Using colour in graphs and charts

Exercise 6.3.

On this page you’ll find some additional notes regarding the use of colour in graphs and charts. These items did not quite make the final edit to the book itself but make a useful (I hope) addition to the topic in Chapter 6.

• Introduction
• Using colour in Excel charts
  • Quick settings
  • Overall settings
  • Setting chart colours explicitly
• Using colour in R plots
  • Specifying colours
  • Setting a colour palette
  • Built-in colour palettes
  • Shading lines
• Summary

Colour is very important in presenting data and results. Both Excel and R have a wide range of colours you can use when creating your graphs and charts (certainly more than 50 shades of gray!).

Controlling and managing the colours you display is an important element in presenting your work. With an increasing volume of work being presented via the Internet, colour is something not to take for granted. Using default colours is “easy” but for maximum impact you should think carefully about how to present the best colours for the job.

Traditional journals generally use monochrome, which you can think of as just another set of colours, but even if you are “stuck” with shades of grey you need to think carefully. Pattern filling can be an especially useful option when using monochrome.

You can set colours in Excel in several ways:

• General color can be set from the Page Layout menu, which sets overall color themes.
• When you make a chart the Chart Tools > Design > Change Colors button allows you to “override” the general colors and set your own.
• You can format elements in charts directly from the Chart Tools > Format
• Right-click or double-click a chart element directly.

When you set a colour explicitly you can also incorporate fill effects, with Pattern Fill being the most useful.

R has over 650 named colors to choose from. You can see the colors using the colors() command.

colors() 
 [1] "white"          "aliceblue"      "antiquewhite"
 [4] "antiquewhite1"  "antiquewhite2"  "antiquewhite3"
 [7] "antiquewhite4"  "aquamarine"     "aquamarine1"
[10] "aquamarine2"    "aquamarine3"    "aquamarine4"
[13] "azure"          "azure1"         "azure2"
[16] "azure3"         "azure4"         "beige"
[19] "bisque"         "bisque1"        "bisque2"
[22] "bisque3"        "bisque4"        "black"
[25] "blanchedalmond" "blue"           "blue1"
[28] "blue2"          "blue3"          "blue4"

The colors used for most graphical commands are taken from a default palette, which can be different for different commands. For example the barplot() command uses shades of gray whilst the pie() command uses a palette of pastel shades.

In most graphical commands you can set the colors for the plot using the col parameter. Colors can be named explicitly or given numbers, in which case the numbers are taken to be the colors of the existing color palette().

You can set the colors of an R plot in several ways:

• Give color names (in quotes) as in the colors()
• Give numbers – the numbers will refer to the colors in the currently set palette().
• Give the name of a built-in color palette (and the number of shades).

You can set the colors directly in a plotting command using the col parameter and a vector of names (in quotes), for example:

> barplot(VADeaths, beside = TRUE,
col = c("aliceblue", "bisque", "coral", "seagreen", "tomato"))

If you plan to use the colors more than once you might want to save your vector of colors as a named object.

> mycol = c("aliceblue", "bisque", "coral", "seagreen", "tomato")
> pie(VADeaths[1,], col = mycol)

If you don’t provide enough colors then they are recycled. If there are too many colors the un-required ones are ignored.

If you give the colors as numbers the plotting command will take the colors from their position in the vector of colors that are in the color palette(), not the position of the color from the colors() command.

You can also use one of the built-in palettes by specifying the palette name and the number of shades needed.

The palette() command allows you to set a default color palette. The default palette() can be viewed using an empty command:

> palette()
[1] "black"   "red"     "green3"  "blue"    "cyan"
[6] "magenta" "yellow"  "gray"

Now, whenever a color is referred to by an integer value the color is taken as the position in the current palette(). Some plotting commands have their own default colors, which are used if you do not specify the colors explicitly.

• The barplot() command uses a palette() of gray.
• The pie() command uses a palette() of pastel shades.

You can set the palette() by giving a vector of colors:

> palette(mycol)
> palette()
[1] "aliceblue" "bisque"    "coral"     "seagreen"  "tomato"

To restore the default palette():

> palette("default")

You can make your own color palette() by specifying color names explicitly. However, R has several built-in palettes that you can use to create a series of “co-ordinated” colors.

There are six built-in palettes.

• rainbow()
• colors()
• colors()
• colors()
• colors()
• colors()

In general you specify how many colors you require in the palette and the command produces a series of colors graded across the range, however, with rainbow() and gray.colors() you can specify starting and ending points.

Type help(palette) to get more information from within R.

In some chart types it may be helpful to have shading lines, especially when using monochromatic color palettes. The barplot() and pie() commands allow you to specify shading lines from within the command. There are two parameters:

• density – gives the density of the shading lines in lines per inch. If not specified or negative the color is solid, even if angle is given.
• angle – gives the angle to draw the shading lines measured anti-clockwise, 0 is horizontal and the default is 45 degrees.

Shading is not available in the boxplot() command. If is rather less useful there anyhow, as the bars are all labelled. It is possible to find a solution using the polygon() command but this is not for the faint hearted.

Don’t just rely on the default colors for your graphs and charts. If you are presenting a graphic that uses color then think carefully about how easy it will be for readers to differentiate the colors. Think about the colors themselves, perhaps a particular color theme would be especially suitable for your presentation.

You can use color to highlight a particularly important finding, making some data stand out from the rest. You can also make some data “disappear” into obscurity!

For monochrome charts try a wide range so that individual series are identifiable. This is where pattern fills are especially useful.

Don’t forget that the purpose of your chart is to help a reader understand the data/results easily.