再说ggplot2

今天快下班的时候，业务临时提出了个需求，想看到网站跳出率分析数据，不得不在用气ggplot2快速画了几个图，中途还出了点差错，reshape包中的melt函数太久没用，忘了，耽误不少时间，不说，直接上ggplot的代码，代码实现的是散点连线图，有很多细节方面的东西，有心情的话看看：

library(RMySQL)library(ggplot2)library(reshape)# 文件操作# list.files(pattern=("\\.pdf$"))# file.remove( list.files(pattern=("\\.pdf$")))# file.exists("uv走势图total.pdf")conn <- dbConnect(MySQL(), dbname = "pms", username="gaoyang922", password="gaoyang922@123456!",host="10.10.109.62",port=1333)query_homepage<-dbSendQuery(conn,"select insert_date,avg(stay_time) as avg_staytime from( select left(insert_time,8) as insert_date, case when stay_time >=1800 then 1800  else stay_time end as  stay_time  from tracker.hbase_visit where page_url like '%www.zhong.com%') a group by insert_date  having   insert_date  is not null;")result_homepage<- fetch(query_homepage,n=-1)query_detailpage<-dbSendQuery(conn,"select insert_date,avg(stay_time) as avg_staytime from(select left(insert_time,8) as insert_date,case when stay_time >=1800 then 1800  else stay_time end as  stay_timefrom tracker.hbase_visit where page_url like '%item.zhong.com/item/detail.do?productId%') a group by insert_date having   insert_date  is not null;")result_detailpage<- fetch(query_detailpage,n=-1)query_homejumppage<-dbSendQuery(conn,"select insert_date,pv,bounce,  (bounce/pv) as bounceRate from( select  left(insert_time,8) as insert_date, count(*) as pv,sum(case when stay_time =0 and leave_time=0 then 1 else 0 end) as bounce  from tracker.hbase_visit where page_url like '%www.zhong.com%'  group by left(insert_time,8) ) a  where insert_date is not null ;")result_homejumppage<- fetch(query_homejumppage,n=-1)query_detailjumppage<-dbSendQuery(conn,"select insert_date,pv,bounce,  (bounce/pv) as bounceRate from(select  left(insert_time,8) as insert_date, count(*) as pv,                                  sum(case when stay_time =0 and  leave_time=0  then 1 else 0 end) as bounce                                  from tracker.hbase_visit where page_url like '%item.zhong.com/item/detail.do?productId%'                                  group by left(insert_time,8)) a where insert_date is not null;")result_detailjumppage<- fetch(query_detailjumppage,n=-1)dbDisconnect(conn)head(result_homepage)t<-Sys.time()now_yesterday<-as.POSIXlt(t-24*60*60)now<-as.Date(now_yesterday,format="%Y-%m-%d")date_result<-strsplit(as.character(now),"-")title<-paste("08月18至",date_result[[1]][2],"月",date_result[[1]][3],"日",sep="")#theme(legend.position='none')参数是去掉右边日期标签p_detailtime<-ggplot(result_detailpage,aes(x=insert_date,y=avg_staytime,colour=insert_date))+geom_line(colour="black",position=pd,aes(group=1)) + geom_point(size=4,position=pd)+xlab("日期")+ylab("停留时间")p_detailtime+ggtitle(paste(title,"访问者每天每详情页停留时间",sep=""))+theme(panel.background = element_rect(fill = "transparent", color = "gray"))+  theme(axis.text.x=element_text(angle=90,color='black'))+theme(legend.position='none')# dev.off()#首页跳出率p_homejumppage<-ggplot(result_homejumppage,aes(x=insert_date,y=bounceRate,colour=insert_date))+geom_line(colour="black",position=pd,aes(group=1)) + geom_point(size=4,position=pd)+xlab("日期")+ylab("停留时间")p_homejumppage+ggtitle(paste(title,"访问者每天首页跳出率",sep=""))+theme(panel.background = element_rect(fill = "transparent", color = "gray"))+  theme(axis.text.x=element_text(angle=30,color='black'))# dev.off()#首页跳出率和总的图对比result_homejumppage_melt<-melt(result_homejumppage,id=c("insert_date"),measure=c(2:3),variable_name = "group",value.name="value")result_homejumppage_melt<-result_homejumppage_melt[order(result_homejumppage_melt$insert_date),]p_home_melt<-ggplot(result_homejumppage_melt,aes(x=insert_date,y=value,colour=group))+geom_point(size=4)+geom_line(aes(group=group))p_home_melt+xlab("日期")+ylab("pv")+ggtitle(paste(title,"首页每日uv和跳出率对比图",sep=""))+theme(panel.background = element_rect(fill = "transparent", color = "gray")) +  scale_colour_hue("渠道",labels=c("pv","bounce"))+theme(axis.text.x=element_text(angle=30,color='black'))# dev.off()#详情页跳出率p_detailjumppage<-ggplot(result_detailjumppage,aes(x=insert_date,y=bounceRate,colour=insert_date))+geom_line(colour="black",position=pd,aes(group=1)) + geom_point(size=4,position=pd)+xlab("日期")+ylab("停留时间")p_detailjumppage+ggtitle(paste(title,"每日详情页跳出率分析",sep=""))+theme(panel.background = element_rect(fill = "transparent", color = "gray"))+  theme(axis.text.x=element_text(angle=30,color='black'))# dev.off()#详情页跳出率和总的图对比result_detailjumppage_melt<-melt(result_detailjumppage,id=c("insert_date"),measure=c(2:3),variable_name = "group",value.name="value")result_detailjumppage_melt<-result_detailjumppage_melt[order(result_detailjumppage_melt$insert_date),]p_detail_melt<-ggplot(result_homejumppage_melt,aes(x=insert_date,y=value,colour=group))+geom_point(size=4)+geom_line(aes(group=group))p_detail_melt+xlab("日期")+ylab("pv")+ggtitle(paste(title,"详情页每日uv和跳出率对比图",sep=""))+theme(panel.background = element_rect(fill = "transparent", color = "gray")) +  +scale_colour_hue("渠道",labels=c("pv","bounce"))+theme(axis.text.x=element_text(angle=30,color='black'))# + geom_text(aes(label=value))# dev.off()