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最新推荐文章于 2024-10-20 06:02:48 发布

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title: “Data visualization manual of R”
author: “hardy”
date: “2020”
output:
pdf_document: default
html_document: default

数据可视化手册代码：数据探索性分析主要条形图，直方图，散点直线图、箱线图以及自制函数图。我们从条形图开始。首先了解绘图区域，绘图行为和ggplot2参见R绘图系统。
绘图行为：颜色（bg，fg，col）
线条（lty，lwd，solid，dashed）
文本（ps，cex，font，family，adj）
数据符号（pch，type）
坐标轴（axis）
ggplot：数据：data
几何对象和图形属性：geom_point,geom_line,geom_path,
aes(aethetics)映射到图形属性
标度:scale_x_continuous,sacle_y_continuous
统计变换:stat，stat="identity”
图例:shap
位置调整：position="fill"等
坐标变换：coord_trans
分面:face_wrap
主题：theme
注释：geom_hline,geom_text
本文的翻译过程将不间断持续更新，在提升自己能力的同时，希望对大家学习R语言绘图有帮助。

knitr::opts_chunk$set(echo = TRUE)

直方图
简单直方图
连续形变量

rm(list=ls())
library(gcookbook)
library(ggplot2)
head(pg_mean)
ggplot(pg_mean,aes(x=group,y=weight))+
  geom_bar(stat="identity")

使用factor转为离散型变量

ggplot(BOD,aes(x=Time,y=demand))+geom_bar(stat="identity")
ggplot(BOD,aes(x=factor(Time),y=demand))+geom_bar(stat="identity")
ggplot(BOD,aes(x=factor(Time),y=demand))+geom_bar(stat="identity",
                                                  fill="lightblue",
                                                  color="black")

簇状直方图,对比位置调整缺失的不同

ggplot(cabbage_exp,aes(x=Date,y=Weight,fill=Cultivar))+
         geom_bar(position = "dodge",stat = "identity")
ggplot(cabbage_exp,aes(x=Date,y=Weight,fill=Cultivar))+
         geom_bar(stat = "identity")
ggplot(cabbage_exp,aes(x=Date,y=Weight,fill=Cultivar))+
         geom_bar(position="dodge",stat = "identity",color="black")+
          scale_fill_brewer(palette = "Pastell")

绘制频数条形图

ggplot(diamonds,aes(x=cut))+geom_bar()
ggplot(diamonds,aes(x=carat))+geom_bar(stat = "bin")

条形图着色

head(uspopchange)
upc<-subset(uspopchange,rank(Change)>40)
ggplot(upc,aes(x=reorder(Abb,Change),y=Change,fill=Region))+geom_bar(stat = "identity",color="black")+
  scale_fill_manual(values = c("#669933","#FFCC66"))+xlab("State")

正负条形图着色

csub<-subset(climate,Source=="Berkeley"&Year>=1900)
csub$pos<-csub$Anomaly10y>=0
ggplot(csub,aes(x=Year,y=Anomaly10y,fill=pos))+geom_bar(stat="identity",position = "identity")
ggplot(csub,aes(x=Year,y=Anomaly10y,fill=pos))+
  geom_bar(stat="identity",position = "identity",colour="black",size=0.25)+
  scale_fill_manual(values = c("#CCEEFF","#FFDDDD"),guide=FALSE)

调整条形图宽度和间距

ggplot(pg_mean,aes(x=group,y=weight))+geom_bar(stat = "identity",width = 0.5)

ggplot(pg_mean,aes(x=group,y=weight))+geom_bar(stat = "identity",width = 1)

绘制堆积条形图

ggplot(cabbage_exp,aes(x=Date,y=Weight,fill=Cultivar))+
  geom_bar(stat="identity")+
  guides(fill=guide_legend(reverse = TRUE))

library(plyr)
ggplot(cabbage_exp,aes(x=Date,y=Weight,fill=Cultivar,order=desc(Cultivar)))+
  geom_bar(stat="identity")##图例顺序的调整

library(plyr)
ggplot(cabbage_exp,aes(x=Date,y=Weight,fill=Cultivar))+
  geom_bar(stat = "identity",colour="black")+
  guides(fill=guide_legend(reverse = TRUE))+
  scale_fill_brewer(palette = "Pastell")

绘制堆积百分比条形图

ce<-ddply(cabbage_exp,"Date",
          transform,percent_weight=Weight/sum(Weight)*100)
ggplot(ce,aes(x=Date,y=percent_weight,fill=Cultivar))+
  geom_bar(stat = "identity")

ggplot(ce,aes(x=Date,y=percent_weight,fill=Cultivar))+
  geom_bar(stat = "identity",colour="black")+
  guides(fill=guide_legend(reverse = TRUE))+
  scale_fill_brewer(palette = "Pastell")

条件数据标签

ggplot(cabbage_exp,aes(x=interaction(Date,Cultivar),y=Weight))+
  geom_bar(stat = "identity")+
  geom_text(aes(label=Weight),vjust=1.5,colour="white")

ggplot(cabbage_exp,aes(x=interaction(Date,Cultivar),y=Weight))+
  geom_bar(stat = "identity")+
  geom_text(aes(label=Weight),vjust=-0.5,colour="black")

堆积条形图的数据标签

ce<-arrange(cabbage_exp,Date,Cultivar)
ce<-ddply(ce,"Date",transform,label_y=cumsum(Weight)-0.5*Weight)
ggplot(ce,aes(x=Date,y=Weight,fill=Cultivar))+
  geom_bar(stat = "identity")+
  geom_text(aes(y=label_y,label=Weight),colour="White")

ggplot(ce,aes(x=Date,y=Weight,fill=Cultivar))+
  geom_bar(stat = "identity")+
  geom_text(aes(y=label_y,label=Weight),colour="White")

ggplot(ce,aes(x=Date,y=Weight,fill=Cultivar))+
  geom_bar(stat = "identity",colour="black")+
  geom_text(aes(y=label_y,label=paste(format(Weight,nsmall = 2),"kg")),
            size=4)+
  guides(fill=guide_legend(reverse = TRUE))+
  scale_fill_brewer(palette = "Pastell")

绘制cleveland点图

tophit<-tophitters2001[1:25,]
ggplot(tophit,aes(x=avg,y=name))+geom_point()

ggplot(tophit,aes(x=avg,y=reorder(name,avg)))+
  geom_point(size=3)+
  theme_bw()+
  theme(axis.text.x = element_text(angle = 60,hjust = 1),
        panel.grid.major.y =element_blank(),#主要网格线
        panel.grid.minor.y = element_blank(),#次要网格线
        panel.grid.major.x = element_line(colour = "grey60",linetype = "dashed"))

ggplot(tophit,aes(x=reorder(name,avg),y=avg))+
  geom_point(size=3)+
  theme_bw()+
  theme(axis.text.x = element_text(angle = 60,hjust = 1),
        panel.grid.major.y =element_blank(),#主要网格线
        panel.grid.minor.y = element_blank(),#次要网格线
        panel.grid.major.x = element_line(colour = "grey60",linetype = "dashed"))

火柴棒图

ggplot(tophit,aes(x=avg,y=name))+
  geom_segment(aes(yend=name),xend=0,colour="grey50")+
  geom_point(size=3,aes(colour=lg))+
  scale_color_brewer(palette = "Set1",limits=c("NL","AL"))+
  theme_bw()+
  theme(panel.grid.major = element_blank(),
        legend.position = c(1,0.55),
        legend.justification = c(1,0.5))

ggplot(tophit,aes(x=avg,y=name))+
  geom_segment(aes(yend=name),xend=0,colour="grey50")+
  geom_point(size=3,aes(colour=lg))+
  scale_color_brewer(palette = "Set1",limits=c("NL","AL"),guide=FALSE)+
  theme_bw()+
  theme(panel.grid.major.y =element_blank())+
  facet_grid(lg~.,scales="free_y",space="free_y")
        
  
#以对分组的火柴棒图

折线图

      ggplot(BOD,aes(x=Time,y=demand))+geom_line()#折线图
      ggplot(BOD,aes(x=Time,y=demand,group=1))+geom_line()#折线图
      ggplot(BOD,aes(x=Time,y=demand,group=1))+geom_line()+
        ylim(0,max(BOD$demand))#限制Y轴
      ggplot(BOD,aes(x=Time,y=demand,group=1))+geom_line()+
      expand_limits(y=0)#限制Y轴距离
      ggplot(BOD,aes(x=Time,y=demand,group=1))+geom_line()+
      geom_point()#添加点标签
      
      ggplot(worldpop,aes(x=Year,y=Population))+geom_line()+geom_point()

绘制多重折线图

    tg<-ddply(ToothGrowth,c("supp","dose"),summarise,length=mean(len))
    ggplot(tg,aes(x=dose,y=length,colour=supp))+geom_line()
    ggplot(tg,aes(x=dose,y=length,linetype=supp))+geom_line()
    ggplot(tg,aes(x=factor(dose),y=length,colour=supp,group=supp))+
    geom_line()##factor将连续型变量转为因子
    ggplot(tg,aes(x=dose,y=length,shape=supp))+
             geom_line()+
             geom_point(size=4,shape=2)
ggplot(tg,aes(x=dose,y=length,fill=supp))+
             geom_line()+
             geom_point(size=4,shape=2)
     
     
ggplot(tg,aes(x=dose,y=length,fill=supp))+
             geom_line(position = position_dodge(0.2))+##连接移动线左移和右移动
             geom_point(position = position_dodge(0.2),size=4)

修改线条样式

  ggplot(BOD,aes(x=Time,y=demand))+
  geom_line(linetype="dashed",size=1,color="blue")
  tg<-ddply(ToothGrowth,c("supp","dose"),summarise,
            length=mean(len))
  ggplot(tg,aes(x=dose,y=length,colour=supp))+
  geom_line()+
  scale_color_brewer(palette = "Set1")

修改数据标记样式

  ggplot(BOD,aes(x=Time,y=demand))+
  geom_line()+
  geom_point(size=4,shape=22,colour="darkred",fill="pink")
  ggplot(BOD,aes(x=Time,y=demand))+
  geom_line()+
  geom_point(size=4,shape=21,colour="darkred",fill="white")

绘制面积图geom_area

    sunspotyear<-data.frame(
      Year=as.numeric(time(sunspot.year)),
      sunspots=as.numeric(sunspot.year)
    )
    ggplot(sunspotyear,aes(x=Year,y=sunspots))+
      geom_area()
    
  ggplot(sunspotyear,aes(x=Year,y=sunspots))+
    geom_area(color="black",alpah=0.2,fill="blue")
  ggplot(sunspotyear,aes(x=Year,y=sunspots))+
    geom_area(alpah=0.2,fill="blue")+
    geom_line()

绘制堆积面积图

    library(gcookbook)
    ggplot(uspopage,aes(x=Year,y=Thousands,fill=AgeGroup))+
    geom_area()

    
    ggplot(uspopage,aes(x=Year,y=Thousands,fill=AgeGroup))+
    geom_area(colour="black",size=0.2,alpha=0.4)+
    scale_fill_brewer(palette="Blues",breaks=rev(levels(uspopage$AgeGroup)))
    # 反转图例
    ggplot(uspopage,aes(x=Year,y=Thousands,fill=AgeGroup,order=desc(AgeGroup)))+
    geom_area(colour="black",size=0.2,alpha=0.4)+
    scale_fill_brewer(palette="Blues")
    #
    ggplot(uspopage,aes(x=Year,y=Thousands,fill=AgeGroup,order=desc(AgeGroup)))+
      geom_area(colour=NA,alpha=0.4)+
      scale_fill_brewer(palette = "Blues")+
      geom_line(position = "stack",size=0.2)

百分比堆积面积图

    library(plyr)
    uspopage_prop<-ddply(uspopage,"Year",transform,Percent=Thousands/sum(Thousands)*100)
    ggplot(uspopage,aes(x=Year,y=uspopage_prop$Percent,fill=AgeGroup))+
      geom_area(colour="black",size=0.2,alpha=0.4)+
      scale_fill_brewer(palette = "Blues",breaks=rev(levels(uspopage$AgeGroup)))

添加置信区间

library(gcookbook)
clim<-subset(climate,Source=="Berkeley",
             select = c("Year","Anomaly10y",
                        "Unc10y"))
ggplot(clim,aes(x=Year,y=Anomaly10y))+
    geom_ribbon(aes(ymin=Anomaly10y-Unc10y,ymax=Anomaly10y+Unc10y),colour="grey50",alpha=0.2)+
    geom_line()