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Fill missing values by a named method

Source: R/replace_na_with.R
replace_na_with.Rd

Generic entry point to the replace_na_*() family: pick the method with an argument rather than by choosing a function.

Usage

replace_na_with(
  x,
  method = c("linear", "spline", "stine", "locf", "value"),
  value = NULL,
  min_gap = 1,
  max_gap = Inf,
  times = NULL,
  ...
)

Arguments

x

A numeric vector, or a data frame of numeric columns, with missing values to fill.

method

Character string specifying the replacement method:

  • "linear": Linear interpolation (default)

  • "spline": Spline interpolation for smoother curves

  • "stine": Stineman interpolation preserving data shape

  • "locf": Last observation carried forward

  • "value": Replace with a constant value

value

Numeric value for replacement when method = "value".

min_gap

Integer specifying the minimum gap size to fill. Gaps shorter than this are left as NA. Default 1 (fill all gaps).

max_gap

Integer or Inf specifying the maximum gap size to fill. Gaps longer than this are left as NA. Default Inf (no limit).

times

Optional numeric vector of positions for the values in x, normally the frame's index. Interpolation is then over elapsed time rather than over row position, so an irregularly sampled gap is filled correctly. Defaults to row position, and is ignored by the methods that do not interpolate.

...

Additional parameters passed to the underlying function.

Value

The same shape as x, with gaps filled where the gap-length criteria are met.

Details

Returns the same shape it is given. Every method is univariate, so a data frame is filled one column at a time — meaning this generic does work with dplyr::across() as well as dplyr::pick().

See also

filter_with() for smoothing, filter_na_with() for masking.

Examples

x <- c(1, NA, NA, 4, 5, NA, NA, NA, 9)

replace_na_with(x, "linear")
#> [1] 1 2 3 4 5 6 7 8 9
replace_na_with(x, "value", value = 0)
#> [1] 1 0 0 4 5 0 0 0 9
replace_na_with(x, "linear", max_gap = 2)
#> [1]  1  2  3  4  5 NA NA NA  9

# A frame is filled column by column
replace_na_with(data.frame(a = x, b = rev(x)), "locf")
#>   a b
#> 1 1 9
#> 2 1 9
#> 3 1 9
#> 4 4 9
#> 5 5 5
#> 6 5 4
#> 7 5 4
#> 8 5 4
#> 9 9 1