Question

我的数据集如下所示。我正在尝试编写R代码来转换它。这是自我网络，意味着第一列有两个人列出了他们的连接（在A1，A2和A3列中）。然后在第5到第10列中，我在A1，A2和A3中的人之间存在相互关系：

d <- data.frame(matrix(c("Steph","Ellen","John","Jim","Sam","Tom","Sally","Jane","Sam","Jane","Sally","NA","John","Jim","NA","Jane","Sam","NA","NA","Tom"),2,10))
names(d)<-c("Ego","A1","A2","A3","A1Connection1","A1Connection2","A2Connection1","A2Connection2","A3Connection1","A3Connection2")
d

我的挑战是采用第2到第10列，使它们看起来像这样

ReshapedData<-data.frame(matrix(c("John","John","Sam","Sam","Sally","Sally","Jim","Jim","Tom","Tom","Jane","Jane",
            "Sam","Sally","John","NA","Sam","NA","Jane","NA","Jim","Jane","NA","Tom"),12,2))
names(ReshapedData)<-c("Alter", "Alter_Alter")
ReshapedData

至少在这个阶段，我不需要自我的名字。关键是首先得到其他东西。到目前为止，我能想到的最好的事情是在每行中调换5-10列，然后使用rbind创建一个长列，然后使用A1，A2，A3中的变量列表创建一个长列。这必须是一些更简化的方法来管理它。

由于

的Bogdan

Answer 1

使用melt()包中的reshape函数并匹配具有公共索引的项目：

d <- data.frame(matrix(c("Steph","Ellen","John","Jim","Sam","Tom","Sally","Jane","Sam","Jane","Sally","NA","John","Jim","NA","Jane","Sam","NA","NA","Tom"),2,10))
names(d)<-c("Ego","A1","A2","A3","A1Connection1","A1Connection2","A2Connection1","A2Connection2","A3Connection1","A3Connection2")
d

library(reshape)

a <- melt(d,id.vars=NULL,measure.vars = c("A1","A2","A3"))
a$match <- as.character(paste(a[,1],rep(1:2)))
b <- melt(d,id.vars=NULL,measure.vars = c(5:dim(df)[2]))
b$match <- as.character(paste(gsub(pattern = ".*A([0-9]+).*",replacement = "A\\1",x = b[,1]),
                              rep(1:2)))

df.final <- data.frame(Alter=a$value[match(b$match,a$match)], Alter_Alter=b$value)

index <- 1:dim(df.final)[1]

index <- matrix(1:dim(df.final)[1], nrow = dim(df.final)[1]/2,byrow = T)

df.final <- df.final[as.vector(index),]

df.final
   Alter Alter_Alter
1   John         Sam
3   John       Sally
5    Sam        John
7    Sam          NA
9  Sally         Sam
11 Sally          NA
2    Jim        Jane
4    Jim          NA
6    Tom         Jim
8    Tom        Jane
10  Jane          NA
12  Jane         Tom

# Test

ReshapedData<-data.frame(matrix(c("John","John","Sam","Sam","Sally","Sally","Jim","Jim","Tom","Tom","Jane","Jane",
            "Sam","Sally","John","NA","Sam","NA","Jane","NA","Jim","Jane","NA","Tom"),12,2))
names(ReshapedData)<-c("Alter", "Alter_Alter")

df.final==ReshapedData

   Alter Alter_Alter
1   TRUE        TRUE
3   TRUE        TRUE
5   TRUE        TRUE
7   TRUE        TRUE
9   TRUE        TRUE
11  TRUE        TRUE
2   TRUE        TRUE
4   TRUE        TRUE
6   TRUE        TRUE
8   TRUE        TRUE
10  TRUE        TRUE
12  TRUE        TRUE

如何在R中重塑以下数据框？

1 个答案: