Creating an iterative function using lag and mutate command in R

I have a data set DF with the following data

I want to create a column Z = X + Y - Previous year's Y So it creates the following Table:

I can use "mutate" from DPLYR to generate column Z: mutate(DF, Z = X + Y - lag(Y))

I can use tapply to apply recursively on DF. Can I create a function using DPLYR in a user-defined function to apply this using tapply later?

In dplyr you can add group_by to apply a function for every group (Zone).

library(dplyr)
DF %>% group_by(Zone) %>% mutate(Z = X + Y - lag(Y))

#   Zone  Year     X     Y     Z
#  <int> <int> <int> <int> <int>
#1  1001  2018    10     5    NA
#2  1001  2019    20    10    25
#3  1001  2020    30    20    40
#4  1002  2018    15    10    NA
#5  1002  2019    25    20    35
#6  1002  2020    35    40    55

We can also write a function :

add_new_col = function(x, y) {
  x + y - lag(y)
}

which can be used as :

DF %>% group_by(Zone) %>% mutate(Z = add_new_col(X, Y))

data

DF <- structure(list(Zone = c(1001L, 1001L, 1001L, 1002L, 1002L, 1002L
), Year = c(2018L, 2019L, 2020L, 2018L, 2019L, 2020L), X = c(10L, 
20L, 30L, 15L, 25L, 35L), Y = c(5L, 10L, 20L, 10L, 20L, 40L)), 
class = "data.frame", row.names = c(NA, -6L))