(width = 0.2), size = 0.8)

我可以看到雄性是绿色的，雌性是红色的。但是，如何区分两个不同Scores的误差线？我怎样才能给它们上不同的颜色？

哈顿cp

您可以通过使用 tidyr::unite() 将性别和分数变量组合到一个列中，然后将新的组合变量分配给颜色美学来实现这一点。

    tibble(Index = c(1L, 1L, 2L, 2L, 3L, 3L, 
                 1L, 1L, 2L, 2L, 3L, 3L), 
       Gender = c("Male", "Female", "Male", "Female", "Male", 
                  "Female", "Male", "Female", "Male", "Female", "Male", "Female"), 
       Height = c(NA, NA, 0.740339097715042, 0.758196660530606, 0.218048382364689, 
                  0.329217343894418, NA, NA, 0.749669793529369, 0.7445564572896, 
                  0.273171513372133, 0.452720902980308), 
       Lo = c(NA, NA, 0.729682349457229, 
              0.739120997850057, 0.20316516805848, 0.311224922583981, NA, NA, 
              0.718886931624498, 0.708069014803844, 0.233670719484927, 0.402244911750405), 
       Up = c(NA, NA, 0.755735601081241, 0.778557403161694, 0.237068004398738, 
              0.349859894992744, NA, NA, 0.786845227603324, 0.786837817718618, 
              0.314042083915779, 0.499544458312984), 
       Score = c(0.075, 0.075,  0.075, 0.075, 0.075, 0.075, 
                 0.3, 0.3, 0.3, 0.3, 0.3, 0.3)) %>% 
  tidyr::unite(Gender, Score, col = "group") %>% 
  ggplot(aes(x = Index, y = Height, color = group, ymin = Lo, ymax = Up)) +
  geom_errorbar(position = position_dodge(width = 0.2),  width = 0.2) +
  geom_point(position = position_dodge(width = 0.2), size = 0.8)