"merge" is generally the base R answer to this question, and there are
equivalent functions in various contributed packages.
However, it is necessary to identify which columns in each table uniquely
identify each row ("primary key"). If your Serial 3036 shows up 10 times in the
first table and 10 times in the second table then you will end up with all
combinations of those rows (100 rows) in a merge that uses only Serial to match
rows. Is that what you want?
On January 8, 2020 6:52:18 AM PST, Thomas Subia <[email protected]> wrote:
>Colleagues,
>
>I have two data frames which look like this.
>
>Data frame 1
>
> Serial Pre.Hole Pre.flow Pre.Date
>1 3036 1 0.24 19-Nov-19
>2 3036 2 0.212 19-Nov-19
>3 3036 3 1.292 19-Nov-19
>4 3036 4 0.262 19-Nov-19
>5 3036 5 1.291 19-Nov-19
>6 3036 6 0.26 19-Nov-19
>
>Data frame 2
>
> Serial Post.Hole Post.flow Post.Date
>62323 11024 44 -0.678 11-Dec-19
>62324 11024 45 -0.659 11-Dec-19
>62325 11024 46 -0.654 11-Dec-19
>62326 11024 47 -0.699 11-Dec-19
>62327 11024 48 -0.671 11-Dec-19
>62328 11024 49 -0.687 11-Dec-19
>
>What I want is to create a data frame whose serials numbers are common
>to data frames 1 and 2.
>The resulting data frame 1st row would look like this.
>
>Serial Post.Hole Post.flow Post.Date Pre.Hole
>Pre.flow Pre.Date
>
>Any ideas on how to do this would be appreciated.
>
>Thomas Subia
>Statistician / Senior Quality Engineer
>
>IMG Companies
>225 Mountain Vista Parkway
>Livermore, CA 94551
>T. (925) 273-1106
>F. (925) 273-1111
>E. [email protected]
>
>
>Precision Manufacturing for Emerging Technologies
>imgprecision.com
>
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