将行数据转换为二进制列
我试图将一列数据格式化为许多二进制列，最终用于关联规则挖掘。 使用for循环和简单的三元组矩阵已经取得了一些成功，但我不确定如何根据第一列中的级别进行聚合 - 类似于SQL中的group by语句。 我在下面提供了一个示例，尽管数据集小得多 - 如果成功，我的实际数据集将是4,200行3,902列，因此任何解决方案都需要可扩展。 任何建议或替代方法将不胜感激！
> data <- data.frame(a=c('sally','george','andy','sue','sue','sally','george'), b=c('green','yellow','green','yellow','purple','brown','purple'))
> data
a b
1 sally green
2 george yellow
3 andy green
4 sue yellow
5 sue purple
6 sally brown
7 george purple
x <- data[,1]
for(i in as.numeric(2:ncol(data)))
x <- cbind(x, simple_triplet_matrix(i=1:nrow(data), j=as.numeric(data[,i]),
v = rep(1,nrow(data)), dimnames = list(NULL, levels(data[,i]))) )
##Looks like this:
> as.matrix(x)
name brown green purple yellow
[1,] "sally" "0" "1" "0" "0"
[2,] "george" "0" "0" "0" "1"
[3,] "andy" "0" "1" "0" "0"
[4,] "sue" "0" "0" "0" "1"
[5,] "sue" "0" "0" "1" "0"
[6,] "sally" "1" "0" "0" "0" ##Need to aggregate by Name
##Would like it to look like this:
name brown green purple yellow
[1,] "sally" "1" "1" "0" "0"
[2,] "george" "0" "0" "0" "1"
[3,] "andy" "0" "1" "0" "0"
[4,] "sue" "0" "0" "1" "1"
这应该可以做到这一点：
## Get a contingency table of counts
X <- with(data, table(a,b))
## Massage it into the format you're wanting
cbind(name = rownames(X), apply(X, 2, as.character))
# name brown green purple yellow
# [1,] "andy" "0" "1" "0" "0"
# [2,] "george" "0" "0" "1" "1"
# [3,] "sally" "1" "1" "0" "0"
# [4,] "sue" "0" "0" "1" "1"