adding mising rows in R - r

Question

I have a table in R as follows
month day total
1 1 3 1414
2 1 5 1070
3 1 6 211
4 1 7 2214
5 1 8 1766
6 1 13 2486
7 1 14 43
8 1 15 2349
9 1 16 4616
10 1 17 2432
11 1 18 1482
12 1 19 694
13 1 20 968
14 1 23 381
15 1 24 390
16 1 26 4063
17 1 27 3323
18 1 28 988
19 1 29 9671
20 1 30 11968
I have to add the missing values of days such as 1,2,4 with zero such that the result should be like
month day total
- 1 1 0
- 1 2 0
1 3 1414
1 4 0
2 1 5 1070
3 1 6 211
4 1 7 2214
5 1 8 1766
1 9 0
1 10 0
1 11 0
1 12 0
6 1 13 2486
7 1 14 43
8 1 15 2349
9 1 16 4616
10 1 17 2432
11 1 18 1482
12 1 19 694
13 1 20 968
1 21 0
1 22 0
14 1 23 381
15 1 24 390
1 25 0
16 1 26 4063
17 1 27 3323
18 1 28 988
19 1 29 9671
20 1 30 11968

Answer 1

Using only base R, you could do it this way:
for(d in 1:31) {
if(!d %in% my.df$day)
my.df[nrow(my.df) + 1,] <- c(1,d,0)
}
# Reorder rows
my.df <- my.df[with(my.df, order(month, day)),]
rownames(my.df) <- NULL
# Check the results
head(my.df)
# month day total
# 1 1 1 0
# 2 1 2 0
# 3 1 3 1414
# 4 1 4 0
# 5 1 5 1070
# 6 1 6 211

Answer 2

In R, we could create a new dataset with 'day' column from 1:30 and 'month' as '1', left_join with the original dataset and replace the NA values after the merge with '0'
df2 <- data.frame(month=1, day=1:30)
library(dplyr)
left_join(df2, df1) %>%
mutate(total=replace(total, which(is.na(total)),0))
Or use merge from base R to get 'dM' and assign the NA values in the 'total' to '0'
dM <- merge(df1, df2, all.y=TRUE)
dM$total[is.na(dM$total)] <- 0