我就废话不多说了，大家还是直接看代码吧~
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ts1<-ts(test_data$tot_num,frequency = 365,start=c(2017,11,21))
plot(ts1,col='blue',lty='dotted',ylim=c(50,550))
par(new=TRUE)
ts2<-ts(test_data$pre_result,frequency = 365,start=c(2017,11,21))
plot(ts2,col='red',ylim=c(50,550))
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好用，需要注意控制相同的xlim和ylim
补充：用R语言在同一副图里面画两个折线图的注意事项
如下所示：
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setwd("C:/Users/11565/Desktop/合并二")
shuju <- read.csv("数据.csv",header = T)
library(psych)
head(shuju)
attach(shuju)
head(mtcars)
aggregate(shuju,by= list(state),FUN = mean,na.rm = T)
tapply(shuju[,3],shuju$year,mean)#每次只能求一列
aggregate(shuju[,3:4],list(shuju[,2]),mean)#每次可以求多列
mean_1 <- aggregate(shuju[,3:6],list(shuju[,2]),mean)
detach(shuju)
attach(mean_1)
head(mean_1)
mean_1$pcap <- mean_1$pcap/10
mean_1$Group.1<- as.numeric(mean_1$Group.1)
plot(Group.1,pcap,lty= 3,pch = 21,ylim = c(1000,3000))#画不出两幅图的原因很可能是两个变量数量级存在问题
lines(Group.1,hwy/10,lty = 2,pch = 22)#画折现图要先看一下x对应的y和y的数量级如何
str(mean_1)
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补充：在R中把多条曲线放置在一张图中
如下：
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library(xlsx)
myield<-read.xlsx("myield.xlsx",header=T,sheetIndex=1)
head(myield)
time X3m X6m X1y X2y X3y X4y
1 2002.010.019889 0.020353 0.021264 0.023014 0.024670 0.026232
2 2002.020.020781 0.021131 0.021819 0.023155 0.024437 0.025663
3 2002.030.018449 0.018829 0.019574 0.021015 0.022389 0.023695
4 2002.040.019096 0.019325 0.019780 0.020668 0.021529 0.022362
5 2002.050.018228 0.018425 0.018815 0.019578 0.020319 0.021037
6 2002.060.017224 0.017479 0.017980 0.018952 0.019882 0.020771
tm<-myield[,2]
sm<-myield[,3]
oy<-myield[,4]
ty<-myield[,5]
time<-myield[,1]
thy<-myield[,6]
fy<-myield[,7]
plot(tm~time,type="l",lty=1)
lines(sm~time,col="red",lty=2)
lines(oy~time,col="blue",lty=3)
lines(ty~time,col="yellow",lty=4)
lines(thy~time,col="green",lty=5)
lines(fy~time,col="grey",lty=6)
title("YIELD(m)",lwd=3)
legend("topleft",cex=.6,c("tm","sm","oy","ty","thy","fy"),col=c("black","red","blue","yellow","green","grey"),lty=1:6)
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也可以应用matplot函数，但使用之前注意把数值型数据转换为数据框或者向量，根据本例，即把tm,sm,oy等数值型数据转化为数据框，
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z<-data.frame(cbind(tm,sm,oy,ty,thy,fy))
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然后
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matplot(time,z,col=1:6,type="l",lwd=2,xlab="",ylab="",lty=1:5)
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以上为个人经验，希望能给大家一个参考，也希望大家多多支持服务器之家。如有错误或未考虑完全的地方，望不吝赐教。
原文链接：https://blog.csdn.net/Jinpeijie217/article/details/88991235