删除缺少x％的列/行 [英] Delete columns/rows with more than x% missing

问题描述

我要删除数据框中所有 NA s超过50％的列或行。

I want to delete all columns or rows with more than 50% NAs in a data frame.

这是我的解决方案：

# delete columns with more than 50% missings
miss <- c()
for(i in 1:ncol(data)) {
  if(length(which(is.na(data[,i]))) > 0.5*nrow(data)) miss <- append(miss,i) 
}
data2 <- data[,-miss]


# delete rows with more than 50% percent missing
miss2 <- c()
for(i in 1:nrow(data)) {
  if(length(which(is.na(data[i,]))) > 0.5*ncol(data)) miss2 <- append(miss2,i) 
}
data <- data[-miss,]

，但是我正在寻找更好/更快的解决方案。

but I'm looking for a nicer/faster solution.

我也希望得到 dplyr 解决方案

推荐答案

要删除具有一定数量NA的列，可以使用
colMeans（is.na（...））

To remove columns with some amount of NA, you can use colMeans(is.na(...))

## Some sample data
set.seed(0)
dat <- matrix(1:100, 10, 10)
dat[sample(1:100, 50)] <- NA
dat <- data.frame(dat)

## Remove columns with more than 50% NA
dat[, which(colMeans(!is.na(dat)) > 0.5)]

## Remove rows with more than 50% NA
dat[which(rowMeans(!is.na(dat)) > 0.5), ]

## Remove columns and rows with more than 50% NA
dat[which(rowMeans(!is.na(dat)) > 0.5), which(colMeans(!is.na(dat)) > 0.5)]

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