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I have this dataframe (but let’s imagine it with many columns/variables)

```
df = data.frame(x = c(0,0,0,1,0),
y = c(1,1,1,0,0),
z = c(1,1,0,0,1))
```

I want to subset this dataset based on the condition that (x=1) and (y=0 or z = 0 or etc..)

I am already familiar with the basic function that works for small datasets, but I want a function that works for bigger datasets. Thanks

### >Solution :

You can make use of `Reduce()`

. The function `+`

basically works as an `OR`

operator since its result is `>0`

if it contains any `TRUE`

value.

Correspondingly, `*`

would work as an `AND`

since it only returns a value `>0`

if all cases are `TRUE`

.

```
df = data.frame(x = c(0,0,0,1,0),
y = c(1,1,1,0,0),
z = c(1,1,0,0,1))
nms <- names(df)
# take all variables except for `x`
nms_rel <- setdiff(nms, "x")
nms_rel
#> [1] "y" "z"
# filter all rows in which `x` is 1 AND any other variable is 0
df[df$x == 1 & Reduce(`+`, lapply(df[nms_rel], `==`, 0)) > 0, ]
#> x y z
#> 4 1 0 0
```