Discard value=1 across entire row

Question

Rows where all the values are 1. I wish to remove all such rows.

Related: [How to delete rows where all the columns are zero](https://stackoverflow.com/questions/20592611/how-to-delete-rows-where-all-the-columns-are-zero) — Henrik, Jul 31 '22 at 21:33

score 6 · Answer 1 · answered Jul 31 '22 at 15:40

6

Calling your data df,

df[rowSums(df == 1) < ncol(df), ]

rowSums(df == 1) is the count of 1s in each row. We keep rows where that is strictly less than the number of columns.

answered Jul 31 '22 at 15:40

Gregor Thomas

136,190
20
167
294

score 3 · Answer 2 · answered Jul 31 '22 at 15:44

For this we could use filter in combination with if_all:

library(dplyr)
df %>% 
  filter(if_all(everything(), ~ .x != 1))

  V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
1  0  0  0  0  0  0  0  0  0   0
2  0  0  0  0  0  0  0  0  0   0
3  0  0  0  0  0  0  0  0  0   0
4  0  0  0  0  0  0  0  0  0   0
5  0  0  0  0  0  0  0  0  0   0
6  0  0  0  0  0  0  0  0  0   0

data:

structure(list(V1 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), V2 = c(1L, 
0L, 0L, 0L, 0L, 1L, 0L, 0L), V3 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 
0L), V4 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), V5 = c(1L, 0L, 0L, 
0L, 0L, 1L, 0L, 0L), V6 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), 
    V7 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), V8 = c(1L, 0L, 0L, 
    0L, 0L, 1L, 0L, 0L), V9 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L
    ), V10 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L)), class = "data.frame", row.names = c(NA, 
-8L))

score 3 · Accepted Answer · answered Jul 31 '22 at 17:10

As these are 1s and 0s, an option is also with pmin

df[!do.call(pmin, df),]
 V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
2  0  0  0  0  0  0  0  0  0   0
3  0  0  0  0  0  0  0  0  0   0
4  0  0  0  0  0  0  0  0  0   0
5  0  0  0  0  0  0  0  0  0   0
7  0  0  0  0  0  0  0  0  0   0
8  0  0  0  0  0  0  0  0  0   0

Or using all with apply (less efficient)

df[!apply(df, 1, all),]
  V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
2  0  0  0  0  0  0  0  0  0   0
3  0  0  0  0  0  0  0  0  0   0
4  0  0  0  0  0  0  0  0  0   0
5  0  0  0  0  0  0  0  0  0   0
7  0  0  0  0  0  0  0  0  0   0
8  0  0  0  0  0  0  0  0  0   0

score 2 · Answer 4 · answered Jul 31 '22 at 18:59

Another base R option using lapply with Reduce like this:

df <- structure(list(V1 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), V2 = c(1L, 
                                                              0L, 0L, 0L, 0L, 1L, 0L, 0L), V3 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 
                                                                                                  0L), V4 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), V5 = c(1L, 0L, 0L, 
                                                                                                                                                      0L, 0L, 1L, 0L, 0L), V6 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), 
               V7 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L), V8 = c(1L, 0L, 0L, 
                                                              0L, 0L, 1L, 0L, 0L), V9 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L
                                                              ), V10 = c(1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L)), class = "data.frame", row.names = c(NA, 
                                                                                                                                               -8L))

df[!Reduce(`&`, lapply(df, `==`, 1)),]
#>   V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
#> 2  0  0  0  0  0  0  0  0  0   0
#> 3  0  0  0  0  0  0  0  0  0   0
#> 4  0  0  0  0  0  0  0  0  0   0
#> 5  0  0  0  0  0  0  0  0  0   0
#> 7  0  0  0  0  0  0  0  0  0   0
#> 8  0  0  0  0  0  0  0  0  0   0

^{Created on 2022-07-31 by the reprex package (v2.0.1)}

Data from @TarJae, Thanks!

Discard value=1 across entire row

4 Answers4