Merging two dataframes creates new missing observations - r

Question

I have two dataframes with the following matching keys: year, region and province. They each have a set of variables (in this illustrative example I use x1 for df1 and x2 for df2) and both variables have several missing values on their own.
df1 df2
year region province x2 ... xn year region province x2 ... xn
2019 1 5 NA 2019 1 5 NA
2019 2 4 NA. 2019 2 4 NA.
2019 2 4 NA. 2019 2 4 NA
2018 3 7 13. 2018 3 7 13
2018 3 7 15 2018 3 7 15
2018 3 7 17 2018 3 7 17
I want to merge both dataframes such that they end up like this:
year region province x1 x2
2019 1 5 3 NA
2019 2 4 27 NA
2019 2 4 15 NA
2018 3 7 12 13
2018 3 7 NA 15
2018 3 7 NA 17
2017 4 9 NA 12
2017 4 9 19 30
2017 4 9 20 10
However, when doing so using merged_df <- merge(df1, df2, by=c("year","region","province"), all.x=TRUE), R seems to create a lot of additional missing values on each of the variable columns (x1 and x2), which were not there before. What is happening here? I have tried sorting both using df1 %>% arrange(province,-year) and df2 %>% arrange(province,-year), which is enough to have matching order in both dataframes, only to find the same issue when running the merge command. I've tried a bunch of other stuff too, but nothing seems to work. R's output sort of looks like this:
year region province x1 x2
2019 1 5 NA NA
2019 2 4 NA NA
2019 2 4 NA NA
2018 3 7 NA NA
2018 3 7 NA NA
2018 3 7 NA NA
2017 4 9 15 NA
2017 4 9 19 30
2017 4 9 20 10
I have done this before; in fact, one of the dataframes is an already merged dataframe in which I did not encounter this issue.

Answer 1

Maybe it is not clear the concept of merge(). I include two examples with example data. I hope you understand and it helps you.
#Data
set.seed(123)
DF1 <- data.frame(year=rep(c(2017,2018,2019),3),
region=rep(c(1,2,3),3),
province=round(runif(9,1,5),0),
x1=rnorm(9,3,1.5))
DF2 <- data.frame(year=rep(c(2016,2018,2019),3),
region=rep(c(1,2,3),3),
province=round(runif(9,1,5),0),
x2=rnorm(9,3,1.5))
#Merge based only in df1
Merged1 <- merge(DF1,DF2,by=intersect(names(DF1),names(DF2)),all.x=T)
Merged1
year region province x1 x2
1 2017 1 2 2.8365510 NA
2 2017 1 3 3.7557187 NA
3 2017 1 5 4.9208323 NA
4 2018 2 4 2.8241371 NA
5 2018 2 5 6.7925048 1.460993
6 2018 2 5 0.4090941 1.460993
7 2019 3 1 5.5352765 NA
8 2019 3 3 3.8236451 4.256681
9 2019 3 3 3.2746239 4.256681
#Merge including all elements despite no match between ids
Merged2 <- merge(DF1,DF2,by=intersect(names(DF1),names(DF2)),all = T)
Merged2
year region province x1 x2
1 2016 1 3 NA 4.052034
2 2016 1 4 NA 2.062441
3 2016 1 5 NA 2.673038
4 2017 1 2 2.8365510 NA
5 2017 1 3 3.7557187 NA
6 2017 1 5 4.9208323 NA
7 2018 2 1 NA 0.469960
8 2018 2 2 NA 2.290813
9 2018 2 4 2.8241371 NA
10 2018 2 5 6.7925048 1.460993
11 2018 2 5 0.4090941 1.460993
12 2019 3 1 5.5352765 NA
13 2019 3 2 NA 1.398264
14 2019 3 3 3.8236451 4.256681
15 2019 3 3 3.2746239 4.256681
16 2019 3 4 NA 1.906663