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How to subset a large dataframe using many conditions for many variables in a simple way?

October 12, 2022

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