library(haven)
# create labelled integer
x <- labelled(
  c(1, 2, 1, 3, 4, 1),
  c(Male = 1, Female = 2, Refused = 3, "N/A" = 4)
)
frq(x)
x <- labelled(
  c(1:3, tagged_na("a", "c", "z"), 4:1, 2:3),
  c("Agreement" = 1, "Disagreement" = 4, "First" = tagged_na("c"),
    "Refused" = tagged_na("a"), "Not home" = tagged_na("z"))
)
frq(x)
# in a pipe
data(efc)
library(dplyr)
efc %>%
  select(e42dep, e15relat, c172code) %>%
  frq()
# or:
# frq(efc, e42dep, e15relat, c172code)
# with grouped data frames, in a pipe
efc %>%
  group_by(e16sex, c172code) %>%
  frq(e16sex, c172code, e42dep)
# with select-helpers: all variables from the COPE-Index
# (which all have a "cop" in their name)
frq(efc, ~contains("cop"))
# all variables from column "c161sex" to column "c175empl"
frq(efc, c161sex:c175empl)
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