Dropping factors which levels have observations smaller than a specific value-R

Question

Let I have such data frame(df1) with factors:

factor1  factor2  factor3
-------  -------  -------
d        a         x
d        a         x
b        a                


        

Answer 1

We could use Filter

Filter(function(x) min(nlevels(x))>2, df1)

(based on the results in one of the upvoted posts)

Or it could be also

Filter(function(x) min(tabulate(x))>2, df1)

Answer 2

is that what you want?

df <- data.frame(col1=rep(letters[1:4], each=3),
                 col2=rep(letters[1:2], each=6),
                 col3=rep(letters[1:3], each=4))

ddf[, sapply(df, function(x) min(nlevels(x)) > 2)]

Answer 3

You could try using lapply and table:

df1[, lapply(c(1,2,3), FUN = function(x) min(table(df1[,x]))) >= 3]

and, a little more generic:

df1[, lapply(1:ncol(df1), FUN = function(x) min(table(df1[,x]))) >= 3]

Answer 4

I would create a quick helper function that checks how many unique instances of each level exist with a quick call to table() -- look at table(df$fac1) to see how this works. Note this isn't very robust, but should get you started:

df <- data.frame(fac1 = factor(c("d", "d", "b", "b", "b", "c", "c", "c", "c")),
                 fac2 = factor(c("a", "a", "a", "c", "c", "c", "n", "n", "n")),
                 fac3 = factor(c(rep("x", 4), rep("y", 5))),
                 other = 1:9)

at_least_three_instances <- function(column) {
  if (is.factor(column)) {
    if (min(table(column)) > 2) {
      return(TRUE)
    } else {
      return(FALSE)
    }
  } else {
    return(TRUE)
  }
}

df[unlist(lapply(df, at_least_three_instances))]