如何为选定列替换表中的NA值 [英] How to replace NA values in a table for selected columns

问题描述

关于替换NA值的文章很多.我知道可以用以下内容替换下表/框架中的NA:

There are a lot of posts about replacing NA values. I am aware that one could replace NAs in the following table/frame with the following:

x[is.na(x)]<-0

但是，如果我想将其限制为仅某些列怎么办?让我给你看一个例子.

But, what if I want to restrict it to only certain columns? Let's me show you an example.

首先，让我们从数据集开始.

First, let's start with a dataset.

set.seed(1234)
x <- data.frame(a=sample(c(1,2,NA), 10, replace=T),
                b=sample(c(1,2,NA), 10, replace=T), 
                c=sample(c(1:5,NA), 10, replace=T))

哪个给:

    a  b  c
1   1 NA  2
2   2  2  2
3   2  1  1
4   2 NA  1
5  NA  1  2
6   2 NA  5
7   1  1  4
8   1  1 NA
9   2  1  5
10  2  1  1

好，所以我只想将替换限制为列"a"和"b".我的尝试是:

Ok, so I only want to restrict the replacement to columns 'a' and 'b'. My attempt was:

x[is.na(x), 1:2]<-0

和:

x[is.na(x[1:2])]<-0

这不起作用.

我的data.table尝试(其中y<-data.table(x))显然永远不会起作用:

My data.table attempt, where y<-data.table(x), was obviously never going to work:

y[is.na(y[,list(a,b)]), ]

我想在is.na参数中传递列，但这显然行不通.

I want to pass columns inside the is.na argument but that obviously wouldn't work.

我想在data.frame和data.table中执行此操作.我的最终目标是将'a'和'b'中的1:2编码为0:1，同时保持'c'的原样，因为它不是逻辑变量.我有一堆专栏，所以我不想一个接一个地做.而且，我只想知道如何做到这一点.

I would like to do this in a data.frame and a data.table. My end goal is to recode the 1:2 to 0:1 in 'a' and 'b' while keeping 'c' the way it is, since it is not a logical variable. I have a bunch of columns so I don't want to do it one by one. And, I'd just like to know how to do this.

您有什么建议吗?

推荐答案

您可以这样做:

x[, 1:2][is.na(x[, 1:2])] <- 0

或更好的(IMHO)，请使用变量名称:

or better (IMHO), use the variable names:

x[c("a", "b")][is.na(x[c("a", "b")])] <- 0

在两种情况下，1:2或c("a", "b")都可以用预先定义的向量替换.

In both cases, 1:2 or c("a", "b") can be replaced by a pre-defined vector.

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