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copied!<p>Personally, I prefer "one" liners. Something along the lines:</p> <pre><code>my.df <- data.frame(col1 = sample(c(1,2), 10, replace = TRUE), col2 = as.factor(sample(10)), col3 = letters[1:10], col4 = sample(c(TRUE, FALSE), 10, replace = TRUE)) my.list <- list(list1 = my.df, list2 = my.df[3], list3 = letters) </code></pre> <p>The data structure should mimic the idea of writer's problem and not the exact verbatim structure. I really appreciate it when variables don't overwrite my own variables or god forbid, functions (like <code>df</code>).</p> <p>Alternatively, one could cut a few corners and point to a pre-existing data set, something like:</p> <pre><code>library(vegan) data(varespec) ord <- metaMDS(varespec) </code></pre> <p>Don't forget to mention any special packages you might be using.</p> <p>If you're trying to demonstrate something on larger objects, you can try</p> <pre><code>my.df2 <- data.frame(a = sample(10e6), b = sample(letters, 10e6, replace = TRUE)) </code></pre> <p>If you're working with spatial data via the <code>raster</code> package, you can generate some random data. A lot of examples can be found in the package vignette, but here's a small nugget.</p> <pre><code>library(raster) r1 <- r2 <- r3 <- raster(nrow=10, ncol=10) values(r1) <- runif(ncell(r1)) values(r2) <- runif(ncell(r2)) values(r3) <- runif(ncell(r3)) s <- stack(r1, r2, r3) </code></pre> <p>If you're in need of some spatial object as implemented in <code>sp</code>, you can get some datasets via external files (like ESRI shapefile) in "spatial" packages (see the Spatial view in Task Views).</p> <pre><code>library(rgdal) ogrDrivers() dsn <- system.file("vectors", package = "rgdal")[1] ogrListLayers(dsn) ogrInfo(dsn=dsn, layer="cities") cities <- readOGR(dsn=dsn, layer="cities") </code></pre>

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