组合来自不同两个数据框的两个线图

Question

我有两个折线图显示：一个显示四个采样中六个物种的下降，另一个显示相同六个物种的总下降。 我想创建一个图，其中分别显示了六个物种和总体下降情况。

下面是我的六个物种的数据框示例

 Week       Species      Unit
   1           A           13
   1           B           24
   2           B           15
   2           C           32
   3           C           43
   4           D           32

下面是我用来创建显示六个物种衰退的折线图的代码

Species_Change<-ggplot(Total_Count, aes(x=Week, y=Unit, group=Scientific.name, color=Scientific.name)) +
  geom_point()+
  geom_line()+
  scale_colour_manual(values = c("yellow", "orange 2", "purple", "maroon 2", "blue", "purple 4","green"))+
  ylab("Total number of floral units over the four habitats")+
  xlab("Sampling round")+
  labs(col="Plant species")

以下是数据框的示例，显示了采样期间所有物种的总数

Week           Unit
 1              32
 2              55
 3              73
 4              62

下面显示了用于创建第二个折线图的代码，该折线图显示了采样轮次中所有物种的总数

Total_Change<-ggplot(Total_Round, aes(x=Week, y=Unit, )) +
  geom_point()+
  geom_line()+
  ylab("Total number of floral units over the four habitats")+
  xlab("Sampling round")+
  labs(col="Plant species")

Answer 1

我不确定这是否是您想要的，但您可以在Total_count data.frame中添加一个名为“total”的新物种。 使用您提供的数据：

数据

dput(Total_Count) structure(list(Week = c(1L, 1L, 2L, 2L, 3L, 4L), Species = structure(c(1L, 2L, 2L, 3L, 3L, 4L), .Label = c("A", "B", "C", "D"), class = "factor"), Unit = c(13L, 24L, 15L, 32L, 43L, 32L)), row.names = c(NA, -6L), class = "data.frame") dput(Total_Round) structure(list(Week = c(1, 2, 3, 4), Unit = c(32, 55, 73, 62)), class = "data.frame", row.names = c(NA, -4L))

代码

Total_Round$Species <- factor(rep("Total",nrow(Total_Round))) # Create total species df <- rbind(Total_Count, Total_Round) # Merge both data.frames AllwithTotal_Species_Change<-ggplot(df, aes(x=Week, y=Unit, group=Species, color=Species)) + geom_point()+ geom_line()+ scale_colour_manual(values = c("yellow", "orange 2", "purple", "maroon 2", "blue", "purple 4", "green"))+ ylab("Total number of floral units over the four habitats")+ xlab("Sampling round")+ labs(col="Plant species") AllwithTotal_Species_Change

希望这可以帮助！