基于多列的具有独特案例的子集 [英] Subset with unique cases, based on multiple columns

问题描述

我想对数据框进行子集化，以仅包含具有三列独特组合的行.我的情况类似于 this 问题，但我也想保留数据中的其他列.这是我的例子:

I'd like to subset a dataframe to include only rows that have unique combinations of three columns. My situation is similar to the one presented in this question, but I'd like to preserve the other columns in my data as well. Here's my example:

> df
  v1  v2  v3   v4  v5
1  7   1   A  100  98 
2  7   2   A   98  97
3  8   1   C   NA  80
4  8   1   C   78  75
5  8   1   C   50  62
6  9   3   C   75  75

请求的输出将是这样的，我正在寻找基于 v1、v2 和 v3 的独特案例:

The requested output would be something like this, where I'm looking for unique cases based on v1, v2, and v3 only:

> df.new
  v1  v2  v3   v4  v5
1  7   1   A  100  98 
2  7   2   A   98  97
3  8   1   C   NA  80
6  9   3   C   75  75

如果我能恢复非唯一行，那就太好了:

If I could recover the non-unique rows that would be great too:

> df.dupes
  v1  v2  v3   v4  v5
3  8   1   C   NA  80
4  8   1   C   78  75
5  8   1   C   50  62

我在 sql 中看到了一个有关如何执行此操作的相关问题(here)，但我无法在 R 中得到它.我确信这很简单，但是搞砸了 unique() 和 subset() 并没有取得成果.提前致谢.

I saw a related question for how to do this in sql (here), but I can't get this in R. I'm sure it's simple but messing with unique() and subset() hasn't been fruitful. Thanks in advance.

推荐答案

您可以使用 duplicated() 函数来查找唯一组合:

You can use the duplicated() function to find the unique combinations:

> df[!duplicated(df[1:3]),]
  v1 v2 v3  v4 v5
1  7  1  A 100 98
2  7  2  A  98 97
3  8  1  C  NA 80
6  9  3  C  75 75

要仅获取重复项，您可以双向检查:

To get only the duplicates, you can check it in both directions:

> df[duplicated(df[1:3]) | duplicated(df[1:3], fromLast=TRUE),]
  v1 v2 v3 v4 v5
3  8  1  C NA 80
4  8  1  C 78 75
5  8  1  C 50 62

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