我在这个SO线程中成功使用了答案 r-how-to-add-row-index-to-a-data-frame-based-on-combination-of-factors但我需要处理可以绑定两个(或更多)行的情况。
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", "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
在这个例子中,第1周,Matt Ryan和Matthew Stafford都是2,然后Peyton Manning将是4。
答案 0 :(得分:4)
您希望在rank
来电中使用ties.method="min"
功能ave
:
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
答案 1 :(得分:3)
假设您希望按季节和星期排名,可以使用dplyr
的{{1}}轻松完成此操作:
min_rank
答案 2 :(得分:2)
您可以使用frank
中较快的data.table
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