如何提取方差最大的 100 列？

Question

我得到了一个包含 4983 行和 369 列的列表对象。每一列都是一个不同的样本，每一行都是该样本的一个值。

现在我需要提取其行中方差最大的 100 个样本，但我不知道该怎么做 ..

Answer 1

仅使用 20 行和 5 列的示例，返回具有最高可变性的两列：

# some example data:
dat <- data.frame(var1 = rnorm(n=20, mean = 1, sd=4),
                  var2 = rnorm(n=20, mean = 1, sd=3),
                  var3 = rnorm(n=20, mean = 1, sd=2),
                  var4 = rnorm(n=20, mean = 1, sd=8),
                  var5 = rnorm(n=20, mean = 1, sd=6))
head(dat)

# calculate variance per column
variances <- apply(X=dat, MARGIN=2, FUN=var)

# sort variance, grab index of the first 2
sorted <- sort(variances, decreasing=TRUE, index.return=TRUE)$ix[1:2] # replace 2 with 100 ...

# use that to subset the original data
dat.highvariance <- dat[, sorted]
dat.highvariance

Answer 2

我的代码与 "Where's my towel" 完全相同，但使用 Rfast 包更快

# some example data:
dat <- data.frame(var1 = rnorm(n=20, mean = 1, sd=4),
              var2 = rnorm(n=20, mean = 1, sd=3),
              var3 = rnorm(n=20, mean = 1, sd=2),
              var4 = rnorm(n=20, mean = 1, sd=8),
              var5 = rnorm(n=20, mean = 1, sd=6))

MaxVars_R<-function(dat,n){
    head(dat)

    # calculate variance per column
    variances <- apply(X=dat, MARGIN=2, FUN=var)

    # sort variance, grab index of the first 2
    sorted <- sort(variances, decreasing=TRUE, index.return=TRUE)$ix[1:n]

    # use that to subset the original data
    dat.highvariance <- dat[, sorted]
    dat.highvariance
}

MaxVars<-function(dat,n,parallel = FALSE){
    x<-Rfast::data.frame.to_matrix(dat)
    variances<-Rfast::colVars(x,parallel = parallel)
    indices<-Rfast::Order(variances,descending = TRUE,partial = n)[1:n]
    dat[,indices]
}

all.equal(MaxVars(dat,2),MaxVars_R(dat,2))

如何提取方差最大的 100 列？

How do I extract the 100 columns with the highest variance?

r

list

variance