如何使用循环删除R中所有带有负值的行 [英] How to use a loop to delete all rows with negative values in R

问题描述

我是新手.我有一个笨拙的数据框，我想减少它，以便仅保留没有负数的观测值(行).这是我卡住的地方.每次都会创建一个空值，而不是修剪后的数据帧.

I am new to loops. I have an unwieldy data frame that I want to cut down so that only observations (rows) without negative numbers remain. Here is where I'm stuck. This creates a null value every time instead of a trimmed down data frame.

    mydata=for (i in names(df)) {
      subset(df, df[[ paste(i)]]>=0) 
    }

推荐答案

纯矢量化解决方案如何:

How about a purely vectorised solution:

DF[!rowSums(DF < 0), ]
#  ID Items Sequence
#1  1     D        1
#2  1     A        2
#5  2     B        2

---

数据

DF=structure(list(ID = c(1, 1, 1, -1, 2), Items = c("D", "A", "A", 
"A", "B"), Sequence = c(1, 2, -2, 1, 2)), .Names = c("ID", "Items", 
"Sequence"), row.names = c(NA, -5L), class = "data.frame")

---

说明

比较 DF<0 为data.frame中的每个值给出 TRUE/FALSE .

The comparison DF < 0 gives TRUE/FALSE for every value in the data.frame

DF < 0
#         ID Items Sequence
# [1,] FALSE FALSE    FALSE
# [2,] FALSE FALSE    FALSE
# [3,] FALSE FALSE     TRUE
# [4,]  TRUE FALSE    FALSE
# [5,] FALSE FALSE    FALSE

然后

rowSums()给我们每一行的总和(如 TRUE == 1，FALSE == 0 )

rowSums() then gives us the sum of each row (as TRUE == 1, FALSE == 0)

rowSums(DF<0)
# [1] 0 0 1 1 0

因此，我们可以使用此向量对data.frame进行子集化.但是，因为我们希望它的值都为正(即rowSums == 0)，所以我们取消了过滤器

So we can use this vector to subset our data.frame. But, because we want it where the values are all positive (i.e. rowSums == 0), we negate the filter

DF[!rowSums(DF < 0), ]

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