使用R如下代码：df_line # filterGroup == 1_Negative Group == 2_NegativeGroup == 87_No learning ggplotaes横坐标纵坐标 group = Group color = Group fill = Group+ geom_point+ # geom_linealpha=05+ geom_smoothse =

如果纵坐标存在NA值，可以通过使用na.omit()函数来删除含有NA值的观测值，从而避免在绘制smooth曲线时出现问题。

以下是修改后的代码示例：

df_line %>%
  # filter(Group == "1_Negative"| Group == "2_Negative"|Group == "87_No learning") %>%
  ggplot(aes(横坐标,纵坐标, group = Group, color = Group, fill = Group))+
  geom_point()+
  # geom_line(alpha=0.5)+
  geom_smooth(data = na.omit(df_line), se = F) +  # 使用na.omit()删除含有NA值的观测值
  # scale_color_manual(values = c("red", "grey", "#a08dbb"))+
  labs(x = "Sleep Cycles", y = "SO-Spindle coupling count",color = NULL)+
  theme_bw()+
  theme(legend.position = "none")

通过使用data = na.omit(df_line)将geom_smooth()函数中的数据设置为删除了NA观测值的df_line数据框。这样，geom_smooth()函数将只考虑不含有NA值的观测值来拟合平滑曲线，从而避免了由于NA值导致的问题。