这是我的问题：
使用这个简单的示例数据框：
    Samples = c("SRR9292593", "SRR9292593", "SRR9292593", "SRR9292594", "SRR9292594", "SRR9292594")
    expression_gene = c(3.5, 0.4, 8.2, 4.5, 3.2, 3.1)
    expression_intron = c(0.1, 0.1, 0.1, 0.5, 0.5, 0.5)
    p <- data.frame(Samples, expression_gene, expression_intron)
我想制作一个带有两个x轴的箱线图，一个指示"Samples"中的值，另一个带有"expression_intron"中相应的值。
我尝试了这个：
    ggplot(p, aes(x=reorder(Samples, expression_intron), y=expression_gene)) + 
           geom_boxplot(color="black") +
           scale_x_continuous(sec.axis = sec_axis(~ . * 1, breaks = c("SRR9292593", "SRR9292594"), labels = c("0.1","0.5")))
但它给我这个错误：
    Error: Discrete value supplied to continuous scale
我该如何修复这个问题？
提前感谢您的回答。

library(dplyr)
p2 <- p %>%
  mutate(
    Samples = reorder(Samples, expression_intron),
    expression_intron = factor(expression_intron)
  )
ggplot(p2, aes(x = as.numeric(Samples), y = expression_gene, group = Samples)) +
  geom_boxplot(color="black") +
  scale_x_continuous(
    # 分配断点/标签以将我们的数字转换为离散标签
    breaks = seq_along(levels(p2$Samples)),
    labels = levels(p2$Samples),
    sec.axis = sec_axis(
      ~ .,
      name = "expression_intron",
      # 这也可以是 seq_along(levels(p2$expr...))，效果一样
      breaks = seq_along(levels(p2$Samples)),
      labels = levels(p2$expression_intron)
    )
  ) +
  labs(x = "Samples")

[1]: https://i.stack.imgur.com/PFuK7.png
<details>
<summary>英文:</summary>
I think we can adapt https://stackoverflow.com/q/45361904/3358272 to force the x-axis to be continuous; I say &quot;adapt&quot; because when we convert `Samples` to a `factor` and use `as.numeric(Samples)`, it produces a single boxplot; we need to add `group=` to get it to split as needed.
Note that this requires a perfect 1-to-1 between `Samples` and `expression_intron`; anything else doesn&#39;t quite make sense in the perspective of your plotting request.
I&#39;ll demo with dplyr, but this can easily be adapted to base R if needed.
```r
library(dplyr)
p2 &lt;- p %&gt;%
  mutate(
    Samples = reorder(Samples, expression_intron),
    expression_intron = factor(expression_intron)
  )
ggplot(p2, aes(x = as.numeric(Samples), y = expression_gene, group = Samples)) +
  geom_boxplot(color=&quot;black&quot;) +
  scale_x_continuous(
    # assign breaks/labels to convert our numerics to discrete labels
    breaks = seq_along(levels(p2$Samples)),
    labels = levels(p2$Samples),
    sec.axis = sec_axis(
      ~ .,
      name = &quot;expression_intron&quot;,
      # this could be seq_along(levels(p2$expr...)) as well, same thing
      breaks = seq_along(levels(p2$Samples)),
      labels = levels(p2$expression_intron)
    )
  ) +
  labs(x = &quot;Samples&quot;)