Question

我想过滤数据框以至少在至少2列中保留值大于5.5的行。

我知道dplyr函数filter(df,columnX>5.5)，但它一次只能容纳一列或几列。

df：

    structure(list(tumor = c(5.69857588735462, 5.14269655336569, 
15.5965461799242, 5.28949625542, 6.43237599127586, 5.21673785968077
), tumor = c(5.79729396999926, 5.10961482429376, 15.8339301491681, 
5.47321124082556, 6.0624492087845, 5.21740033243091), tumor = c(5.67184459054712, 
5.024088977993, 16.1659194908984, 5.20119456848026, 6.67441109230211, 
5.15023836750153), tumor = c(5.9616857066853, 5.23907758025991, 
15.2742729676712, 5.31827944648937, 6.47526325782951, 5.15926657492595
), tumor = c(5.75116456249489, 5.03195808382708, 16.0180448251626, 
5.36575242301428, 6.85603803194346, 5.18022831262029)), class = "data.frame", row.names = c("A_33_P3390097", 
"NM_178466", "GE_BrightCorner", "ENST00000396843", "NM_001166137", 
"DarkCorner"))

Answer 1

使用基数R rowSums的一种简单快捷的方法，我们在多个列中过滤那些值大于5.5的行。

df[rowSums(df > 5.5) > 1, ]

#                    tumor     tumor     tumor     tumor     tumor
#A_33_P3390097    5.698576  5.797294  5.671845  5.961686  5.751165
#GE_BrightCorner 15.596546 15.833930 16.165919 15.274273 16.018045
#NM_001166137     6.432376  6.062449  6.674411  6.475263  6.856038

Answer 2

这是使用@Ronak rowSums和dplyr

的另一种解决方案

library(dplyr)
df %>% filter(rowSums(.[1:5]>5.5)>=2)

PS：将此解决方案用于OP数据集之前，请使用colnames(df)<- paste0('X',1:5)更改列名称，以避免出现以下错误：

错误：列tumor，tumor，tumor，tumor必须具有唯一的名称

过滤具有X列数且值大于Y的行

2 个答案: