Time-Based Rolling Sum
tbr_sum(.tbl, x, tcolumn, unit = "years", n, na.rm = FALSE)
a data frame with at least two variables; time column formatted as date, date/time and value column.
column containing the values to calculate the sum.
formatted time column.
character, one of "years", "months", "weeks", "days", "hours", "minutes", "seconds"
numeric, describing the length of the time window.
logical. Should missing values be removed?
dataframe with column for the rolling sum.
tbr_sum(Dissolved_Oxygen, x = Average_DO, tcolumn = Date, unit = "years", n =
5)
#> # A tibble: 236 × 7
#> Station_ID Date Param_Code Param_Desc Average_DO Min_DO sum
#> <int> <date> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 12515 2000-01-03 00300 OXYGEN, DISSOLVED (… 6.19 6.19 6.19
#> 2 12515 2000-03-14 00300 OXYGEN, DISSOLVED (… 6.7 6.7 20.2
#> 3 12517 2000-03-14 00300 OXYGEN, DISSOLVED (… 7.3 7.3 20.2
#> 4 12515 2000-03-16 00300 OXYGEN, DISSOLVED (… 6.41 6.41 26.6
#> 5 12515 2000-05-03 00300 OXYGEN, DISSOLVED (… 4.42 4.42 31.0
#> 6 12517 2000-06-14 00300 OXYGEN, DISSOLVED (… 5.74 5.74 36.8
#> 7 12515 2000-06-15 00300 OXYGEN, DISSOLVED (… 4.86 4.86 41.6
#> 8 12515 2000-07-11 00300 OXYGEN, DISSOLVED (… 4.48 4.48 46.1
#> 9 12515 2000-09-12 00300 OXYGEN, DISSOLVED (… 5.64 5.64 51.7
#> 10 12517 2000-10-17 00300 OXYGEN, DISSOLVED (… 7.96 7.96 59.7
#> # … with 226 more rows