Make condition when have equal values in a column

Note that k is the value of n, where Mode is equal to 1. However, in this case below, I have two values ​​where Mode is equal to 1, which is n = 2 and n = 4. So I would like to make some condition or something like that, that this will happen, considering the case where M1 is equal to 1, in this case, the first alternative, that is, n = 2. So k would be equal to 2.

df1<-structure(list(n= c(2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
    12, 13, 14, 15, 16, 17, 18, 19, 20), M1 = c(1L, 3L, 2L, 19L, 
    18L, 16L, 17L, 14L, 15L, 13L, 12L, 7L, 6L, 8L, 9L, 10L, 11L, 
    4L, 5L), M2 = c(1L, 3L, 2L, 19L, 18L, 16L, 17L, 14L, 
    15L, 13L, 12L, 7L, 6L, 8L, 9L, 10L, 11L, 4L, 5L), M3 = c(3L, 
    2L, 1L, 19L, 18L, 16L, 17L, 14L, 15L, 13L, 12L, 7L, 6L, 8L, 9L, 
    10L, 11L, 4L, 5L), M4 = c(2L, 3L, 1L, 19L, 18L, 16L, 
    17L, 14L, 15L, 13L, 12L, 7L, 6L, 8L, 9L, 10L, 11L, 4L, 5L), Mode = c(1, 
    3, 1, 19, 18, 16, 17, 14, 15, 13, 12, 7, 6, 8, 9, 10, 11, 4, 
    5), Percentage = c("50%", "75%", "50%", "100%", "100%", "100%", 
    "100%", "100%", "100%", "100%", "100%", "100%", "100%", "100%", 
    "100%", "100%", "100%", "100%", "100%")), class = "data.frame", row.names = c(NA, 
    -19L))

    n M1 M2 M3 M4 Mode Percentage
1   2  1  1  3  2    1        50%
2   3  3  3  2  3    3        75%
3   4  2  2  1  1    1        50%
4   5 19 19 19 19   19       100%
5   6 18 18 18 18   18       100%
6   7 16 16 16 16   16       100%
7   8 17 17 17 17   17       100%
8   9 14 14 14 14   14       100%
9  10 15 15 15 15   15       100%
10 11 13 13 13 13   13       100%
11 12 12 12 12 12   12       100%
12 13  7  7  7  7    7       100%
13 14  6  6  6  6    6       100%
14 15  8  8  8  8    8       100%
15 16  9  9  9  9    9       100%
16 17 10 10 10 10   10       100%
17 18 11 11 11 11   11       100%
18 19  4  4  4  4    4       100%
19 20  5  5  5  5    5       100%

k<-subset(df1, Mode==1)$n 

> k
[1] 2 4

>Solution :

match is a good way to find the first n for which Mode == 1

k = with(df1[order(df1$M1), ], n[match(1, Mode)])
k
# [1] 2

Change df1[order(df1$M1), ] to df1[order(df1$M1, df1$M2, df1$M3, ...), ] if you want to use additional columns as tie breakers.

If you need to generalize this to modes that are not first in the default sort order (like 1 is in your sample data), do it like this:

m = 1
k = with(df1[order(df1$M1 == m, decreasing = TRUE), ], n[match(m, Mode)])