linear_fill: Fill gaps by linear interpolation, or carrying forward or...

In whep: Processing Agro-Environmental Data

Fill gaps by linear interpolation, or carrying forward or backward.

Description

Fills gaps (NA values) in a time-dependent variable by linear interpolation between two points, or carrying forward or backwards the last or initial values, respectively. It also creates a new variable indicating the source of the filled values.

Usage

linear_fill(
  df,
  var,
  time_index,
  interpolate = TRUE,
  fill_forward = TRUE,
  fill_backward = TRUE,
  .by = NULL
)

Arguments

df	A tibble data frame containing one observation per row.
var	The variable of df containing gaps to be filled.
time_index	The time index variable (usually year).
interpolate	Logical. If TRUE (default), performs linear interpolation.
fill_forward	Logical. If TRUE (default), carries last value forward.
fill_backward	Logical. If TRUE (default), carries first value backward.
.by	A character vector with the grouping variables (optional).

Value

A tibble data frame (ungrouped) where gaps in var have been filled, and a new "source" variable has been created indicating if the value is original or, in case it has been estimated, the gapfilling method that has been used.

Examples

sample_tibble <- tibble::tibble(
  category = c("a", "a", "a", "a", "a", "a", "b", "b", "b", "b", "b", "b"),
  year = c(
    "2015", "2016", "2017", "2018", "2019", "2020",
    "2015", "2016", "2017", "2018", "2019", "2020"
  ),
  value = c(NA, 3, NA, NA, 0, NA, 1, NA, NA, NA, 5, NA),
)
linear_fill(sample_tibble, value, year, .by = c("category"))
linear_fill(
  sample_tibble,
  value,
  year,
  interpolate = FALSE,
  .by = c("category"),
)

whep documentation built on Nov. 5, 2025, 7:18 p.m.