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    <p>I do a lot of basic manipulation of data, so here are two built-in functions ( <strong>transform</strong> , <strong>subset</strong> ) and one library ( <strong>sqldf</strong> ) that I use daily.</p> <h2>create sample sales data</h2> <pre><code>sales &lt;- expand.grid(country = c('USA', 'UK', 'FR'), product = c(1, 2, 3)) sales$revenue &lt;- rnorm(dim(sales)[1], mean=100, sd=10) &gt; sales country product revenue 1 USA 1 108.45965 2 UK 1 97.07981 3 FR 1 99.66225 4 USA 2 100.34754 5 UK 2 87.12262 6 FR 2 112.86084 7 USA 3 95.87880 8 UK 3 96.43581 9 FR 3 94.59259 </code></pre> <h2>use transform() to add a column</h2> <pre><code>## transform currency to euros usd2eur &lt;- 1.434 transform(sales, euro = revenue * usd2eur) &gt; country product revenue euro 1 USA 1 108.45965 155.5311 2 UK 1 97.07981 139.2125 3 FR 1 99.66225 142.9157 ... </code></pre> <h2>use subset() to slice the data</h2> <pre><code>subset(sales, country == 'USA' &amp; product %in% c(1, 2), select = c('product', 'revenue')) &gt; product revenue 1 1 108.4597 4 2 100.3475 </code></pre> <h2>use sqldf() to slice and aggregate with SQL</h2> <p>The <a href="http://code.google.com/p/sqldf/" rel="nofollow noreferrer">sqldf package</a> provides an SQL interface to R data frames</p> <pre><code>## recast the previous subset() expression in SQL sqldf('SELECT product, revenue FROM sales \ WHERE country = "USA" \ AND product IN (1,2)') &gt; product revenue 1 1 108.4597 2 2 100.3475 </code></pre> <p>Perform an aggregation or GROUP BY</p> <pre><code>sqldf('select country, sum(revenue) revenue \ FROM sales \ GROUP BY country') &gt; country revenue 1 FR 307.1157 2 UK 280.6382 3 USA 304.6860 </code></pre> <p>For more sophisticated map-reduce-like functionality on data frames, check out the <a href="http://crantastic.org/packages/plyr" rel="nofollow noreferrer">plyr</a> package. And if find yourself wanting to pull your hair out, I recommend checking out <a href="http://rads.stackoverflow.com/amzn/click/0387747303" rel="nofollow noreferrer">Data Manipulation with R</a>.</p>
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