R中多个绘图中的通用图例

如何编写代码为这7个绘图设置公共图例： 我试过这个代码，但效果不明显

par(mfrow=c(3,3))
# mortality age 50
plot(DataAge50$Year,DataAge50$DA_Female/DataAge50$EA_Female,xlab="Year",ylab="Mortality rates",main="Age 50",type="l",col="green",cex=1)
lines(DataAge50$Year,DataAge50$DBC_Female/DataAge50$EBC_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="blue",cex=1)
lines(DataAge50$Year,DataAge50$DM_Female/DataAge50$EM_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="red",cex=1)
lines(DataAge50$Year,DataAge50$DNB_Female/DataAge50$ENB_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="black",cex=1)
lines(DataAge50$Year,DataAge50$DNL_Female/DataAge50$ENL_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="yellow",cex=1)
lines(DataAge50$Year,DataAge50$DNTN_Female/DataAge50$ENTN_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="beige",cex=1)
lines(DataAge50$Year,DataAge50$DNS_Female/DataAge50$ENS_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="orange",cex=1)
lines(DataAge50$Year,DataAge50$DO_Female/DataAge50$EO_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="blue",cex=1)
lines(DataAge50$Year,DataAge50$DPEI_Female/DataAge50$EPEI_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="grey",cex=1)
lines(DataAge50$Year,DataAge50$DQ_Female/DataAge50$EQ_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="chocolate",cex=1)
lines(DataAge50$Year,DataAge50$DS_Female/DataAge50$ES_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="salmon",cex=1)
lines(DataAge50$Year,DataAge50$DY_Female/DataAge50$EY_Female,xlab="Year",ylab="Mortality rates",main="Age=50",type="l",col="maroon",cex=1)

#Moratlity rates by age=55

plot(DataAge55$Year,DataAge55$DA_Female/DataAge55$EA_Female,xlab="Year",ylab="Mortality rates",main="Age 55",type="l",col="green",cex=1)
lines(DataAge55$Year,DataAge55$DBC_Female/DataAge55$EBC_Female,xlab="Year",ylab="Mortality rates",main="Age 55",type="l",col="blue",cex=1)
lines(DataAge55$Year,DataAge55$DM_Female/DataAge55$EM_Female,xlab="Year",ylab="Mortality rates",main="Age 55",type="l",col="red",cex=1)
lines(DataAge55$Year,DataAge55$DNB_Female/DataAge55$ENB_Female,xlab="Year",ylab="Mortality rates",main="Age=55",type="l",col="black",cex=1)
lines(DataAge55$Year,DataAge55$DNL_Female/DataAge55$ENL_Female,xlab="Year",ylab="Mortality rates",main="Age=55",type="l",col="yellow",cex=1)
lines(DataAge55$Year,DataAge55$DNTN_Female/DataAge55$ENTN_Female,xlab="Year",ylab="Mortality rates",main="Age=55",type="l",col="beige",cex=1)
lines(DataAge55$Year,DataAge55$DNS_Female/DataAge55$ENS_Female,xlab="Year",ylab="Mortality rates",main="Age=55",type="l",col="orange",cex=1)
lines(DataAge55$Year,DataAge55$DO_Female/DataAge55$EO_Female,xlab="Year",ylab="Mortality rates",main="Age=55",type="l",col="blue",cex=1)
lines(DataAge55$Year,DataAge55$DPEI_Female/DataAge55$EPEI_Female,xlab="Year",ylab="Mortality rates",main="Age=55",type="l",col="grey",cex=1)
lines(DataAge55$Year,DataAge55$DQ_Female/DataAge55$EQ_Female,xlab="Year",ylab="Mortality rates",main="Age=55",type="l",col="chocolate",cex=1)
lines(DataAge55$Year,DataAge55$DS_Female/DataAge55$ES_Female,xlab="Year",ylab="Mortality rates",main="Age=55",type="l",col="salmon",cex=1)
lines(DataAge55$Year,DataAge55$DY_Female/DataAge55$EY_Female,xlab="Year",ylab="Mortality rates",main="Age=55",type="l",col="maroon",cex=1)

#mortality age 60

plot(DataAge60$Year,DataAge60$DA_Female/DataAge60$EA_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="green",cex=1)
lines(DataAge60$Year,DataAge60$DBC_Female/DataAge60$EBC_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="blue",cex=1)
lines(DataAge60$Year,DataAge60$DM_Female/DataAge60$EM_Female,xlab="Year",ylab="Mortality rates",main="Age 60",type="l",col="red",cex=1)
lines(DataAge60$Year,DataAge60$DNB_Female/DataAge60$ENB_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="black",cex=1)
lines(DataAge60$Year,DataAge60$DNL_Female/DataAge60$ENL_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="yellow",cex=1)
lines(DataAge60$Year,DataAge60$DNTN_Female/DataAge60$ENTN_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="beige",cex=1)
lines(DataAge60$Year,DataAge60$DNS_Female/DataAge60$ENS_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="orange",cex=1)
lines(DataAge60$Year,DataAge60$DO_Female/DataAge60$EO_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="blue",cex=1)
lines(DataAge60$Year,DataAge60$DPEI_Female/DataAge60$EPEI_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="grey",cex=1)
lines(DataAge60$Year,DataAge60$DQ_Female/DataAge60$EQ_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="chocolate",cex=1)
lines(DataAge60$Year,DataAge60$DS_Female/DataAge60$ES_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="salmon",cex=1)
lines(DataAge60$Year,DataAge60$DY_Female/DataAge60$EY_Female,xlab="Year",ylab="Mortality rates",main="Age=60",type="l",col="maroon",cex=1)

#mortality age 65

plot(DataAge65$Year,DataAge65$DA_Female/DataAge65$EA_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="green",cex=1)
lines(DataAge65$Year,DataAge65$DBC_Female/DataAge65$EBC_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="blue",cex=1)
lines(DataAge65$Year,DataAge65$DM_Female/DataAge65$EM_Female,xlab="Year",ylab="Mortality rates",main="Age 65",type="l",col="red",cex=1)
lines(DataAge65$Year,DataAge65$DNB_Female/DataAge65$ENB_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="black",cex=1)
lines(DataAge65$Year,DataAge65$DNL_Female/DataAge65$ENL_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="yellow",cex=1)
lines(DataAge65$Year,DataAge65$DNTN_Female/DataAge65$ENTN_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="beige",cex=1)
lines(DataAge65$Year,DataAge65$DNS_Female/DataAge65$ENS_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="orange",cex=1)
lines(DataAge65$Year,DataAge65$DO_Female/DataAge65$EO_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="blue",cex=1)
lines(DataAge65$Year,DataAge65$DPEI_Female/DataAge65$EPEI_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="grey",cex=1)
lines(DataAge65$Year,DataAge65$DQ_Female/DataAge65$EQ_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="chocolate",cex=1)
lines(DataAge65$Year,DataAge65$DS_Female/DataAge65$ES_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="salmon",cex=1)
lines(DataAge65$Year,DataAge65$DY_Female/DataAge65$EY_Female,xlab="Year",ylab="Mortality rates",main="Age=65",type="l",col="maroon",cex=1)

#mortality age 70

plot(DataAge70$Year,DataAge70$DA_Female/DataAge70$EA_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="green",cex=1)
lines(DataAge70$Year,DataAge70$DBC_Female/DataAge70$EBC_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="blue",cex=1)
lines(DataAge70$Year,DataAge70$DM_Female/DataAge70$EM_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="red",cex=1)
lines(DataAge70$Year,DataAge70$DNB_Female/DataAge70$ENB_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="black",cex=1)
lines(DataAge70$Year,DataAge70$DNL_Female/DataAge70$ENL_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="yellow",cex=1)
lines(DataAge70$Year,DataAge70$DNTN_Female/DataAge70$ENTN_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="beige",cex=1)
lines(DataAge70$Year,DataAge70$DNS_Female/DataAge70$ENS_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="orange",cex=1)
lines(DataAge70$Year,DataAge70$DO_Female/DataAge70$EO_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="blue",cex=1)
lines(DataAge70$Year,DataAge70$DPEI_Female/DataAge70$EPEI_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="grey",cex=1)
lines(DataAge70$Year,DataAge70$DQ_Female/DataAge70$EQ_Female,xlab=”Year”,ylab=”Mortality rates”,main=”Age=70”,type=”l”,col=”chocolate”,cex=1)
lines(DataAge70$Year,DataAge70$DS_Female/DataAge70$ES_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="salmon",cex=1)
lines(DataAge70$Year,DataAge70$DY_Female/DataAge70$EY_Female,xlab="Year",ylab="Mortality rates",main="Age=70",type="l",col="maroon",cex=1)
# mortality age 75
plot(DataAge75$Year,DataAge75$DA_Female/DataAge75$EA_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="green",cex=1)
lines(DataAge75$Year,DataAge75$DBC_Female/DataAge75$EBC_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="blue",cex=1)
lines(DataAge75$Year,DataAge75$DM_Female/DataAge75$EM_Female,xlab="Year",ylab="Mortality rates",main="Age 75",type="l",col="red",cex=1)
lines(DataAge75$Year,DataAge75$DNB_Female/DataAge75$ENB_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="black",cex=1)
lines(DataAge75$Year,DataAge75$DNL_Female/DataAge75$ENL_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="yellow",cex=1)
lines(DataAge75$Year,DataAge75$DNTN_Female/DataAge75$ENTN_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="beige",cex=1)
lines(DataAge75$Year,DataAge75$DNS_Female/DataAge75$ENS_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="orange",cex=1)
lines(DataAge75$Year,DataAge75$DO_Female/DataAge75$EO_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="blue",cex=1)
lines(DataAge75$Year,DataAge75$DPEI_Female/DataAge75$EPEI_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="grey",cex=1)
lines(DataAge75$Year,DataAge75$DQ_Female/DataAge75$EQ_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="chocolate",cex=1)
lines(DataAge75$Year,DataAge75$DS_Female/DataAge75$ES_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="salmon",cex=1)
lines(DataAge75$Year,DataAge75$DY_Female/DataAge75$EY_Female,xlab="Year",ylab="Mortality rates",main="Age=75",type="l",col="maroon",cex=1)
# mortality age 80
plot(DataAge80$Year,DataAge80$DA_Female/DataAge80$EA_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="green",cex=1)
lines(DataAge80$Year,DataAge80$DBC_Female/DataAge80$EBC_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="blue",cex=1)
lines(DataAge80$Year,DataAge80$DM_Female/DataAge80$EM_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="red",cex=1)
lines(DataAge80$Year,DataAge80$DNB_Female/DataAge80$ENB_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="black",cex=1)
lines(DataAge80$Year,DataAge80$DNL_Female/DataAge80$ENL_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="yellow",cex=1)
lines(DataAge80$Year,DataAge80$DNTN_Female/DataAge80$ENTN_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="beige",cex=1)
lines(DataAge80$Year,DataAge80$DNS_Female/DataAge80$ENS_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="orange",cex=1)
lines(DataAge80$Year,DataAge80$DO_Female/DataAge80$EO_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="blue",cex=1)
lines(DataAge80$Year,DataAge80$DPEI_Female/DataAge80$EPEI_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="grey",cex=1)
lines(DataAge80$Year,DataAge80$DQ_Female/DataAge80$EQ_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="chocolate",cex=1)
lines(DataAge80$Year,DataAge80$DS_Female/DataAge80$ES_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="salmon",cex=1)
lines(DataAge80$Year,DataAge80$DY_Female/DataAge80$EY_Female,xlab="Year",ylab="Mortality rates",main="Age=80",type="l",col="maroon",cex=1)
[enter link description here][1]

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请您帮助我改进我的代码好吗？

在没有尝试或甚至没有看到数据的情况下，这段代码是无法运行的，但它应该能让您了解如何简化流程：

legend(“topright”,legend=c(“Alberta”,”British Columbia”,”Manitoba”,”New Brunswick”,”New Foundlands”,New Terrotories”, New scotia”, “Ontario”,Prince Edouad Island”,”Quebec”, “SaKastchewan””Yukon”),cex=0.8,fill.colors)

#执行数据列的重复标准化
规范化我在哪里可以找到数据集，例如，
DataAge50
来复制您的代码？代码中有很多重复，像lattice或ggplot2这样的包可能会大大简化您的代码（并注意图例的副作用）。好的，谢谢您的帮助。我试过了，但没有达到我预期的效果。我将在包裹格中找到更多信息。好的，谢谢你的帮助。我试过了，但没有达到我预期的效果。在我的图中，我想到了X=1921-2009年的年份，Y=商，正如你在我的代码中看到的，这是死亡率。我可以用收件箱将数据库数据发送给你。我对r绝对是新手，这就是为什么我在挣扎。感谢只有当你提供一个完全可再现的问题，包括数据时，人们才能在这里帮助你，最好把它缩小到你试图做的事情的最简单的例子。它不必是您的实际数据集，虚拟数据集通常更好。@NtamJoachile:这在很多级别上都是错误的，我甚至不知道从哪里开始……请，用一个最小的、自包含的、可复制的示例再试一次（要明白，你需要激励人们花时间帮助你——追逐你的数据或编写由于问题没有得到正确的说明而无法运行的解决方案是不有趣的。同时，也不需要经历许多与问题核心无关的代码行）。
# perform the repetitive normalisation of the columns of data
normalise <- function(d, varnames = c("A","BC","M","NB","NL",
                                      "NTN","NS","O","PEI","Q","S","Y")){
  dnames <- paste0("D", varnames, "_Female")
  enames <- paste0("E", varnames, "_Female")

  result <- data.frame(d[["Year"]], d[dnames] / d[enames])
  names(result) <- c("date", varnames)
  result

}
# combine all the datasets in a list
l1 <- list(age50 = DataAge50,
           age55 = DataAge55,
           age60 = DataAge60,
           age65 = DataAge65,
           age70 = DataAge70,
           age75 = DataAge75,
           age80 = DataAge80)

# apply our function to all datasets
l2 <- lapply(l1, normalise)

library(reshape2)
# combine datasets into a long format data.frame for plotting
m <- melt(l2, id="date")
str(m)

library(ggplot2)
# plot with facetting and automatic legend
ggplot(m, aes(date, value, colour=variable)) + 
  facet_wrap(~L1, ncol=3) +
  geom_path()