Calculate Lagged Metrics

Usage

change(df, cols, csm = NULL)

Arguments

df: data frame
cols: numeric columns to calculate absolute/relative change & rate of return
csm: numeric cols to calculate cumulative sum for

Examples

mock_provider(2020:2025) |>
  dplyr::group_by(group) |>
  change(payment, csm = c("payment", "_chg"))
#> # A tibble: 12 × 8
#>     year group payment payment_chg payment_pct payment_ror payment_csm
#>    <int> <chr>   <int>       <int>       <dbl>       <dbl>       <int>
#>  1  2020 A       15292           0      0            1           15292
#>  2  2021 A       15526         234      0.0153       1.02        30818
#>  3  2022 A       16603        1077      0.0694       1.07        47421
#>  4  2023 A       10484       -6119     -0.369        0.631       57905
#>  5  2024 A       12606        2122      0.202        1.20        70511
#>  6  2025 A       11475       -1131     -0.0897       0.910       81986
#>  7  2020 B       18165           0      0            1           18165
#>  8  2021 B       12244       -5921     -0.326        0.674       30409
#>  9  2022 B       14612        2368      0.193        1.19        45021
#> 10  2023 B       19982        5370      0.368        1.37        65003
#> 11  2024 B       14172       -5810     -0.291        0.709       79175
#> 12  2025 B       19089        4917      0.347        1.35        98264
#> # ℹ 1 more variable: payment_chg_csm <int>