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    <p>The <code>data.table</code> package (that allows for x[y] syntax) makes this job incredibly easy. Assuming <code>df1</code> and <code>df2</code> are your data.frames:</p> <pre><code>require(data.table) dt1 &lt;- data.table(df1, key=c("V1","V2","V3")) dt2 &lt;- data.table(df2, key=c("V1","V2","V3")) dt2[dt1] # V1 V2 V3 V4 # 1: T1 A1 B1 1 # 2: T1 A1 B2 NA # 3: T1 A2 B1 3 # 4: T1 A2 B2 1 # 5: T2 A1 B1 2 # 6: T2 A1 B2 2 # 7: T2 A2 B1 3 # 8: T2 A2 B2 2 </code></pre> <p>gives you the desired result.</p> <p><strong>Edit:</strong> I've used your edited data and it seems to work.</p> <pre><code>df1 &lt;- structure(list(V1 = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L), .Label = c("T1", "T2"), class = "factor"), V2 = structure(c(1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L), .Label = c("A1", "A2"), class = "factor"), V3 = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), .Label = c("B1", "B2"), class = "factor")), .Names = c("V1", "V2", "V3"), class = "data.frame", row.names = c(NA, -8L)) df2 &lt;- structure(list(V1 = structure(c(1L, 1L, 2L, 1L, 2L, 2L, 2L), .Label = c("T1", "T2"), class = "factor"), V2 = structure(c(2L, 2L, 2L, 1L, 1L, 2L, 1L), .Label = c("A1", "A2"), class = "factor"), V3 = structure(c(2L, 1L, 1L, 1L, 2L, 2L, 1L), .Label = c("B1", "B2"), class = "factor"), run.no = 1:7, run.no.std.rp = structure(c(3L, 7L, 6L, 4L, 5L, 2L, 1L), .Label = c("C0.15", "C0.16", "C0.17", "C0.3", "C0.4", "C0.6", "C0.7"), class = "factor"), Block.ccd = c(0L, 0L, 0L, 0L, 0L, 0L, 0L), A = c(400L, 450L, 350L, 450L, 350L, 350L, 450L), B = c(147.5, 120, 175, 120, 120, 120, 120), C = c(5L, 2L, 2L, 8L, 8L, 2L, 2L), D = c(2.675, 4, 4, 4, 4, 1.35, 1.35)), .Names = c("V1", "V2", "V3", "run.no", "run.no.std.rp", "Block.ccd", "A", "B", "C", "D"), row.names = c("C0.17", "C0.7", "C0.6", "C0.3", "C0.4", "C0.16", "C0.15"), class = "data.frame") require(data.table) dt1 &lt;- data.table(df1, key=c("V1", "V2", "V3")) dt2 &lt;- data.table(df2, key=c("V1", "V2", "V3")) dt2[dt1] # V1 V2 V3 run.no run.no.std.rp Block.ccd A B C D # 1: T1 A1 B1 4 C0.3 0 450 120.0 8 4.000 # 2: T1 A1 B2 NA NA NA NA NA NA NA # 3: T1 A2 B1 2 C0.7 0 450 120.0 2 4.000 # 4: T1 A2 B2 1 C0.17 0 400 147.5 5 2.675 # 5: T2 A1 B1 7 C0.15 0 450 120.0 2 1.350 # 6: T2 A1 B2 5 C0.4 0 350 120.0 8 4.000 # 7: T2 A2 B1 3 C0.6 0 350 175.0 2 4.000 # 8: T2 A2 B2 6 C0.16 0 350 120.0 2 1.350 </code></pre>
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    1. COIt may have done with the sample data that I gave but when I use the code with the data I have, I get an erro. Error in '[.data.table'(dt2,dt1): typeof x.Temp (double) != typeof i.Block.ccd (integer)
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    2. COHi @Arun, my proposed table has 102 rows. Is the code above the only way to convert the data.frame to a data.table?
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    3. COHi @Arun, my real data returns, 'Error in `[.data.table`(dt2, dt1) : x.'Temp' is a factor column being joined to i.'Temp' which is type 'integer'. Factor columns must join to factor or character columns.'
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