Question

我创建了以下数据框

Group <- c('A','A','A','B','B','B','B','C','C','C')
YearWeek <-c('201401','201401','201401','201401','201401','201401','201401','201401','201401','201401')
Score1 <- c(404,440,395,500,450,476,350,500,600,575)
Group <- c('A','A','A','B','B','B','B','C','C','C','A','A','A','B','B','B','B','C','C','C')
YearWeek <-c('201401','201401','201401','201401','201401','201401','201401','201401','201401','201401','201402','201402','201402','201402','201402','201402','201402','201402','201402','201402')
Score1 <-c(404,440,395,500,450,476,350,500,600,575,460,445,400,508,470,422,368,555,700,634)
employee <- c(1:20)
employ.data <- data.frame(employee, Group, YearWeek, Score1)

我想按“YearWeek”的每个级别计算组'A'（我的对照组）的平均值，并根据相同的YearWeek从每个员工（包括对照组员工）的Score1中减去它，并添加结果将数据框作为新变量“差异”

我首先尝试获取组'A'（对照组员工）的平均值，但收到以下错误：

CTRLScore <- as.data.frame(employ.data[, j=list(mean(Score1),by = list(YearWeek,Group,"A"))]) 
Error in .subset(x, j) : invalid subscript type 'list'

另外：警告信息：

In `[.data.frame`(employ.data, , j = list(mean(Score1), by = list(YearWeek,  :
named arguments other than 'drop' are discouraged

Answer 1

这是我认为可行的策略。

首先计算每个YearWeek的A组平均值

ctrlmeans <- with(subset(employ.data, Group=="A"), tapply(Score1, YearWeek, mean))

返回命名向量。然后我们可以使用data.frame的YearWeek列来查看该表以减去平均值。我们可以用

做到这一点

Difference <- employ.data$Score1-ctrlmeans[employ.data$YearWeek]

然后将其添加回data.frame

employ.data$Difference <- Difference

Answer 2

这似乎对我有用：

library(reshape)
melted<-melt(employ.data)
casted<-cast(x,formula=Group+YearWeek~variable,subset=variable=="Score1",fun.aggregate=mean)

#Print Out 
casted

# Holder variables
addColumn <- NULL
i<-0

for(i in 1:nrow(employ.data))
{
  score <- employ.data[i,]$Score1
  group<-employ.data[i,]$Group
  yearWeek <- employ.data[i,]$YearWeek
  sub<-casted[casted$Group %in% group,]
  meanScore<-sub[sub$YearWeek %in% yearWeek,]$Score1
  addColumn <- c(addColumn,score-meanScore)
}

# Combine
cbind(employ.data,addColumn)

Answer 3

@ MrFlick答案的dplyr变体：

# calculating the means
ctrlmeans <- with(subset(employ.data, Group=="A"), tapply(Score1, YearWeek, mean))

# adding the difference to the data.frame
require(dplyr)
employ.data <- employ.data %.%
  mutate(Difference = Score1 - ctrlmeans[employ.data$YearWeek])

按两个单独的分类变量的级别进行汇总统计

3 个答案: