使用逻辑表达式向量来对R中的数据帧进行子集化

Question

I am trying to use a vector of logical expressions to subset a data frame. As a simple example, here is a data frame that I will subset using a logical expression. First, I'll type in the logical expression manually:

> dat <- data.frame(x = c(0,0,1,1), y = c(0,0,0,1), z = c(0,1,1,1))
> dat
  x y z
1 0 0 0
2 0 0 1
3 1 0 1
4 1 1 1
> subset(dat, x == 1)
  x y z
3 1 0 1
4 1 1 1

If I have a vector of logical expressions, how can I call from that vector and apply them to a subsetting method? Here is one way that doesn't work:

> criteria <- as.factor(c("x == 1", "y == 1", "y == 1 & z == 1"))
> subset(dat, criteria[1])
Error in subset.data.frame(dat, criteria[1]) : 'subset' must be logical

Any suggestions?

Answer 1

You can't make an atomic vector of vectors, so you can contain them in a list. Subsetting with [ , which is easier to program with than subset ,

dat <- data.frame(x = c(0,0,1,1), 
                  y = c(0,0,0,1), 
                  z = c(0,1,1,1))

indices <- list(dat$x == 1, 
                dat$y == 1, 
                dat$x == 1 & dat$z == 1)

str(indices)
#> List of 3
#>  $ : logi [1:4] FALSE FALSE TRUE TRUE
#>  $ : logi [1:4] FALSE FALSE FALSE TRUE
#>  $ : logi [1:4] FALSE FALSE TRUE TRUE

dat[indices[[1]], ]
#>   x y z
#> 3 1 0 1
#> 4 1 1 1

lapply(indices, function(i) dat[i, ])
#> [[1]]
#>   x y z
#> 3 1 0 1
#> 4 1 1 1
#> 
#> [[2]]
#>   x y z
#> 4 1 1 1
#> 
#> [[3]]
#>   x y z
#> 3 1 0 1
#> 4 1 1 1

Answer 2

We can use parse and eval to evaluate the condition as a vector of string.

criteria <- c("x == 1", "y == 1", "y == 1 & z == 1")

subset(dat, eval(parse(text = criteria)))
#   x y z
# 4 1 1 1

We can use index to select the element in the criteria vector to subset the data frame.

subset(dat, eval(parse(text = criteria[1])))
#   x y z
# 3 1 0 1
# 4 1 1 1

Answer 3

With a vector of logicals:

critearia <- dat$x == 1 & dat$y == 1 & dat$z == 1
subset(dat, critearia)

Directly:

subset(dat, x == 1 & y == 1 & z == 1)

With data.table :

library(data.table)
dat  <- as.data.table(dat)
dat[x == 1 & y == 1 & z == 1]