删除具有负值的行

发布于 2024-10-03 07:09:46 字数 438 浏览 0 评论 0原文

在 RI 中，我尝试删除数据框（蚂蚁）中列标题“浊度”下具有负值的行。我已经尝试过

ants<-ants[ants$Turbidity<0,]

，但它返回以下错误：

Warning message:
In Ops.factor(ants$Turbidity, 0) : < not meaningful for factors

有什么想法可能是这样吗？也许我需要设置负值 NA 然后我删除所有 NA 吗？

任何想法非常感谢，谢谢！

@Joris：结果是

str(ants$Turbidity)

num [1:291] 0 0 -0.1 -0.2 -0.2 -0.5 0.1 -0.4 0 -0.2 ...

原文

In R I am trying to delete rows within a dataframe (ants) which have a negative value under the column heading Turbidity. I have tried

ants<-ants[ants$Turbidity<0,]

but it returns the following error:

Warning message:
In Ops.factor(ants$Turbidity, 0) : < not meaningful for factors

Any ideas why this may be? Perhaps I need to make the negative values
NA before I then delete all NAs?

Any ideas much appreciated, thank you!

@Joris: result is

str(ants$Turbidity)

num [1:291] 0 0 -0.1 -0.2 -0.2 -0.5 0.1 -0.4 0 -0.2 ...

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药祭#氼 2024-10-10 07:09:46

马雷克是对的，这是一个数据问题。现在，如果您使用 [as.numeric(ants$Turbidity] ，请小心，因为该值始终为正。它给出了因子级别（1 到 length(ants$Turbidity)），而不是数字因子。

试试这个：

tt <- as.numeric(as.character(ants$Turbidity))
which(!is.na(tt))

它将为您提供一个值首先不是数字的索引列表。这应该使您能够首先清理数据，

例如：

> Turbidity <- factor(c(1,2,3,4,5,6,7,8,9,0,"a"))
> tt <- as.numeric(as.character(Turbidity))
Warning message:
NAs introduced by coercion 
> which(is.na(tt))
[1] 11

您不应该使用 as.numeric(as.character(... )) 结构来转换有问题的数据，因为它会生成 NA，从而扰乱其余数据，例如：

> Turbidity[tt > 5]
[1] 6    7    8    9    <NA>
Levels: 0 1 2 3 4 5 6 7 8 9 a

Marek is right, it's a data problem. Now be careful if you use [as.numeric(ants$Turbidity] , as that one will always be positive. It gives the factor levels (1 to length(ants$Turbidity)), not the numeric factors.

Try this :

tt <- as.numeric(as.character(ants$Turbidity))
which(!is.na(tt))

It will give you a list of indices where the value was not numeric in the first place. This should enable you to first clean up your data.

eg:

> Turbidity <- factor(c(1,2,3,4,5,6,7,8,9,0,"a"))
> tt <- as.numeric(as.character(Turbidity))
Warning message:
NAs introduced by coercion 
> which(is.na(tt))
[1] 11

You shouldn't use the as.numeric(as.character(...)) structure to convert problematic data, as it will generate NA's that will mess with the rest. Eg:

> Turbidity[tt > 5]
[1] 6    7    8    9    <NA>
Levels: 0 1 2 3 4 5 6 7 8 9 a

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夕色琉璃 2024-10-10 07:09:46

读入数据后一定要进行summary(ants)，并检查是否得到了预期的结果。

它会为你省去很多问题。数字数据很容易神奇地转换为字符或因子类型。

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〃温暖了心ぐ 2024-10-10 07:09:46

编辑。我忘记了 as.character 转换（请参阅 Joris 评论）。

消息意味着 ants$Turbidit 是一个因素。时，它就会起作用。

ants <- ants[as.numeric(as.character(ants$Turbidity)) > 0,]

当您执行或

ants <- subset(ants, as.character(as.numeric(Turbidity)) > 0)

但真正的问题是您的数据还没有准备好进行分析。这种转换应该在一开始就完成。您应该小心，因为也可能存在非数字值。

EDIT. I forget about as.character conversion (see Joris comment).

Message mean that ants$Turbidit is a factor. It will work when you do

ants <- ants[as.numeric(as.character(ants$Turbidity)) > 0,]

ants <- subset(ants, as.character(as.numeric(Turbidity)) > 0)

But the real problem is that your data are not prepared to analysis. Such conversion should be done in the beginning. You should be careful cause there could be non-numeric values also.

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