下面是使用ggtext包的一种简单且更通用的方法

的数据
生产：

library(ggtext) 

ggplot(iris, aes(Sepal.Length, Sepal.Width, color = Species)) +
  geom_point(size = 3) +
  scale_color_manual(
    name = NULL,
    values = c(setosa = "#0072B2", virginica = "#009E73", versicolor = "#D55E00"),
    labels = c(
      setosa = "<i style='color:#0072B2'>I. setosa</i>",
      virginica = "<i style='color:#009E73'>I. virginica</i>",
      versicolor = "<i style='color:#D55E00'>I. versicolor</i>")
  ) +
  labs(
    title = "**Fisher's *Iris* dataset**  
    <span style='font-size:11pt'>Sepal width vs. sepal length for 
    <span style='color:#0072B2;'>setosa</span>, 
    <span style='color:#D55E00;'>versicolor</span>, and
    <span style='color:#009E73;'>virginica</span>
    </span>",
    x = "Sepal length (cm)", y = "Sepal width (cm)"
  ) +
  theme_minimal() +
  theme(
    plot.title = element_markdown(lineheight = 1.1),
    legend.text = element_markdown(size = 11)
  )

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这个解决方案是基于Displaying text below the plot generated by ggplot2和Colorize parts of the title in a plot的（感谢贡献者！）.
通过对文本使用phantom占位符，我们避免了（大部分）位置的硬编码。

# create text grobs, one for each color
library(grid)
t1 <- textGrob(expression("Concentration of " * phantom(bold("affluence")) * "and" * phantom(bold("poverty")) * " nationwide"),
               x = 0.5, y = 1.1, gp = gpar(col = "black"))

t2 <- textGrob(expression(phantom("Concentration of ") * bold("affluence") * phantom(" and poverty nationwide")),
               x = 0.5, y = 1.1, gp = gpar(col = "#EEB422"))

t3 <- textGrob(expression(phantom("Concentration of affluence and ") * bold("poverty") * phantom(" nationwide")),
               x = 0.5, y = 1.1, gp = gpar(col = "#238E68"))

# plot and add grobs with annotation_custom
ggplot(data, aes(year, concentration, color = group)) +
  geom_line(size = 1.5) +
  geom_point(size = 4) +
  annotation_custom(grobTree(t1, t2, t3)) +
  scale_y_continuous(limits = c(0, 0.15)) +
  scale_color_manual(values = c("#EEB422", "#238E68")) +
  coord_cartesian(clip = "off") +
  labs(x = NULL, y = NULL) +
  theme_minimal() +
  theme(legend.position = 'none',
        # add some extra margin on top
        plot.margin = unit(c(4, 1, 1, 1), "lines"))

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x1c 0d1x的数据
对于大量的彩色单词，不同expression的创建应该更多地以编程方式完成。例如，在base图的类似问题中，可以看到nice multiTitle函数：title: words in different colors?，在ggplot中也应该有用。

一个有点麻烦的annotation_custom解决方案：

ggplot(dat, aes(year, concentration, color = group)) +
  geom_line(size = 1.5) +
  geom_point(size = 4) +
  scale_y_continuous(limits = c(0, 0.16)) +
  labs(x = NULL, y = NULL, title = ' ') +
  theme_minimal() +
  theme(legend.position = 'none') +
  scale_color_manual(values = c('#EEB422', '#238E68')) +
  annotation_custom(textGrob('Concentration of', gp = gpar(col = 'black')), 
                    xmin = 1972, xmax = 1972, ymin = 0.165, ymax = 0.165) +
  annotation_custom(textGrob('affluence', gp = gpar(col = '#EEB422', fontface = 'bold')), 
                    xmin = 1975.7, xmax = 1975.7, ymin = 0.165, ymax = 0.165) +
  annotation_custom(textGrob(' and ', gp = gpar(col = 'black')), 
                    xmin = 1977.65, xmax = 1977.65, ymin = 0.165, ymax = 0.165) +
  annotation_custom(textGrob('poverty', gp = gpar(col = '#238E68', fontface = 'bold')), 
                    xmin = 1979.35, xmax = 1979.35, ymin = 0.165, ymax = 0.165) +
  annotation_custom(textGrob('nationwide', gp = gpar(col = 'black')), 
                    xmin = 1982, xmax = 1982, ymin = 0.165, ymax = 0.165)

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其给出：

的数据
这种方法的主要缺点是，它需要大量的参数，以获得正确的位置标题的话摆弄。