Fill gaps in time series

Fills gaps by linear interpolation when possible, or carrying forward/backward when not possible. Labels output according to filling method.

Usage

Filling(data, var, Index)

Arguments

data

Data frame (grouped if needed)

var

Variable to be filled (unquoted column name)

Index

Time index (usually year)

Value

Data frame with filled variable and source column indicating filling method

Details

Remember to use `group_by()` and `ungroup()` when needed (do NOT use `.by` with this function). Always add `dplyr::ungroup()` immediately after using this function to prevent grouped data from flowing downstream.

The function creates a Source_* column indicating: - "Original": Value was present in original data - "Linear interpolation": Value filled by linear interpolation - "Last value carried forward": Value filled by carrying last known value forward - "First value carried backwards": Value filled by carrying first known value backward

Examples

if (FALSE) { # \dontrun{
data |>
  group_by(Region, Item) |>
  Filling(Production, Year) |>
  ungroup()
} # }