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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