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Choose an appropriate plot for the data you want to represent.
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Always add a title and axis labels. These should be in plain English, not variable names!
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Specify units after the axis label if the axis has units. For instance, "Height (ft)".
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Don't forget that many people are colorblind! Also, plots are often printed in black and white. Use point (
pch) and line (lty) styles to distinguish groups; color is optional. -
Add a legend whenever you've used more than one point or line style.
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Always write a few sentences explaining what the plot reveals. Don't describe the plot, because the reader can just look at it. Instead, explain what they can learn from the plot and point out important details that are easily overlooked.
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Sometimes points get plotted on top of each other. This is called overplotting. Plots with a lot of overplotting can be hard to read and can even misrepresent the data by hiding how many points are present. Use a smooth scatter plot or jitter the points to deal with overplotting.
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For side-by-side plots, use the same axis scales for both plots so that comparing them is not deceptive.
What plot is appropriate?
| Variable | Versus | Plot |
|---|---|---|
| numerical | box, histogram, density | |
| categorical | bar, dot | |
| categorical | categorical | mosaic, bar, dot |
| numerical | categorical | box, density |
| numerical | numerical | scatter, smooth scatter, line |
If you want to add:
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3rd numerical variable, use it to change point/line sizes.
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3rd categorical variable, use it to change point/line styles.
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4th categorical variable, use side-by-side plots.
Before plotting, use par() to change general plot settings. Many of the
parameters for par() can also be used as parameters in the plotting
functions, so take a look at ?par.
Functions for making plots:
| Function | Purpose |
|---|---|
| plot() | general plot function |
| barplot() | bar plot |
| dotchart() | dot chart (use instead of bar plot or pie chart) |
| boxplot() | box and whisker plot |
| hist() | histogram |
| plot(density(...)) | density plot |
| mosaicplot() | mosaic plot |
| pairs() | matrix of scatterplots |
| matplot() | grouped scatterplot |
| smoothScatter() | smooth scatterplot |
| stripchart() | one-dimensional scatterplot |
| curve() | plot a function |
Functions for customizing plots:
| Function | Purpose |
|---|---|
| lines() | add lines to a plot |
| arrows() | add arrows to a plot |
| points() | add points to a plot |
| abline() | add straight lines to a plot |
| legend() | add legends to a plot |
| title() | add title or labels to a plot |
| axis() | add axes to a plot |
Lattice has plotting functions similar to R's built-in plotting functions.
| R Built-in | Lattice |
|---|---|
| plot() | xyplot() |
| barplot() | barchart() |
| dotchart() | dotplot() |
| boxplot() | bwplot() |
| hist() | histogram() |
| plot(density()) | densityplot() |
All of the lattice functions use formula notation:
y ~ x | group
The "group" in the formula makes side-by-side plots, with one for each group. Sometimes side-by-side plots are called faceted plots.
The lattice functions also a have a separate groups parameter for marking groups within a single plot.
Setting the auto.key parameter to TRUE tells lattice to add a legend.
It's possible to use both groupings at once.
The drawback of lattice is that LATTICE DOES NOT WORK WITH THE BUILT-IN PLOTTING FUNCTIONS!!!
Documentation for ggplot2 is available here.