Fill from past values

If back index ( NA index - back) is lower than zero then the it is filled with the first value of the data frame. If the value in the back index is also NA, it iterates backwards until finding a non-NA value.

Usage

fill_from_past(dtf, varnames, back = 24)

Arguments

dtf

data.frame or tibble, first column of name datetime being of class datetime and rest of columns being numeric

varnames

character or vector of characters, column names with NA values

back

integer, number of indices (rows) to go back and get the filling value

Value

tibble or data.frame

Examples

past_data <- data.frame(
  datetime = as.POSIXct("2024-01-01 00:00:00", tz = "UTC") + 0:3 * 3600,
  consumption = c(1.2, NA, NA, 2.5)
)
fill_from_past(past_data, "consumption", back = 1)
#>              datetime consumption
#> 1 2024-01-01 00:00:00         1.2
#> 2 2024-01-01 01:00:00         1.2
#> 3 2024-01-01 02:00:00         1.2
#> 4 2024-01-01 03:00:00         2.5