Insert rows with zeros in data frames with nested groups

Question

I have a data set with nested groups and with some rows missing:

set.seed(123)
df <- data.frame(Gr1 = rep(c("x", "y"), each = 10),
                 Gr2 = rep(c("x1", "x2", "y1", "y2"), each = 5),
                 ID = paste0(rep(c("x", "y"), each = 10), letters[1:5]),
                 var1 = round(rnorm(20), 2),
                 var2 = round(rnorm(20), 2))

rmv.rows <- sample(1:20, 5)
df <- df[-rmv.rows, ]

   Gr1 Gr2 ID  var1  var2
1    x  x1 xa -0.56 -1.07
3    x  x1 xc  1.56 -1.03
4    x  x1 xd  0.07 -0.73
6    x  x2 xa  1.72 -1.69
7    x  x2 xb  0.46  0.84
9    x  x2 xd -0.69 -1.14
10   x  x2 xe -0.45  1.25
11   y  y1 ya  1.22  0.43
12   y  y1 yb  0.36 -0.30
15   y  y1 ye -0.56  0.82
16   y  y2 ya  1.79  0.69
17   y  y2 yb  0.50  0.55
18   y  y2 yc -1.97 -0.06
19   y  y2 yd  0.70 -0.31
20   y  y2 ye -0.47 -0.38

I would like to fill missing rows (i.e. combinations of Gr1, Gr2 and ID) by zeros.

I tried approaches as suggested here, however it returns all possible combinations of Gr1, Gr2 and ID and not those present in data. In other words, I would like to insert only existing combinations of Gr1, Gr2 and ID. The desired output should be:

   Gr1 Gr2 ID  var1  var2
1    x  x1 xa -0.56 -1.07
2    x  x1 xb  0.00  0.00
3    x  x1 xc  1.56 -1.03
4    x  x1 xd  0.07 -0.73
5    x  x1 xe  0.00  0.00
6    x  x2 xa  1.72 -1.69
7    x  x2 xb  0.46  0.84
8    x  x2 xc  0.00  0.00
9    x  x2 xd -0.69 -1.14
10   x  x2 xe -0.45  1.25
11   y  y1 ya  1.22  0.43
12   y  y1 yb  0.36 -0.30
13   y  y1 yc  0.00  0.00
14   y  y1 yd  0.00  0.00
15   y  y1 ye -0.56  0.82
16   y  y2 ya  1.79  0.69
17   y  y2 yb  0.50  0.55
18   y  y2 yc -1.97 -0.06
19   y  y2 yd  0.70 -0.31
20   y  y2 ye -0.47 -0.38

Answer 1

Here is an option that uses data.table:

library(data.table)
setDT(df)
all_comb <- df[, CJ(Gr2, ID, unique = TRUE), by = Gr1]
df_out <- df[all_comb, on = .(Gr1, Gr2, ID)]
df_out[is.na(df_out)] <- 0
df_out

#     Gr1 Gr2 ID  var1  var2
#  1:   x  x1 xa -0.56 -1.07
#  2:   x  x1 xb -0.23 -0.22
#  3:   x  x1 xc  1.56 -1.03
#  4:   x  x1 xd  0.07 -0.73
#  5:   x  x1 xe  0.13 -0.63
#  6:   x  x2 xa  0.00  0.00
#  7:   x  x2 xb  0.00  0.00
#  8:   x  x2 xc  0.00  0.00
#  9:   x  x2 xd -0.69 -1.14
# 10:   x  x2 xe -0.45  1.25
# 11:   y  y1 ya  0.00  0.00
# 12:   y  y1 yb  0.36 -0.30
# 13:   y  y1 yc  0.40  0.90
# 14:   y  y1 yd  0.11  0.88
# 15:   y  y1 ye  0.00  0.00
# 16:   y  y2 ya  1.79  0.69
# 17:   y  y2 yb  0.50  0.55
# 18:   y  y2 yc -1.97 -0.06
# 19:   y  y2 yd  0.70 -0.31
# 20:   y  y2 ye -0.47 -0.38

PS.

For users that have not yet updated to R 3.6 here is the data produced by OP code in the current version of R:

df <- structure(list(Gr1 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("x", "y"), class = "factor"), 
    Gr2 = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 3L, 
    4L, 4L, 4L, 4L, 4L), .Label = c("x1", "x2", "y1", "y2"), class = "factor"), 
    ID = structure(c(1L, 2L, 3L, 4L, 5L, 4L, 5L, 7L, 8L, 9L, 
    6L, 7L, 8L, 9L, 10L), .Label = c("xa", "xb", "xc", "xd", 
    "xe", "ya", "yb", "yc", "yd", "ye"), class = "factor"), var1 = c(-0.56, 
    -0.23, 1.56, 0.07, 0.13, -0.69, -0.45, 0.36, 0.4, 0.11, 1.79, 
    0.5, -1.97, 0.7, -0.47), var2 = c(-1.07, -0.22, -1.03, -0.73, 
    -0.63, -1.14, 1.25, -0.3, 0.9, 0.88, 0.69, 0.55, -0.06, -0.31, 
    -0.38)), row.names = c(1L, 2L, 3L, 4L, 5L, 9L, 10L, 12L, 
13L, 14L, 16L, 17L, 18L, 19L, 20L), class = "data.frame")