英文:
One of the groups not showing when using combined legend on ggplot2
问题
我正在尝试在两个图中绘制三个模型，但这两个图只有一个共同的模型（模型 A）。然而，当我尝试制作一个合并的图时，并没有显示所有三个模型。我正在寻找一个让图例包含所有三个模型（A、B、C）的方法。**代码：**cols=c("red","blue","green")df = rbind(data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="B",x=10:1,val=runif(n=10,min=0,max=1)))plot<-ggplot()+geom_point(df, mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(df, mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y 轴", x="x 轴",color="模型")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","B","C"),values = c(cols[1],cols[2],cols[3]))gdf = rbind(data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="C",x=10:1,val=runif(n=10,min=0,max=1)))gplot<-ggplot()+geom_point(gdf, mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(gdf, mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y 轴", x="x 轴",color="模型")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","C","B"),values = c(cols[1],cols[3],cols[2]))final_plot = ggarrange(plot,gplot,nrow=1,ncol=2,common.legend = TRUE, legend = "bottom")**图：**[![enter image description here][1]][1]**最新尝试：** 我尝试将数据合并为一个数据集，然后进行子集，但结果相同cols=c("red","blue","green")df = rbind(data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="B",x=10:1,val=runif(n=10,min=0,max=1)), data.frame(model ="C",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)))df$ind=1df$ind[21:40]=0plot<-ggplot(df)+geom_point(data=df%>%subset(ind==1), mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(data=df%>%subset(ind==1), mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y 轴", x="x 轴",color="模型")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","B","C"),values = c(cols[1],cols[2],cols[3]))gplot<-ggplot(df)+geom_point(data=df%>%subset(ind==0), mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(data=df%>%subset(ind==0), mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y 轴", x="x 轴",color="模型")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","C","B"),values = c(cols[1],cols[3],cols[2]))final_plot = ggarrange(plot,gplot,nrow=1,ncol=2,common.legend = TRUE, legend = "bottom")
英文:
I'm trying to plot 3 models over 2 plots, but the plots only have 1 model in common (model A). However, when I try to make a combined plot, it doesn't show all 3 models. I'm looking for a way for the legend to have all 3 models (A,B,C).
Code:
cols=c("red","blue","green")df = rbind(data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="B",x=10:1,val=runif(n=10,min=0,max=1)))plot<-ggplot()+geom_point(df, mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(df, mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y axis", x="x axis",color="Model")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","B","C"),values = c(cols[1],cols[2],cols[3]))gdf = rbind(data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="C",x=10:1,val=runif(n=10,min=0,max=1)))gplot<-ggplot()+geom_point(gdf, mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(gdf, mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y axis", x="x axis",color="Model")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","C","B"),values = c(cols[1],cols[3],cols[2]))final_plot = ggarrange(plot,gplot,nrow=1,ncol=2,common.legend = TRUE, legend = "bottom")
Plot:
Latest attempt: I've tried to combine the data into one dataset and then subset, but I get the same result
cols=c("red","blue","green")df = rbind(data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="B",x=10:1,val=runif(n=10,min=0,max=1)), data.frame(model ="C",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)))df$ind=1df$ind[21:40]=0plot<-ggplot(df)+geom_point(data=df%>%subset(ind==1), mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(data=df%>%subset(ind==1), mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y axis", x="x axis",color="Model")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","B","C"),values = c(cols[1],cols[2],cols[3]))gplot<-ggplot(df)+geom_point(data=df%>%subset(ind==0), mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(data=df%>%subset(ind==0), mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y axis", x="x axis",color="Model")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","C","B"),values = c(cols[1],cols[3],cols[2]))final_plot = ggarrange(plot,gplot,nrow=1,ncol=2,common.legend = TRUE, legend = "bottom")
答案1
得分: 1
我成功地用Paul的建议解决了这个问题：
cols=c("red","blue","green")df = rbind(data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="B",x=10:1,val=runif(n=10,min=0,max=1)), data.frame(model ="C",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)))df$ind=1df$ind[21:40]=0plot<-ggplot(df)+geom_point(data=df, mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(data=df, mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y axis", x="x axis",color="Model")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","B","C"),values = c(cols[1],cols[2],cols[3]))+facet_wrap(~ ind)
英文:
I managed to solve this using the suggestion by Paul:
cols=c("red","blue","green")df = rbind(data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="B",x=10:1,val=runif(n=10,min=0,max=1)), data.frame(model ="C",x=10:1,val=runif(n=10,min=0,max=1)),data.frame(model ="A",x=10:1,val=runif(n=10,min=0,max=1)))df$ind=1df$ind[21:40]=0plot<-ggplot(df)+geom_point(data=df, mapping=aes(x=x, y=val, group=model, color=model,size=2),size=2)+scale_x_reverse(limits = c(10,0))+geom_line(data=df, mapping=aes(x=x, y=val, group=model, color=model,size=1),size=1)+scale_y_continuous(limits = c(0, 1))+labs(y = "y axis", x="x axis",color="Model")+ theme_bw() +theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +scale_color_manual(labels = c("A","B","C"),values = c(cols[1],cols[2],cols[3]))+facet_wrap(~ ind)
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