Double entries in dataframe after merg r - r

Question

My data
Hello, I have a problem with merging two dataframes with each other.
The goal is to merge them so that each date has the corresponding values. If there is no corresponding value, I want to replace NA with 0.
names(FiresNearLA.ab.03)[1] <- "Date.Local"
U.NO2.ab.03 <- unique(NO2.ab.03) # No2.ab.03 has all values multiplied
ind <- merge(FiresNearLA.ab.03,U.NO2.ab.03, all = TRUE, all.x=TRUE)
ind[is.na(ind)] <- 0
So far so good. And the first lines look like they are supposed to look. But beginning from 2004-04-24, all dates are doubled and it writes weird values in the second NO2.Mean colum.
U.NO2.Mean table:
Date.Local NO2.Mean
361 2004-03-31 30.217391
365 2004-04-24 50.000000
366 2004-04-25 47.304348
370 2004-04-26 50.913043
374 2004-04-27 41.157895
ind table:
Date.Local FIRE_SIZE F.number.n_fires NO2.Mean
113 2004-04-22 34.30 10 13.681818
114 2004-04-23 45.00 13 17.222222
115 2004-04-24 55.40 22 28.818182
116 2004-04-24 55.40 22 50.000000
117 2004-04-25 2306.85 15 47.304348
118 2004-04-25 2306.85 15 21.090909
Why, are there Values in NO2.Mean for 2004-04-23 and 2004-04-22 days if they should be 0? and why does it double the values after the 24th and where do the second ones come from?
Thank you

Answer 1

So I managed to merge your data:
FiresNearLA.ab.03 <- dget("FiresNearLA.ab.03.txt", keep.source = FALSE)
U.NO2.ab.03 <- dget("NO2.ab.03.txt", keep.source = FALSE)
ind <- merge(FiresNearLA.ab.03,
U.NO2.ab.03,
all = TRUE,
by.x = "DISCOVERY_DATEymd",
by.y = "Date.Local")
As a side note: Usually, you share a small sample of your data on stackoverflow, not the whole thing. In your case, dput(FiresNearLA.ab.03[1:50, ]) and then copy and paste from the console to the question would have been sufficient.
Back to your problem: The duplication already happens in NO2.ab.03 and a number of dates and values occurs twice or more often. The easiest way to solve this (in my experience) is to use the package data.table which has a duplicated which is more straightforward and also faster:
library(data.table)
# Test duplicated occurrences in U.NO2.ab.03
> table(duplicated(U.NO2.ab.03, by = c("DISCOVERY_DATEymd", "NO2.Mean")))
FALSE TRUE
7767 27308
>
> nrow(ind)
[1] 35229
# Remove duplicated rows from data frame
> ind <- ind[!duplicated(ind, by = c("DISCOVERY_DATEymd", "NO2.Mean")), ]
> nrow(ind)
[1] 7921
After these steps, you should be fine :)

Answer 2

I got the answer. The Original data source of NO3.ab.03 was faulty.
As JonGrub suggestes said, the problem was within NO3.ab.O3. For some days it had two different NO3.Means corresponding to the same date. I deleted this rows and now its working good. Thank you again for the help and the great advices