Is the grouping beforehand necessary? Could you simply, "for all the dates
that are "4.01.2020" and have the "Value" greater than zero add 5 to the
"Value" "? I may be missing something.
--Chris Ryan
On Wed, May 26, 2021 at 11:53 AM Elahe chalabi via R-help <
r-help@r-project.org> wrote:
> Hi everyone,
>
> I have the following dataframe:
>
>
>
> structure(list(Department = c("A", "A", "A", "A", "A", "A", "A",
> "A", "B", "B", "B", "B", "B", "B", "B", "B"), Class = c(1L, 1L,
> 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), Value = c(0L,
> 100L, 800L, 800L, 0L, 300L, 1200L, 0L, 0L, 0L, 400L, 400L, 200L,
> 800L, 1200L, 0L), Date = c("1.01.2020", "2.01.2020", "3.01.2020",
> "4.01.2020", "1.01.2020", "2.01.2020", "3.01.2020", "4.01.2020",
> "1.01.2020", "2.01.2020", "3.01.2020", "4.01.2020", "1.01.2020",
> "2.01.2020", "3.01.2020", "4.01.2020")), class = "data.frame",
> row.names = c(NA,
> -16L))
>
> using dplyr I need to group by "Depatment" and "Class" and then for all
> the dates that are "4.01.2020" and have the "Value" greater than zero add
> 5 to the "Value", meaning the desired dataframe will be (NewValue column) :
>
>
>
> structure(list(Department = c("A", "A", "A", "A", "A", "A", "A",
> "A", "B", "B", "B", "B", "B", "B", "B", "B"), Class = c(1L, 1L,
> 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), Value = c(0L,
> 100L, 800L, 800L, 0L, 300L, 1200L, 0L, 0L, 0L, 400L, 400L, 200L,
> 800L, 1200L, 0L), Date = c("1.01.2020", "2.01.2020", "3.01.2020",
> "4.01.2020", "1.01.2020", "2.01.2020", "3.01.2020", "4.01.2020",
> "1.01.2020", "2.01.2020", "3.01.2020", "4.01.2020", "1.01.2020",
> "2.01.2020", "3.01.2020", "4.01.2020"), NewValue = c(0L, 100L,
> 800L, 805L, 0L, 300L, 1200L, 0L, 0L, 0L, 400L, 405L, 200L, 800L,
> 1200L, 0L)), class = "data.frame", row.names = c(NA, -16L))
>
>
> Thanks a lot for any help!
> Elahe
>
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