jwutil (version 1.2.3)

binary_col_names: names of fields which are numeric, binary or combinations thereof

Description

Doesn't make any allowance for factors.

Usage

binary_col_names(x, invert = FALSE)
two_cat_col_names(x, invert = FALSE, ignore_na = FALSE, trim = TRUE)
binary_cols(x, invert = FALSE)
two_cat_cols(x, invert = FALSE)

Arguments

x

data frame

invert

single logical, if true, will return non-binary columns

ignore_na

If TRUE, then return columns with two distinct values in addition to NA. Default is FALSE, i.e. NA is counted as a distinct item.

trim

If character column found, then trim white space before assessing

Value

vector of column names

Functions

• two_cat_col_names: Get the columns which have exactly two categories therein, not including NA values. This would catch 0,1 "Yes", "No", etc.

• binary_cols: Get the data frame containing just the binary columns.

• two_cat_cols: Get the data frame containing only columns of input which have two categories

Examples

# NOT RUN {
dat <- data.frame(
  c("a", "b"), c(TRUE, FALSE), c(1, 0), c(1L, 0L),
  c(1L, 2L), c(0.1, 0.2), c("9", "8")
)
names(dat) <- c(
  "char", "bin", "binfloat", "binint",
  "int", "float", "charint"
)
binary_cols(dat)
binary_col_names(dat)
binary_col_names(dat, invert = TRUE)
df <- data.frame(
  x = c("A", "B", "A", "B"),
  y = letters[1:4],
  z = c("y", NA, "y", NA),
  stringsAsFactors = FALSE
)
two_cat_col_names(df)
df[1, 1] <- NA
df[2, 2] <- NA
df
stopifnot(two_cat_col_names(df) == "z")
stopifnot(two_cat_col_names(df, ignore_na = TRUE) == "x")
# }