Rescale variables to start values by group

Convenience wrapper of dplyr::group_by and dplyr::mutate to scale variables, especially time-series, by series start values

Usage

rel_start(df, col_vars, group_vars)

Arguments

df

data.frame

col_vars

variable names (quoted or unquoted) to rescale to initial values

group_vars

variable names (quoted or unquoted) to group col_vars by

Value

data.frame with all original data and new rel_ columns for each rescaled variable

Examples

test_df <- data.frame(grp = rep(1:3, each = 10)
, val = rep(10:1, times = 3))


test_df %>%
  rel_start(col_vars = val, group_vars = grp) %>%
  print(n = 30)
#> # A tibble: 30 × 3
#> # Groups:   grp [3]
#>      grp   val rel_val
#>    <int> <int>   <dbl>
#>  1     1    10     1  
#>  2     1     9     0.9
#>  3     1     8     0.8
#>  4     1     7     0.7
#>  5     1     6     0.6
#>  6     1     5     0.5
#>  7     1     4     0.4
#>  8     1     3     0.3
#>  9     1     2     0.2
#> 10     1     1     0.1
#> 11     2    10     1  
#> 12     2     9     0.9
#> 13     2     8     0.8
#> 14     2     7     0.7
#> 15     2     6     0.6
#> 16     2     5     0.5
#> 17     2     4     0.4
#> 18     2     3     0.3
#> 19     2     2     0.2
#> 20     2     1     0.1
#> 21     3    10     1  
#> 22     3     9     0.9
#> 23     3     8     0.8
#> 24     3     7     0.7
#> 25     3     6     0.6
#> 26     3     5     0.5
#> 27     3     4     0.4
#> 28     3     3     0.3
#> 29     3     2     0.2
#> 30     3     1     0.1

test_df %>%
  rel_start(col_vars = "val", group_vars = "grp") %>%
  print(n = 30)
#> # A tibble: 30 × 3
#> # Groups:   grp [3]
#>      grp   val rel_val
#>    <int> <int>   <dbl>
#>  1     1    10     1  
#>  2     1     9     0.9
#>  3     1     8     0.8
#>  4     1     7     0.7
#>  5     1     6     0.6
#>  6     1     5     0.5
#>  7     1     4     0.4
#>  8     1     3     0.3
#>  9     1     2     0.2
#> 10     1     1     0.1
#> 11     2    10     1  
#> 12     2     9     0.9
#> 13     2     8     0.8
#> 14     2     7     0.7
#> 15     2     6     0.6
#> 16     2     5     0.5
#> 17     2     4     0.4
#> 18     2     3     0.3
#> 19     2     2     0.2
#> 20     2     1     0.1
#> 21     3    10     1  
#> 22     3     9     0.9
#> 23     3     8     0.8
#> 24     3     7     0.7
#> 25     3     6     0.6
#> 26     3     5     0.5
#> 27     3     4     0.4
#> 28     3     3     0.3
#> 29     3     2     0.2
#> 30     3     1     0.1