R 用3个标签缩放5个刻度

我有5个条件：

 labels = c("Baseline","Passenger Drive","Passenger Drive","Remote Drive","Remote Drive")

我想把“乘客驾驶”和“远程驾驶”这两个标签放在现有点的中间

玩具数据集：

  df <- data.frame(cbind(cbind(condition = c("Baseline","Passenger Drive",
                        "Passenger Drive","Remote Drive","Remote Drive"),
          rt_type = c("none",rep(c("driver_rt","other_rt"),2))),
  rt = c(.4,.6,.5,.7,.62)))

  ggplot(data = df,aes(x = interaction(rt_type,condition), y = rt)) + 
  theme_classic() + 
  geom_line(group = 1, size = 1) +
  geom_point(size = 3) + 
  scale_x_discrete(labels = c("Baseline",
                              "Passenger Drive",
                              "Remote Drive")) +
  labs(x = "Condition by Speaker", y = "Reaction Time (s)",
       linetype = "Responder", shape = "Speaker")

df解决方案
简单地改变

  scale_x_discrete(labels = c("Baseline",
                              "Passenger Drive",
                              "Remote Drive")) +

到

可取的
我知道你没有要求一个更有效的方法，但我认为一个变量（例如rt_类型）应该映射到点形状

ggplot(data = df, aes(x = condition, y = rt, shape = rt_type)) +
  theme_classic() +
  geom_point(size = 3,) +
  scale_x_discrete(labels = c("Baseline",
                              "Passenger Drive",
                              "Remote Drive")) +
  labs(
    x = "Condition by Speaker",
    y = "Reaction Time (s)"
  )

您可以为x轴创建虚拟数字变量，并使用
scale\u x\u continuous
而不是
scale\u x\u discrete

# This replaces interaction(rt_type, condition)
df$intr <- as.numeric(as.factor(interaction(df$rt_type, df$condition)))

# Creating dummy mid point to place labels in the middle
ref_avg <- aggregate(intr ~ condition, df, mean)
df$my_breaks <- ref_avg[match(df$condition, ref_avg$condition), "intr"]

ggplot(data = df,aes(x = intr, y = rt)) + 
  theme_classic() + 
  geom_point(size = 3)  + 
  geom_path(group = 1) + 
  scale_x_continuous(breaks = df$my_breaks, labels = df$condition) + 
  labs(x = "Condition by Speaker", y = "Reaction Time (s)",
       linetype = "Responder", shape = "Speaker")

#这将替换交互（rt#U类型、条件）
df$intr谢谢！最后，它需要一个略为复杂的伪代码1 1 2 3 2 3 5 6 5 6（由于其他变量），但它可以使用scale_x_continuous。感谢您的建议。我提到了效率，因为线型和形状已经映射到其他变量，因为绘图比玩具数据集稍微复杂一些。
# This replaces interaction(rt_type, condition)
df$intr <- as.numeric(as.factor(interaction(df$rt_type, df$condition)))

# Creating dummy mid point to place labels in the middle
ref_avg <- aggregate(intr ~ condition, df, mean)
df$my_breaks <- ref_avg[match(df$condition, ref_avg$condition), "intr"]

ggplot(data = df,aes(x = intr, y = rt)) + 
  theme_classic() + 
  geom_point(size = 3)  + 
  geom_path(group = 1) + 
  scale_x_continuous(breaks = df$my_breaks, labels = df$condition) + 
  labs(x = "Condition by Speaker", y = "Reaction Time (s)",
       linetype = "Responder", shape = "Speaker")