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伙计们，

从下面的df，我想计算归一化值@skew sk0。Sk0 是给定组的中心偏斜，每组只有一个 sk0。每组病例数为1个或更多。

group=c("g1", "g1", "g1", "g1", "g2", "g3", "g3", "g3", "g4", "g4")
skew=c("sk0", "sk1", "sk2", "sk3", "sk0", "sk2", "sk0", "sk1", "sk1", "sk0")
value=c(0.5, 0.3, 0.8, 1.0, 0.1, 0.4, 0.9, 0.7, 0.6, 0.2)
df = data.frame(group, skew, value)

所需的结果如下所示。相关组的 valueNorm=value/sk0。例如。行 1-> 4 属于组 g1。组 g1 的中心偏斜 sk0 位于第 1 行，其值为 0.5。因此，rowa 1-> 4 的值将除以 0.5 

      group skew  value         GroupSk0  valueNorm
1     g1    sk0   0.5           0.5       1.00
2     g1    sk1   0.3           0.5       0.60
3     g1    sk2   0.8           0.5       1.60
4     g1    sk3   1.0           0.5       2.00
5     g2    sk0   0.1           0.1       1.00
6     g3    sk2   0.4           0.9       0.44
7     g3    sk0   0.9           0.9       1.00
8     g3    sk1   0.7           0.9       0.78
9     g4    sk1   0.6           0.2       3.00
10    g4    sk0   0.2           0.2       1.00

谢谢你的帮助！

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1 回答 1

0

一个基本的 R 解决方案：

df <- merge(df, df[df$skew == "sk0", c("group", "value")], by.x = "group", by.y = "group", suffixes = c("", "GroupSK0"))
names(df) <- gsub("valueGroupSK0", "GroupSK0", names(df))
df$valueNorm <- df$value/df$GroupSK0
df
##    group skew value GroupSK0 valueNorm
## 1     g1  sk0   0.5      0.5 1.0000000
## 2     g1  sk1   0.3      0.5 0.6000000
## 3     g1  sk2   0.8      0.5 1.6000000
## 4     g1  sk3   1.0      0.5 2.0000000
## 5     g2  sk0   0.1      0.1 1.0000000
## 6     g3  sk2   0.4      0.9 0.4444444
## 7     g3  sk0   0.9      0.9 1.0000000
## 8     g3  sk1   0.7      0.9 0.7777778
## 9     g4  sk1   0.6      0.2 3.0000000
## 10    g4  sk0   0.2      0.2 1.0000000

data.table基于的解决方案：

DT <- data.table(df)
DT[, GroupSk0 := .SD[skew=='sk0', value], by = group]
DT[, valueNorm := value / GroupSk0]
DT
##     group skew value GroupSk0 valueNorm
##  1:    g1  sk0   0.5      0.5 1.0000000
##  2:    g1  sk1   0.3      0.5 0.6000000
##  3:    g1  sk2   0.8      0.5 1.6000000
##  4:    g1  sk3   1.0      0.5 2.0000000
##  5:    g2  sk0   0.1      0.1 1.0000000
##  6:    g3  sk2   0.4      0.9 0.4444444
##  7:    g3  sk0   0.9      0.9 1.0000000
##  8:    g3  sk1   0.7      0.9 0.7777778
##  9:    g4  sk1   0.6      0.2 3.0000000
## 10:    g4  sk0   0.2      0.2 1.0000000
于 2013-11-14T08:42:59.217 回答