R-将行索引添加到数据帧,但以最小秩处理关联
我成功地在这条线索中使用了答案 但我需要处理两(或更多)行可以绑定的情况R-将行索引添加到数据帧,但以最小秩处理关联,r,data-manipulation,R,Data Manipulation,我成功地在这条线索中使用了答案 但我需要处理两(或更多)行可以绑定的情况 df <- data.frame( season = c(2014,2014,2014,2014,2014,2014, 2014, 2014), week = c(1,1,1,1,2,2,2,2), player.name = c("Matt Ryan","Peyton Manning","Cam Newton","Matthew Stafford","Carson Palmer","Andrew Luck",
df <- data.frame(
season = c(2014,2014,2014,2014,2014,2014, 2014, 2014),
week = c(1,1,1,1,2,2,2,2),
player.name = c("Matt Ryan","Peyton Manning","Cam Newton","Matthew Stafford","Carson Palmer","Andrew Luck", "Aaron Rodgers", "Chad Henne"),
fant.pts.passing = c(28,19,29,28,18,22,29,22)
)
df <- df[order(-df$season, df$week, -df$fant.pts.passing),]
df$Index <- ave( 1:nrow(df), df$season, df$week, FUN=function(x) 1:length(x) )
df
df假设您希望按季节和周排名,这可以通过dplyr
的minu-rank
轻松实现:
library(dplyr)
df %>% group_by(season, week) %>%
mutate(indx = min_rank(desc(fant.pts.passing)))
# season week player.name fant.pts.passing Index indx
# 1 2014 1 Cam Newton 29 1 1
# 2 2014 1 Matt Ryan 28 2 2
# 3 2014 1 Matthew Stafford 28 3 2
# 4 2014 1 Peyton Manning 19 4 4
# 5 2014 2 Aaron Rodgers 29 1 1
# 6 2014 2 Andrew Luck 22 2 2
# 7 2014 2 Chad Henne 22 3 2
# 8 2014 2 Carson Palmer 18 4 4
您可能希望在ave
调用中使用带有ties.method=“min”
的rank
函数:
df$Index <- ave(-df$fant.pts.passing, df$season, df$week,
FUN=function(x) rank(x, ties.method="min"))
df
# season week player.name fant.pts.passing Index
# 3 2014 1 Cam Newton 29 1
# 1 2014 1 Matt Ryan 28 2
# 4 2014 1 Matthew Stafford 28 2
# 2 2014 1 Peyton Manning 19 4
# 7 2014 2 Aaron Rodgers 29 1
# 6 2014 2 Andrew Luck 22 2
# 8 2014 2 Chad Henne 22 2
# 5 2014 2 Carson Palmer 18 4
df$Index您可以使用数据表中更快的frank
,并通过引用分配(:=
)列
library(data.table)#v1.9.5+
setDT(df)[, indx := frank(-fant.pts.passing, ties.method='min'), .(season, week)]
# season week player.name fant.pts.passing indx
#1: 2014 1 Cam Newton 29 1
#2: 2014 1 Matt Ryan 28 2
#3: 2014 1 Matthew Stafford 28 2
#4: 2014 1 Peyton Manning 19 4
#5: 2014 2 Aaron Rodgers 29 1
#6: 2014 2 Andrew Luck 22 2
#7: 2014 2 Chad Henne 22 2
#8: 2014 2 Carson Palmer 18 4
谢谢我还没有深入研究dplr(我知道),但它在我的任务清单上。谢谢@akrun,但是数据集都<50k,所以速度不是问题。但很高兴知道未来的项目。