Time-Based Rolling Standard Deviation
tbr_sd(.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 standard deviation.
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?
tibble with column for the rolling sd.
tbr_sd(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 sd
#> <int> <date> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 12515 2000-01-03 00300 OXYGEN, DISSOLVED … 6.19 6.19 NA
#> 2 12515 2000-03-14 00300 OXYGEN, DISSOLVED … 6.7 6.7 0.556
#> 3 12517 2000-03-14 00300 OXYGEN, DISSOLVED … 7.3 7.3 0.556
#> 4 12515 2000-03-16 00300 OXYGEN, DISSOLVED … 6.41 6.41 0.481
#> 5 12515 2000-05-03 00300 OXYGEN, DISSOLVED … 4.42 4.42 1.08
#> 6 12517 2000-06-14 00300 OXYGEN, DISSOLVED … 5.74 5.74 0.985
#> 7 12515 2000-06-15 00300 OXYGEN, DISSOLVED … 4.86 4.86 1.02
#> 8 12515 2000-07-11 00300 OXYGEN, DISSOLVED … 4.48 4.48 1.08
#> 9 12515 2000-09-12 00300 OXYGEN, DISSOLVED … 5.64 5.64 1.01
#> 10 12517 2000-10-17 00300 OXYGEN, DISSOLVED … 7.96 7.96 1.18
#> # … with 226 more rows