如何在R的ggplot2中为折线匹配对应颜色并添加末端标签

数据背景 #

我有一个名为df_的data frame，数据结构如下：

df_
# A tibble: 40 × 4
# Groups:   Year [5]
    Year Country    mu Color 
   <int> <fct>   <dbl> <fct> 
 1  2019 ALPHA    68.9 red   
 2  2019 BETA     64.8 black 
 3  2019 GAMMA    70.0 yellow
 4  2019 RHO      65.2 gray  
 5  2019 DELTA    70.1 green 
 6  2019 EPSILON  69.6 pink  
 7  2019 THETA    69.8 purple
 8  2019 OMEGA    67.9 orange
 9  2020 ALPHA    69.3 red   
10  2020 BETA     65.2 black 
# ℹ 30 more rows

数据结构的完整structure：

structure(list(Year = c(2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 
2019L, 2019L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 
2020L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 
2023L, 2023L, 2023L, 2023L, 2023L, 2023L, 2023L, 2023L, 2024L, 
2024L, 2024L, 2024L, 2024L, 2024L, 2024L, 2024L), Country = structure(c(1L, 
2L, 5L, 7L, 3L, 4L, 8L, 6L, 1L, 2L, 5L, 7L, 3L, 4L, 8L, 6L, 1L, 
2L, 5L, 7L, 3L, 4L, 8L, 6L, 1L, 2L, 5L, 7L, 3L, 4L, 8L, 6L, 1L, 
2L, 5L, 7L, 3L, 4L, 8L, 6L), levels = c("ALPHA", "BETA", "DELTA", 
"EPSILON", "GAMMA", "OMEGA", "RHO", "THETA"), class = "factor"), 
    mu = c(68.855, 64.77, 69.9875, 65.22, 70.1266666666667, 69.6166666666667, 
    69.8085714285714, 67.9093333333333, 69.2675, 65.2, 72.4075, 
    69.49, 72.28, 69.262, 70.07125, 65.3864285714286, 74.6584615384615, 
    67.77, 75.3533333333333, 73, 64.09, 73.1715384615385, 66.058, 
    72.12, 75.5645833333333, 70.46, 78.2933333333333, 79.07, 
    59.82, 79.6361538461538, 74.225, 69.5871428571429, 76.4007407407407, 
    67.91, 76.805, 77.31, 74.0966666666667, 81.2811764705882, 
    74.6671428571428, 78.0316666666667), Color = structure(c(7L, 
    1L, 8L, 2L, 3L, 5L, 6L, 4L, 7L, 1L, 8L, 2L, 3L, 5L, 6L, 4L, 
    7L, 1L, 8L, 2L, 3L, 5L, 6L, 4L, 7L, 1L, 8L, 2L, 3L, 5L, 6L, 
    4L, 7L, 1L, 8L, 2L, 3L, 5L, 6L, 4L), levels = c("black", 
    "gray", "green", "orange", "pink", "purple", "red", "yellow"
    ), class = "factor")), class = c("grouped_df", "tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -40L), groups = structure(list(
    Year = c(2019L, 2020L, 2022L, 2023L, 2024L), .rows = structure(list(
        1:8, 9:16, 17:24, 25:32, 33:40), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -5L), .drop = TRUE))

需求 #

• a) 为每个国家对应的折线应用其Color列指定的颜色；
• b) 在每条折线的末端（2024年的数据点处）显示Country名称和对应mu值，格式如“ALPHA ,76.4”。

现有代码 #

基础绘图代码：

ggplot(df_, aes(x = Year, y = mu, color = Color, group = Country)) +
  geom_line(size = 1.5) +
  geom_point() +
  labs(x = "Years", y = "") +
  theme_minimal() +
  theme(legend.position = "none")  

尝试添加标签的代码：
先给数据框新增列：

mutate(label = if_else(Year == max(Year), as.character(Country), NA_character_))

再在绘图代码中添加：

theme(legend.position = "none") +
geom_label_repel(aes(label = label),
                 nudge_x = 1,
                 na.rm = TRUE)

但这样只能显示国家名称，无法同时显示对应mu值。

解决方案 #

1. 修正标签列的生成逻辑 #

原数据是按Year分组的，直接用max(Year)会取每组的最大值，所以必须先取消分组，再将Country和格式化后的mu值拼接成目标格式：

df_ <- df_ %>%
  ungroup() %>%
  mutate(label = if_else(Year == max(Year),
                         paste0(as.character(Country), ", ", round(mu, 1)),
                         NA_character_))

如果需要保留更多小数位数，调整round()的第二个参数即可。

2. 完整绘图代码 #

将修正后的标签应用到绘图中，确保折线颜色和标签显示符合需求：

library(ggplot2)
library(dplyr)
library(ggrepel)

# 预处理数据生成标签
df_ <- df_ %>%
  ungroup() %>%
  mutate(label = if_else(Year == max(Year),
                         paste0(Country, ", ", round(mu, 1)),
                         NA_character_))

# 绘图
ggplot(df_, aes(x = Year, y = mu, color = Color, group = Country)) +
  geom_line(size = 1.5) +
  geom_point() +
  # 添加带排斥效果的标签，避免重叠
  geom_label_repel(aes(label = label),
                   nudge_x = 1,
                   na.rm = TRUE,
                   fill = "white",
                   size = 3) +
  labs(x = "Years", y = "") +
  theme_minimal() +
  theme(legend.position = "none")

关键说明 #

• 取消分组：ungroup()确保max(Year)获取的是全局最大年份2024，而非每组的最大值；
• 标签格式化：round(mu,1)将数值保留1位小数，匹配示例中的显示格式；paste0()完成字符串拼接；
• 标签样式：fill="white"让标签背景为白色，增强可读性；nudge_x=1将标签向右偏移，避免和折线末端点重叠。

内容的提问来源于stack exchange，提问作者Homer Jay Simpson