如何查找数据框中各组之间共享的值？ [英] How to find values shared between groups in a data frame?

问题描述

我有一个整洁的data.frame，有两列： exp 和 val 。我想查找所有不同实验之间共享的 val 值。

I have a tidy data.frame with two columns: exp and val. I want to find which values of val are shared among all different experiments.

df <- data.frame(exp = c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'C', 'C', 'C', 'C'),
                 val = c(10, 20, 15, 10, 10, 15, 99, 2, 15, 20, 10, 4))
df

   exp val
1    A  10
2    A  20
3    A  15
4    A  10
5    B  10
6    B  15
7    B  99
8    B   2
9    C  15
10   C  20
11   C  10
12   C   4

预期结果可以是值的向量：

Expected result could be either a vector of values:

10, 15

或数据框上的一列，告知是否共享价值：

or a column on the data frame telling if that value is shared:

   exp     val shared
   <fct> <dbl> <lgl> 
 1 A        10 TRUE  
 2 A        20 FALSE 
 3 A        15 TRUE  
 4 A        10 TRUE  
 5 B        10 TRUE  
 6 B        15 TRUE  
 7 B        99 FALSE 
 8 B         2 FALSE 
 9 C        15 TRUE  
10 C        20 FALSE 
11 C        10 TRUE  
12 C         4 FALSE 

我能够找到答案（请参阅下面的自我答案），但这似乎是一个足够普遍的问题， 必须比我提出的真正棘手的解决方案更好。

I was able to find an answer (see the self-answer below) but this seems like a common enough question that there must be a better way than the really hacky solution I cam up with.

我试图在中解决此问题dplyr 因为这是我所熟悉的，但是我对任何一种解决方案都感兴趣。

I tried to solve this problem in dplyr since that's what I'm familiar with, but I'm interested in any kind of solution.

推荐答案

或者您可以按 val 分组，然后检查该<$ c $的独立 exp 的数量c> val 等于不同的 exp 的数据帧级别数：

Or you can group by val and then check whether the number of distinct exp for that val is equal to the data frame level number of distinct exp:

df %>% 
    group_by(val) %>% 
    mutate(shared = n_distinct(exp) == n_distinct(.$exp))
    # notice the first exp refers to exp for each group while .$exp refers 
    # to the overall exp column in the data frame

# A tibble: 12 x 3
# Groups:   val [6]
#   exp     val shared
#   <fct> <dbl> <lgl> 
# 1 A        10 TRUE  
# 2 A        20 FALSE 
# 3 A        15 TRUE  
# 4 A        10 TRUE  
# 5 B        10 TRUE  
# 6 B        15 TRUE  
# 7 B        99 FALSE 
# 8 B         2 FALSE 
# 9 C        15 TRUE  
#10 C        20 FALSE 
#11 C        10 TRUE  
#12 C         4 FALSE

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