查找最大值对应的索引

Question

我发现这个线程Find rows in dataframe with maximum values grouped by values in another column 已经讨论了其中一个解决方案。我正在使用此解决方案以递归方式查找最大数量的行索引。但是，我的解决方案非常难看——非常程序化而不是矢量化。

这是我的虚拟数据：

dput(Data)

structure(list(Order_Year = c(1999, 1999, 1999, 1999, 1999, 1999, 
1999, 2000, 2000, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2002, 
2002, 2002, 2002), Ship_Year = c(1997, 1998, 1999, 2000, 2001, 
2002, NA, 1997, NA, 1997, 1998, 1999, 2000, 2001, 2002, NA, 1997, 
1998, 1999, 2000), Yen = c(202598.2, 0, 0, 0, 0, 0, 2365901.62, 
627206.75998, 531087.43, 122167.02, 143855.55, 0, 0, 0, 0, 53650.389998, 
17708416.3198, 98196.4, 31389, 0), Units = c(37, 1, 8, 5, 8, 
8, 730, 99, 91, 195, 259, 4, 1, 3, 3, 53, 3844, 142, 63, 27)), .Names = c("Order_Year", 
"Ship_Year", "Yen", "Units"), row.names = c(NA, 20L), class = "data.frame")

我想找出给定Order_Year 的Yen 和Units 最大的Ship_Year。

这是我尝试过的：

a<-do.call("rbind", by(Data, Data$Order_Year, function(x) x[which.max(x$Yen), ]))
rownames(a)<-NULL
a$Yen<-NULL
a$Units<-NULL
#a has Ship_Year for which Yen is max for a given Order_Year
names(a)[2]<-"by.Yen" 
#Now I'd find max year by units
b<-do.call("rbind", by(Data, Data$Order_Year, function(x) x[which.max(x$Units), ]))
rownames(b)<-NULL
b$Yen<-NULL
b$Units<-NULL
#b has Ship_Year for which Units is max for a given Order_Year
names(b)[2]<-"by.Qty"
c<-a %>% left_join(b)

预期的输出是：

c
  Order_Year by.Yen by.Qty
1       1999     NA     NA
2       2000   1997   1997
3       2001   1998   1998
4       2002   1997   1997

虽然我得到了预期的输出，但上面的方法非常笨拙。有没有更好的方法来处理这个问题？

Answer 1

which.max 与 dplyr 分组效果很好：

library(dplyr)

Data %>% group_by(Order_Year) %>% 
    summarise(by.Yen = Ship_Year[which.max(Yen)], 
              by.Units = Ship_Year[which.max(Units)])

## # A tibble: 4 × 3
##   Order_Year by.Yen by.Units
##        <dbl>  <dbl>    <dbl>
## 1       1999     NA       NA
## 2       2000   1997     1997
## 3       2001   1998     1998
## 4       2002   1997     1997

Answer 2

使用基础 R

a1 <- with(df1,
           by(data    = df1,
              INDICES = Order_Year, 
              FUN     = function(x) list(Yen   = x$Ship_Year[which.max(x$Yen)],
                                         Units = x$Ship_Year[which.max(x$Units)])))

do.call("rbind", lapply(a1, function(x) data.frame(x)))
#       Yen Units
# 1999   NA    NA
# 2000 1997  1997
# 2001 1998  1998
# 2002 1997  1997

数据：

df1 <- structure(list(Order_Year = c(1999, 1999, 1999, 1999, 1999, 1999, 1999,
                                     2000, 2000, 2001, 2001, 2001, 2001, 2001,
                                     2001, 2001, 2002, 2002, 2002, 2002),
                      Ship_Year = c(1997, 1998, 1999, 2000, 2001, 2002, NA, 
                                    1997, NA, 1997, 1998, 1999, 2000, 2001, 
                                    2002, NA, 1997, 1998, 1999, 2000),
                      Yen = c(202598.2, 0, 0, 0, 0, 0, 2365901.62, 627206.75998, 
                              531087.43, 122167.02, 143855.55, 0, 0, 0, 0,
                              53650.389998, 17708416.3198, 98196.4, 31389, 0), 
                      Units = c(37, 1, 8, 5, 8, 8, 730, 99, 91, 195, 259, 4,
                                1, 3, 3, 53, 3844, 142, 63, 27)), 
                 .Names = c("Order_Year", "Ship_Year", "Yen", "Units"), 
                 row.names = c(NA, 20L),
                 class = "data.frame")

Answer 3

我们可以使用data.table。将'data.frame'转换为'data.table'（setDT(Data)），按'Order_Year'分组，我们得到'Yen'最大值的索引，'Units'用match，子集对应的值'Ship_Year' 基于该索引返回汇总输出

library(data.table)
setDT(Data)[,.(by.Yen = Ship_Year[match(max(Yen), Yen)],
        by.Units = Ship_Year[match(max(Units), Units)]) , Order_Year]
#   Order_Year by.Yen by.Units
#1:       1999     NA       NA
#2:       2000   1997     1997
#3:       2001   1998     1998
#4:       2002   1997     1997

---

如果有很多列，我们可以在.SDcols中指定感兴趣的列，按'Order_Year'分组，循环遍历Data.table的子集（.SD）得到索引最大值，unlistlist 输出，基于该索引对“Ship_Year”进行子集化，转换为list (as.list) 并将列的名称设置为“by.Yen”和“by。单位'

setnames(setDT(Data)[,  as.list(Ship_Year[unlist(lapply(.SD, 
  which.max))]), Order_Year, .SDcols = c("Yen", "Units")], 
                2:3, c("by.Yen", "by.Units"))[]
#    Order_Year by.Yen by.Units
#1:       1999     NA       NA
#2:       2000   1997     1997
#3:       2001   1998     1998
#4:       2002   1997     1997