Start out with merge():
> df <- merge(df1, df2, all.x=TRUE) # could add by="location" for emphasis
> df
location Name Position Country
1 36 cristina B <NA>
2 75 francesca A UK
You could make make your 'Match' column from is.na(df$Country) if you
knew that df2$Country were never NA. Otherwise you can add a fake
variable to the merge to tell which output rows come from unmatched
rows in the first data.frame:
> df12 <- merge(df1, cbind(df2, fromDF2=TRUE), all.x=TRUE, by="location")
> df12$Match <- !is.na(df12$fromDF2)
> df12
location Name Position Country fromDF2 Match
1 36 cristina B <NA> NA FALSE
2 75 francesca A UK TRUE TRUE
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
> Behalf Of francy
> Sent: Monday, October 03, 2011 10:55 AM
> To: r-help@r-project.org
> Subject: [R] Merge two data frames and find common values and non-matching
> values
>
> Hi,
>
> I am trying to find a function to match two data frames of different lengths
> for one field only.
> So, for example,
> df1 is:
>
> Name Position location
> francesca A 75
> cristina B 36
>
> And df2 is:
>
> location Country
> 75 UK
> 56 Austria
>
> And I would like to match on "Location" and the output to be something like:
>
> Name Position Location Match
> francesca A 75 1
> cristina B 36 0
>
> I have tried with the function 'match' or with:
> subset(df1, location %in% df2)
> But it does not work.
>
> Could you please help me figure out how to do this?
>
> Thank you!
> -f
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Merge-two-data-frames-and-find-common-
> values-and-non-matching-values-tp3868299p3868299.html
> Sent from the R help mailing list archive at Nabble.com.
> [[alternative HTML version deleted]]
>
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