如果任何列与一组值中的一个匹配，则保留行 [英] Keeping rows if any column matches one of a set of values

问题描述

我有一个关于使用 R 进行子集化的简单问题；我想我很接近，但不能完全理解.基本上，我有 25 个感兴趣的列和大约 100 个值.我想保留其中一列中包含任何这些值的任何行.简单例子:

I have a simple question about subsetting using R; I think I am close but can't quite get it. Basically, I have 25 columns of interest and about 100 values. Any row that has ANY of those values in at one of the columns, I want to keep. Simple example:

Values <- c(1,2,5)

col1 <- c(2,6,8,1,3,5)
col2 <- c(1,4,5,9,0,0)
col3 <- c('dog', 'cat', 'cat', 'pig', 'chicken', 'cat')
df <- cbind.data.frame(col1, col2, col3)

df1 <- subset(df, col1%in%Values)

(请注意，第三列表示还有其他列，但我不需要将这些值与这些值匹配；保留的行仅取决于第 1 列和第 2 列).我知道在这个微不足道的情况下，我可以添加

(Note that the third column is to indicate that there are additional columns but I don't need to match the values to those; the rows retained only depend upon columns 1 and 2). I know that in this trivial case I could just add

| col2%in%Values

从第 2 列中获取额外的行，但对于 25 列，我不想为每一行添加 OR 语句.我试过了

to get the additional rows from column 2, but with 25 columns I don't want to add an OR statement for every single one. I tried

 file2011_test <- file2011[file2011[,9:33]%in%CO_codes] #real names of values

但是没有用.(是的，我知道这是混合子集类型；我发现 subset() 更容易理解，但我认为它不能帮助我满足我的需要?)

but it didn't work. (And yes I know this is mixing subsetting types; I find subset() easier to understand but I don't think it can help me with what I need?)

推荐答案

也许你可以试试:

df[Reduce(`|`, lapply(as.data.frame(df), function(x) x %in% Values)),]
#        col1 col2
#[1,]    2    1
#[2,]    8    5
#[3,]    1    9
#[4,]    5    0

或

 indx <- df %in% Values
 dim(indx) <- dim(df)
 df[!!rowSums(indx),]
 #        col1 col2
 # [1,]    2    1
 # [2,]    8    5
 # [3,]    1    9
 # [4,]    5    0

更新

使用新数据集

 df[Reduce(`|`, lapply(df[sapply(df, is.numeric)], function(x) x %in% Values)),]
 #     col1 col2 col3
 #1    2    1  dog
 #3    8    5  cat
 #4    1    9  pig
 #6    5    0  cat

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