Fill missing values by a function of the nonmissings

For each specified column in x replace the missing values by a function of the nonmissing values.

fill_by_function(x, ..., fun = mean)

Arguments

x	A data frame.
...	The unquoted column names of the variables that should be filled.
fun	The function to apply on the nonmissing values.

Value

x with the altered columns.

Examples

library(dplyr) # for the pipe operator
x <- seq(as.Date('2016-01-01'), by = 'day', length.out = 366)
x <- x[sample(1:366, 200)] %>% sort
x_df <- data_frame(x  = x,
                   y1 = runif(200, 10, 20) %>% round,
                   y2 = runif(200, 1, 50) %>% round)
#> Warning: `data_frame()` is deprecated, use `tibble()`.
#> This warning is displayed once per session.
x_df %>% pad %>% fill_by_function(y1, y2)
#> pad applied on the interval: day
#> # A tibble: 363 x 3
#>    x             y1    y2
#>    <date>     <dbl> <dbl>
#>  1 2016-01-03  14    44  
#>  2 2016-01-04  11    34  
#>  3 2016-01-05  11    20  
#>  4 2016-01-06  15.0  26.4
#>  5 2016-01-07  15.0  26.4
#>  6 2016-01-08  15.0  26.4
#>  7 2016-01-09  15.0  26.4
#>  8 2016-01-10  19    28  
#>  9 2016-01-11  12    13  
#> 10 2016-01-12  17    11  
#> # … with 353 more rows
x_df %>% pad %>% fill_by_function(y1, y2, fun = median)
#> pad applied on the interval: day
#> # A tibble: 363 x 3
#>    x             y1    y2
#>    <date>     <dbl> <dbl>
#>  1 2016-01-03    14  44  
#>  2 2016-01-04    11  34  
#>  3 2016-01-05    11  20  
#>  4 2016-01-06    15  27.5
#>  5 2016-01-07    15  27.5
#>  6 2016-01-08    15  27.5
#>  7 2016-01-09    15  27.5
#>  8 2016-01-10    19  28  
#>  9 2016-01-11    12  13  
#> 10 2016-01-12    17  11  
#> # … with 353 more rows