资深篮球评论员苏群老师的公众号今天分享的文章是《威少投篮惨不忍睹，但他把MVP给乔治》，其中用表格形式展示了威少爷11年职业生涯出手距离投篮命中率和出手距离所占比重的变化，个人认为这类数据用折线图看起来更为直观，本文记录整理苏群老师文章中用到的数据后使用ggplot2制作折线图的代码
数据整理
不同出手距离的命中率
不同出手距离比重
绘图
1、 出手距离与命中率
library(ggplot2)
library(reshape2)
df1<-read.table("clipboard",header=T)
colnames(df1)<-c("Season","0~1","1~3","3~5","5~7","7~")
mydata1<-melt(df1,id.vars = "Season",variable.name = "shooting_distance",value.name = "Percentage")
ggplot(mydata1,aes(x=Season,y=Percentage,group=shooting_distance,color=shooting_distance))+
geom_line()+scale_color_brewer(name="Shooting Distance(m)",palette="Set1")+
geom_point()+theme_bw()+labs(x="")+
scale_y_continuous(breaks = seq(0,1000,by=100),labels=seq(0,100,by=10),
limits = c(0,1000))+
theme(legend.key=element_blank(),
legend.background = element_blank(),
axis.text.x = element_text(angle=90,vjust=0.5))
从上图可以看出1-5米内出手命中率近两个赛季明显下降，1米内出手命中率生涯最佳
2、出手距离比例
df2<-read.table("clipboard",header=T)
df2
mydata2<-melt(df2,id.vars = "Season",variable.name = "shooting_distance",value.name = "Proportion")
mydata2$shooting_distance<-factor(mydata2$shooting_distance,levels=c("E","D","C","B","A"))
ggplot(mydata2,aes(x=Season,y=Proportion,fill=shooting_distance))+
geom_bar(stat="identity")+theme_bw()+
scale_fill_brewer(name="Shooting Distance(m)",palette="Set1",
breaks=c("E","D","C","B","A"),
labels=c("7~","5~7","3~5","1~3","~1"))+
scale_y_continuous(breaks = seq(0,1000,by=100),labels=seq(0,10,by=1),
limits = c(0,1000))+
theme(axis.title = element_blank(),
axis.text.x = element_text(angle=90,vjust=0.5))
由上图可以看出，威少本赛季较上个赛季的进攻方式的变化：略微增加了三分球，减少了长两分，其他没有明显变化
参考文献
R语言ggplot2包画折线图
Legends(ggplot2)
ggplot2 legend : Easy steps to change the position and the appearance of a graph legend in R software