Fill gaps summing the previous value of a variable to the value of another variable.
Source:R/gapfilling.R
sum_fill.RdFills gaps in a variable with the sum of its previous value and the value of another variable. When a gap has multiple observations, the values are accumulated along the series. When there is a gap at the start of the series, it can either remain unfilled or assume an invisible 0 value before the first observation and start filling with cumulative sum.
Arguments
- df
A tibble data frame containing one observation per row.
- var
The variable of df containing gaps to be filled.
- change_var
The variable whose values will be used to fill the gaps.
- start_with_zero
Logical. If TRUE, assumes an invisible 0 value before the first observation and fills with cumulative sum starting from the first change_var value. If FALSE (default), starting NA values remain unfilled.
- .by
A character vector with the grouping variables (optional).
Value
A tibble dataframe (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),
change_variable = c(1, 2, 3, 4, 1, 1, 0, 0, 0, 0, 0, 1)
)
sum_fill(
sample_tibble,
value,
change_variable,
start_with_zero = FALSE,
.by = c("category")
)
#> # A tibble: 12 × 5
#> category year value change_variable source_value
#> <chr> <chr> <dbl> <dbl> <chr>
#> 1 a 2015 NA 1 NA
#> 2 a 2016 3 2 Original
#> 3 a 2017 6 3 Filled with sum
#> 4 a 2018 10 4 Filled with sum
#> 5 a 2019 0 1 Original
#> 6 a 2020 1 1 Filled with sum
#> 7 b 2015 1 0 Original
#> 8 b 2016 1 0 Filled with sum
#> 9 b 2017 1 0 Filled with sum
#> 10 b 2018 1 0 Filled with sum
#> 11 b 2019 5 0 Original
#> 12 b 2020 6 1 Filled with sum
sum_fill(
sample_tibble,
value,
change_variable,
start_with_zero = TRUE,
.by = c("category")
)
#> # A tibble: 12 × 5
#> category year value change_variable source_value
#> <chr> <chr> <dbl> <dbl> <chr>
#> 1 a 2015 1 1 Filled with sum
#> 2 a 2016 3 2 Original
#> 3 a 2017 6 3 Filled with sum
#> 4 a 2018 10 4 Filled with sum
#> 5 a 2019 0 1 Original
#> 6 a 2020 1 1 Filled with sum
#> 7 b 2015 1 0 Original
#> 8 b 2016 1 0 Filled with sum
#> 9 b 2017 1 0 Filled with sum
#> 10 b 2018 1 0 Filled with sum
#> 11 b 2019 5 0 Original
#> 12 b 2020 6 1 Filled with sum