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    <p>The answers so far work to a certain degree, but don't fully answer your question. In particular, they don't address the issue of a case in which there are no shops which sold a particular product. From your example input and desired output, there were no shops which sold "Product3". Indeed, "Product3" does not even appear in your source <code>data.frame</code>. Additionally, they do not address the possible situation of having more than one row for each Shop + Product combination.</p> <p>Here's a modified version of your data and the two solutions so far. I've added another row for a combination of "Shop1" and "Product1". Notice that I have converted your products to a <code>factor</code> variable that includes the levels that the variable can take, even if none of the cases actually has that level.</p> <pre><code>mydf &lt;- data.frame( Shop.Name = c("Shop1", "Shop1", "Shop2", "Shop3", "Shop3", "Shop1"), Items = c(2, 4, 3, 2, 1, 2), Product = factor( c("Product1", "Product2", "Product1", "Product1", "Product4", "Product1"), levels = c("Product1", "Product2", "Product3", "Product4"))) </code></pre> <ol> <li><p><code>dcast</code> from "reshape2"</p> <pre><code>library(reshape2) dcast(mydf, formula = Shop.Name ~ Product, value="Items", fill=0) # Using Product as value column: use value.var to override. # Aggregation function missing: defaulting to length # Error in .fun(.value[i], ...) : # 2 arguments passed to 'length' which requires 1 </code></pre> <p>Wha? Suddenly does not work. Do this instead:</p> <pre><code>dcast(mydf, formula = Shop.Name ~ Product, fill = 0, value.var = "Items", fun.aggregate = sum, drop = FALSE) # Shop.Name Product1 Product2 Product3 Product4 # 1 Shop1 4 4 0 0 # 2 Shop2 3 0 0 0 # 3 Shop3 2 0 0 1 </code></pre></li> <li><p>Let's be oldschool. <code>cast</code> from "reshape"</p> <pre><code>library(reshape) cast(mydf, formula = Shop.Name ~ Product, value="Items", fill=0) # Aggregation requires fun.aggregate: length used as default # Shop.Name Product1 Product2 Product4 # 1 Shop1 2 1 0 # 2 Shop2 1 0 0 # 3 Shop3 1 0 1 </code></pre> <p>Eh. Not what you wanted again... Try this instead:</p> <pre><code>cast(mydf, formula = Shop.Name ~ Product, value = "Items", fill = 0, add.missing = TRUE, fun.aggregate = sum) # Shop.Name Product1 Product2 Product3 Product4 # 1 Shop1 4 4 0 0 # 2 Shop2 3 0 0 0 # 3 Shop3 2 0 0 1 </code></pre></li> <li><p>Let's get back to basics. <code>xtabs</code> from base R</p> <pre><code>xtabs(Items ~ Shop.Name + Product, mydf) # Product # Shop.Name Product1 Product2 Product3 Product4 # Shop1 4 4 0 0 # Shop2 3 0 0 0 # Shop3 2 0 0 1 </code></pre> <p>Or, if you prefer a <code>data.frame</code> (note that your "Shop.Name" variable has been converted to the <code>row.names</code> of the <code>data.frame</code>):</p> <pre><code>as.data.frame.matrix(xtabs(Items ~ Shop.Name + Product, mydf)) # Product1 Product2 Product3 Product4 # Shop1 4 4 0 0 # Shop2 3 0 0 0 # Shop3 2 0 0 1 </code></pre></li> </ol>
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    1. COThis is a bit more comprehensive than the other solutions posted in http://stackoverflow.com/questions/9617348/reshape-three-column-data-frame-to-matrix
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