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问题描述
我有一个带有类型和值的df.我想在type中以x的顺序对它们进行排名，并计算出n行中的x值比(clumn pos)值高的其他行数.
I have a df with types and values. I want to rank them in order of x within type and give a count of how many other rows row n has higher value of x than (column pos).
例如
df <- data.frame(type = c("a","a","a","b","b","b"),x=c(1,77,1,34,1,8))
# for type a row 3 has a higher x than row 1 and 2 so has a pos value of 2
我可以这样:
library(plyr)
df <- data.frame(type = c("a","a","a","b","b","b"),x=c(1,77,1,34,1,8))
df <- ddply(df,.(type), function(x) x[with(x, order(x)) ,])
df <- ddply(df,.(type), transform, pos = (seq_along(x)-1) )
type x pos
1 a 1 0
2 a 1 1
3 a 77 2
4 b 1 0
5 b 8 1
6 b 34 2
但是这种方法没有考虑类型a第1行和第2行之间的联系.在联系具有例如相同值的情况下，获得输出的最简单方法是什么.
But this approach does not take into account ties between type a row 1 and 2. Whats the easiest way to get the output where ties have the same value e.g.
type x pos
1 a 1 0
2 a 1 0
3 a 77 2
4 b 1 0
5 b 8 1
6 b 34 2
推荐答案
ddply(df,.(type), transform, pos = rank(x,ties.method ="min")-1)
type x pos
1 a 1 0
2 a 77 2
3 a 1 0
4 b 34 2
5 b 1 0
6 b 8 1
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