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POPlotting data frame column values as facet columns
 

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  1. POPlotting data frame column values as facet columns
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    <p>I have a data frame of survey data in the following form:</p> <pre><code> category shift difficulty importance frequency dsmImportance supervisor 1 Monitoring Day 3 1 1 3 Debra Smith 2 Monitoring Day 2 1 1 3 Debra Smith 3 Paperwork Night 3 1 1 3 Mark Hobbs 4 Operations Day 1 1 1 2 Ryan Jones 5 Rostering Night 1 1 1 1 Mark Hobbs </code></pre> <p>The data is a survey of tasks performed during a work shift, with a rating of 1-3 assigned according to each tasks' difficulty, importance, etc. </p> <p>What I'd like to do is plot an array of histograms of the task ratings, with <code>difficulty</code>, <code>importance</code>, <code>frequency</code> and <code>dsmImportance</code> for the array columns and <code>category</code> for the rows. My approach so far has been to create single columns for each rating type (<code>difficulty</code>, <code>importance</code> etc.) faceted with <code>category</code>, and then group the columns together using <code>grid_layout()</code>. You can see the result <a href="http://imgur.com/4OSgO" rel="nofollow">here</a>. (Unfortunately I'm prevented from linking directly to an image until I've been a member for longer.) It works but it's not terribly pretty.</p> <p><strong>How do I go about creating the array entirely using <code>ggplot2</code>'s faceting function?</strong> I'm new to R (and stack overflow) but I'm fairly sure I can't do this with the data in the form that it's currently in. I presume I have to melt the data and cast it into a different form, but I don't know what that form should be.</p> <h2>Code</h2> <pre><code>library(ggplot2) library(gridExtra) walkaday.dirty = read.csv("~/Documents/walkaday.csv", header = TRUE, sep = ",", fill = TRUE, blank.lines.skip = TRUE) walkaday = na.omit(walkaday.dirty) // Order category levels by task frequency category.levels = names(sort(table(walkaday$category), decreasing = TRUE)) walkaday$category = factor(walkaday$category, levels = category.levels) </code></pre> <h3>Difficulty chart</h3> <pre><code>difficulty = ggplot(walkaday, aes(factor(difficulty, c("3", "2", "1")), fill = difficulty)) + geom_bar() + coord_flip() + xlab("") + ylab("") + opts(legend.position = "none") difficulty = difficulty + facet_grid(category ~ .) + opts(strip.text.y = theme_blank()) </code></pre> <h3>Importance chart</h3> <pre><code>importance = ggplot(walkaday, aes(factor(importance, c("3", "2", "1")), fill = importance)) + geom_bar() + coord_flip() + xlab("") + ylab("") + opts(legend.position = "none", axis.text.y = theme_blank(), axis.ticks = theme_blank()) importance = importance + facet_grid(category ~ .) + opts(strip.text.y = theme_blank()) </code></pre> <h3>Frequency chart</h3> <pre><code>frequency = ggplot(walkaday, aes(factor(frequency, c("3", "2", "1")), fill = frequency)) + geom_bar() + coord_flip() + xlab("") + ylab("") + opts(legend.position = "none", axis.text.y = theme_blank(), axis.ticks = theme_blank()) frequency = frequency + facet_grid(category ~ .) + opts(strip.text.y = theme_blank()) </code></pre> <h3>DSM Importance chart</h3> <pre><code>dsmImportance = ggplot(walkaday, aes(factor(dsmImportance, c("3", "2", "1")), fill = dsmImportance)) + geom_bar() + coord_flip() + xlab("") + ylab("") + opts(legend.position = "none", axis.text.y = theme_blank(), axis.ticks = theme_blank()) dsmImportance = dsmImportance + facet_grid(category ~ .) + opts(strip.text.y = theme_text(angle = 0)) </code></pre> <h3>Combine charts</h3> <pre><code>pushViewport(viewport(layout = grid.layout(1, 4, widths = c(1,1,1,1.7)))) print(difficulty + opts(title = "Task difficulty"), vp = viewport(layout.pos.row = 1, layout.pos.col = 1)) print(importance + opts(title = "Task importance"), vp = viewport(layout.pos.row = 1, layout.pos.col = 2)) print(frequency + opts(title = "Task frequency"), vp = viewport(layout.pos.row = 1, layout.pos.col = 3)) print(dsmImportance + opts(title = "DSM importance"), vp = viewport(layout.pos.row = 1, layout.pos.col = 4)) </code></pre> <h2>Data</h2> <p>The dataset can be found <a href="http://dl.dropbox.com/u/7046039/walkaday.csv" rel="nofollow">here</a>.</p>
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