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    <p>There are many ways to do this. This answer starts with my favorite ways, but also collects various ways from answers to similar questions scattered around this site.</p> <pre><code>tmp &lt;- data.frame(x=gl(2,3, labels=letters[24:25]), y=gl(3,1,6, labels=letters[1:3]), z=c(1,2,3,3,3,2)) </code></pre> <p>Using reshape2:</p> <pre><code>library(reshape2) acast(tmp, x~y, value.var="z") </code></pre> <p>Using matrix indexing:</p> <pre><code>with(tmp, { out &lt;- matrix(nrow=nlevels(x), ncol=nlevels(y), dimnames=list(levels(x), levels(y))) out[cbind(x, y)] &lt;- z out }) </code></pre> <p>Using <code>xtabs</code>:</p> <pre><code>xtabs(z~x+y, data=tmp) </code></pre> <p>You can also use <code>reshape</code>, as suggested here: <a href="https://stackoverflow.com/q/2126108/210673">Convert table into matrix by column names</a>, though you have to do a little manipulation afterwards to remove an extra columns and get the names right (not shown).</p> <pre><code>&gt; reshape(tmp, idvar="x", timevar="y", direction="wide") x z.a z.b z.c 1 x 1 2 3 4 y 3 3 2 </code></pre> <p>There's also <code>sparseMatrix</code> within the <code>Matrix</code> package, as seen here: <a href="https://stackoverflow.com/q/9833052/210673">R - convert BIG table into matrix by column names</a></p> <pre><code>&gt; with(tmp, sparseMatrix(i = as.numeric(x), j=as.numeric(y), x=z, + dimnames=list(levels(x), levels(y)))) 2 x 3 sparse Matrix of class "dgCMatrix" a b c x 1 2 3 y 3 3 2 </code></pre> <p>The <code>daply</code> function from the <code>plyr</code> library could also be used, as here: <a href="https://stackoverflow.com/a/7020101/210673">https://stackoverflow.com/a/7020101/210673</a></p> <pre><code>&gt; library(plyr) &gt; daply(tmp, .(x, y), function(x) x$z) y x a b c x 1 2 3 y 3 3 2 </code></pre> <p><code>dcast</code> from reshape2 also works, as here: <a href="https://stackoverflow.com/q/8093839/210673">Reshape data for values in one column</a>, but you get a data.frame with a column for the <code>x</code> value.</p> <pre><code>&gt; dcast(tmp, x~y, value.var="z") x a b c 1 x 1 2 3 2 y 3 3 2 </code></pre> <p>Similarly, <code>spread</code> from "tidyr" would also work for such a transformation:</p> <pre><code>library(tidyr) spread(tmp, y, z) # x a b c # 1 x 1 2 3 # 2 y 3 3 2 </code></pre>
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