Adding rows depending on condition

I need a little help with a very simple question:

Let’s say I have this data frame:

data_new <- data.frame(section = c("1", "4", "5","6"),
                       density = c("0.2", "0.7", "0.8", "0.2"))
> data_new
  section density
1       1     0.2
2       4     0.7
3       5     0.8
4       6     0.2

I need to add rows because the full table is based on 6 sections, but only have data on 4. This means that in this case I have to add 2 rows (sections 2 and 3) with density 0 so I have:

> data_desired
  section density
1       1     0.2
2       4     0.7
3       5     0.8
4       6     0.2
5       2       0
6       3       0

The point is that the combination of 0 density rows may vary. In this case sections 3 and 4 were empty, but next time it may be that no section has density 0 or that I have to add 5 sections, etc. It can vary a lot, from 1 section with data to all sections with data.

I’m sure there is an elegant way to add to my pipe to ad the rows I need and that is case specific. Thanks a lot for your help!!

>Solution :

Another option using rows_update:

library(dplyr)
#create zero density dataframe

n<-6
data_zero <- data.frame(section = as.character(c(1:n)),
                       density = as.character(rep(0,n)))

data_new <- data.frame(section = c("1", "4", "5","6"),
                       density = c("0.2", "0.7", "0.8", "0.2"))

rows_update(data_zero ,data_new)
  section density
1       1     0.2
2       2       0
3       3       0
4       4     0.7
5       5     0.8
6       6     0.2