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copied!<p>There's no need to split the data into data-frames by year; you can use the <code>ggplot2</code> package quite easily to differentiate the plots by year. First I'll make up some data:</p> <pre><code>dts <- as.Date("20050101", '%Y%m%d') + seq(0,1000,15) A <- data.frame( Dates = dts, Gas = 4000 + cumsum(abs( rnorm(length(dts), 100, 30)))) </code></pre> <p>Next I'll add two columns to <code>A</code>: <code>DayOfYear</code> which is the "day-number" within the year, and the <code>GasDiff</code> column (same as yours but generated more easily, <em>with no loops</em>!):</p> <pre><code>A <- transform( A, Year = format(Dates, '%Y'), DayOfYear = as.numeric( format(Dates, '%j')), GasDiff = c(diff( Gas ),NA)) </code></pre> <p>Next we use <code>ggplot2</code> to first plot all the years one after the other, but with different colors:</p> <pre><code>require(ggplot2) ggplot(A, aes(Dates, GasDiff)) + geom_line( aes(colour = Year)) </code></pre> <p>which gives you this: <img src="https://i.stack.imgur.com/k6F3P.png" alt="alt text"></p> <p>Alternatively you can plot the different years in a vertical grid:</p> <pre><code>ggplot(A, aes(DayOfYear, GasDiff)) + geom_line( ) + facet_grid(Year ~ .) </code></pre> <p>and you get this: <img src="https://i.stack.imgur.com/DGWRb.png" alt="alt text"></p> <p><strong><em>UPDATE:</em></strong> A third way is to plot all the years on the same plot with different colors/points, which may be useful if you are looking for seasonal patterns (but looks bad in my case because I made up random data).</p> <pre><code>ggplot(A, aes(DayOfYear, GasDiff)) + geom_line( aes(colour = Year) ) + geom_point( aes(shape = Year)) </code></pre> <p><img src="https://i.stack.imgur.com/qXJfy.png" alt="alt text"></p>

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