1. R语言运行效率分析(8)

方法8： 采用 ddply 语句

1: 自定义函数

Month_name_ddply<-function(month){
  Month<-as.data.frame(month)
  Month$ID<-1:nrow(Month)
  df<-ddply(Month,.(month),function(x){mutate(x,month_name=month.abb[month])})
  Month_name<-arrange(df,ID)
  return(Month_name[,-2])
}
Season_name_ddply<-function(month){
  Month<-as.data.frame(month)
  Month$ID<-1:nrow(Month)
  df<-ddply(Month,.(month),function(x){mutate(x,season_name=c("Winter","Winter","Spring","Spring","Spring","Summer","Summer","Summer","Autumn","Autumn","Autumn","Winter")[month])})
  Season_name<-arrange(df,ID)
  return(Season_name[,-2])
  
}
result_ddply<-function(month){
  Month_name_ddply<-Month_name_ddply(month)# months' names
  Season_name_ddply<-Season_name_ddply(month) #seasons' names
  df<-data.frame(month,Month_name_ddply,Season_name_ddply)
  return(df)
}

2: 调用函数进行运算

month<-month_digital(10)
microbenchmark::microbenchmark(Month_name_ddply(month))
microbenchmark::microbenchmark(Season_name_ddply(month))
microbenchmark::microbenchmark(result_ddply(month))

Unit: milliseconds
                    expr      min       lq     mean   median       uq      max
 Month_name_ddply(month) 8.760018 8.888448 9.836038 8.980004 9.211437 21.86194
 neval
   100
Unit: milliseconds
                     expr      min       lq     mean   median       uq      max
 Season_name_ddply(month) 8.731989 8.853146 9.877732 8.976706 9.128971 25.45839
 neval
   100
Unit: milliseconds
                expr      min       lq     mean   median       uq      max
 result_ddply(month) 17.98596 18.18733 19.24074 18.27565 18.64888 33.03697
 neval
   100

(未完！待续……)