数据: -
df=data.frame(Name=c("John","John","Stacy","Stacy","Kat","Kat"),Year=c(2016,2015,2014,2016,2006,2006),Balance=c(100,150,65,75,150,10))
Name Year Balance
1 John 2016 100
2 John 2015 150
3 Stacy 2014 65
4 Stacy 2016 75
5 Kat 2006 150
6 Kat 2006 10
代码: -
aggregate(cbind(Year,Balance)~Name,data=df,FUN=max )
输出: -
Name Year Balance
1 John 2016 150
2 Kat 2006 150
3 Stacy 2016 75
我想使用Year和Balance这两个列来汇总/汇总上面的数据框。我使用基本功能聚合来执行此操作。我需要最近一年/最近一年的最大余额。在输出的第一行,约翰有最新的一年(2016),但是(2015)的余额,这不是我需要的,它应该输出100而不是150.我在哪里错了?
答案 0 :(得分:7)
aggregate
是一种糟糕的聚合工具。你可以让它工作,但我会这样做:
library(data.table)
setDT(df)[order(-Year, -Balance), .SD[1], by = Name]
# Name Year Balance
#1: John 2016 100
#2: Stacy 2016 75
#3: Kat 2006 150
答案 1 :(得分:3)
我建议使用库dplyr:
data.frame(Name=c("John","John","Stacy","Stacy","Kat","Kat"),
Year=c(2016,2015,2014,2016,2006,2006),
Balance=c(100,150,65,75,150,10)) %>% #create the dataframe
tbl_df() %>% #convert it to dplyr format
group_by(Name, Year) %>% #group it by Name and Year
summarise(maxBalance=max(Balance)) %>% # calculate the maximum for each group
group_by(Name) %>% # group the resulted dataframe by Name
top_n(1,maxBalance) # return only the first record of each group
答案 2 :(得分:3)
这是没有data.table包的另一种解决方案。
首先对数据框进行排序,
df <- df[order(-df$Year, -df$Balance),]
然后选择每个组中具有相同名称的第一个
df[!duplicated[df$Name],]