有三種方法  !is.na  , na.omit, complete.cases

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> d <- read.table("GWAS_s2.qassoc", header=T, stringsAsFactors=F)  

// 文件行數(shù)
> nrow(d)
[1] 431493

> d1 <- subset(d, select=c("CHR", "SNP", "BP", "P"))  

// 計算非NA 的行數(shù)

> num.bool <- complete.cases(d1)
> head(num.bool)
[1] FALSE  TRUE  TRUE FALSE  TRUE  TRUE  

> sum(num.bool) 
[1] 363836                                                                                                            
                                                                                                                            
> dn1 <- d1[which(!is.na(d1$P)),]                                                                                                                                                 
> nrow(dn1)                                                                                                                                                                       
[1] 363836

> dn2 <- na.omit(d1)
> nrow(dn2)                                                                                                                                                            
[1] 363836

> dn3 <-d1[complete.cases(d1[,4]),]                                                                                                                                               
> nrow(dn3)                                                                                                                                                                      
[1] 363836


> dn4 <-d1[complete.cases(d1),]                                                                                                                                                  
> nrow(dn4)
[1] 363836

方法三和方法四， 一個是根據(jù)第四列是否為NA判斷的， 一個是根據(jù)所有列。

分享文章：R語言移除缺失值NA
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