Drop empty or constant columns and rows

drop_empty() removes rows or columns that are entirely missing. drop_constant() removes columns that hold a single distinct value. The counterparts of janitor::remove_empty() and janitor::remove_constant().

Usage

drop_empty(data, which = c("rows", "cols"))

drop_constant(data, na_as_value = FALSE)

Arguments

data

A data frame.

which

"rows", "cols", or both (the default).

na_as_value

Treat NA as a distinct value, so a column of NA s plus one real value counts as two (default FALSE) .

Value

The data frame, with the offending rows or columns removed. The names of what was dropped are attached as the "dropped" attribute.

Details

A constant column carries no information and breaks anything that scales by variance, so it is worth removing – but it is also a FINDING. A column that was informative in the pinned capsule and is constant in a fresh fetch means the source changed, so check capsule_drift() before deleting it and moving on.

See also

profile_columns(), which reports n_distinct without removing anything.

Examples

df <- data.frame(
  keep = c(1, 2, NA),
  all_na = c(NA, NA, NA),
  constant = c(7, 7, 7),
  stringsAsFactors = FALSE
)

drop_empty(df)
#>   keep constant
#> 1    1        7
#> 2    2        7
#> 3   NA        7
attr(drop_empty(df), "dropped")
#> [1] "all_na"

drop_constant(df)
#>   keep
#> 1    1
#> 2    2
#> 3   NA

# Rows only.
drop_empty(data.frame(a = c(1, NA), b = c(2, NA)), which = "rows")
#>   a b
#> 1 1 2

# A column of NAs plus one value is constant by default, and not when
# NA is treated as a value of its own.
x <- data.frame(v = c(NA, NA, 5))
ncol(drop_constant(x))
#> [1] 0
ncol(drop_constant(x, na_as_value = TRUE))
#> [1] 1