时间戳

首页 > 解决方案 > 删除 R 中至少包含一个负值的所有行

r - 删除 R 中至少包含一个负值的所有行

问题描述

我不想删除我能做的所有负面元素。但是，我想删除所有行，即使它在我的数据框中只包含一个负值。

> head(kosoyCorrected)
       BER1_EW    BER2_EW      BER3_EW    BER4_EW      BER5_EW     BER6_EW
1  7.087613184 7.09928796  7.087194381 6.96315939  7.086734346  7.09934523
2  4.599450934 3.89325300  4.160360141 4.81419817  4.090161726  4.34070903
3  0.100477184 0.02351617 -0.001589346 0.01072809  0.023073244 -0.06953596
4  0.132531627 0.09994992  0.123564389 0.13849246  0.217604484  0.09164854
5 -0.005220038 0.07117798  0.133075865 0.05525490 -0.003944601  0.10597363
6  0.107204375 0.11755171  0.060868101 0.14361525  0.109494893  0.13081894

例如，在这里，我想删除整个第 3 行和第 5 行，而不仅仅是这些行中的 4 个负值。

提前致谢！

标签： rfiltering

解决方案

我们可以使用rowSums创建一个逻辑向量来对行进行子集化

subset(kosoyCorrected, !rowSums(kosoyCorrected < 0))
#  BER1_EW    BER2_EW   BER3_EW   BER4_EW   BER5_EW    BER6_EW
#1 7.0876132 7.09928796 7.0871944 6.9631594 7.0867343 7.09934523
#2 4.5994509 3.89325300 4.1603601 4.8141982 4.0901617 4.34070903
#4 0.1325316 0.09994992 0.1235644 0.1384925 0.2176045 0.09164854
#6 0.1072044 0.11755171 0.0608681 0.1436152 0.1094949 0.13081894

或者另一种选择是Reduce

subset(kosoyCorrected, Reduce(`&`, lapply(kosoyCorrected, `>`, 0)))

dplyr或带有的矢量化选项filter_all

library(dplyr)
kosoyCorrected %>%
       filter_all( all_vars(. > 0))
#    BER1_EW    BER2_EW   BER3_EW   BER4_EW   BER5_EW    BER6_EW
#1 7.0876132 7.09928796 7.0871944 6.9631594 7.0867343 7.09934523
#2 4.5994509 3.89325300 4.1603601 4.8141982 4.0901617 4.34070903
#4 0.1325316 0.09994992 0.1235644 0.1384925 0.2176045 0.09164854
#6 0.1072044 0.11755171 0.0608681 0.1436152 0.1094949 0.13081894

或在较新的版本中across

kosoyCorrected %>% 
        filter(across(everything(), ~ . > 0))

数据

kosoyCorrected <- structure(list(BER1_EW = c(7.087613184, 4.599450934, 0.100477184, 
0.132531627, -0.005220038, 0.107204375), BER2_EW = c(7.09928796, 
3.893253, 0.02351617, 0.09994992, 0.07117798, 0.11755171), BER3_EW = c(7.087194381, 
4.160360141, -0.001589346, 0.123564389, 0.133075865, 0.060868101
), BER4_EW = c(6.96315939, 4.81419817, 0.01072809, 0.13849246, 
0.0552549, 0.14361525), BER5_EW = c(7.086734346, 4.090161726, 
0.023073244, 0.217604484, -0.003944601, 0.109494893), BER6_EW = c(7.09934523, 
4.34070903, -0.06953596, 0.09164854, 0.10597363, 0.13081894)), 
class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6"))

推荐阅读