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Every scale is associated with a guide that displays the relationship between the aesthetic and the data. For position scales, the axes serve this function. For colour scales this role is played by the legend, which can be customised with the help of a guide function. There are many arguments to this function, allowing you to exercise precise control over the legend. The most important arguments are illustrated below:. These are grid units, e. In Section When applied to colour scales, it allows you to create custom legends like these:.
An alternative way to accomplish the same goal is to specify the guide argument to the scale function. These two plot specifications are identical:.
You can learn more about guide functions in Section Discrete colour and fill scales occur in many situations. A typical example is a barchart that encodes both position and fill to the same variable. Many concepts from Section These colours have been designed to work well in a wide variety of situations, although the focus is on maps and so the colours tend to work better when displayed in large areas.
There are many different options:. The first group of palettes are sequential scales that are useful when your discrete scale is ordered e.
For unordered categorical data, the palettes of most interest are those in the second group. Note that no palette is uniformly good for all purposes. Scatter plots typically use small plot markers, and bright colours tend to work better than subtle ones:.
Bar plots usually contain large patches of colour, and bright colours can be overwhelming. Subtle colours tend to work better in this situation:.
The default colour scheme picks evenly spaced hues around the HCL colour wheel. This works well for up to about eight colours, but after that it becomes hard to tell the different colours apart.
You can control the default chroma and luminance, and the range of hues, with the h , c and l arguments:. There are some problems with this default scheme. One is that unlike many of the other palettes discussed in this chapter, they are not colour blind safe discussed in Section A second is that because the colours all have the same luminance and chroma, they all appear as an identical shade of grey when printed in black and white.
Another alternative is provided by the paletteer package, discussed earlier in connection to continuous colour scales in Section By providing a unified interface that spans a large number of packages, paletteer makes it possible to choose among a very large number of palettes in a consistent way:. This can be useful if you wish to choose colours that highlight a secondary grouping structure or draw attention to different comparisons:.
You can also use a named vector to specify colors to be assigned to each level which allows you to specify the levels in any order you like:. For more information about manual scales see Section Scale limits for discrete colour scales can be set using the limits argument to the scale argument, or by using the lims helper function.
This can be important when the same variable is represented in different plots, and you want to ensure that the colours are consistent across plots. Colour represents the fuel type, which can be r egular, e thanol, d iesel, p remium or c ompressed natural gas.
Each plot makes sense on its own, but visual comparison between the two is difficult. The axis limits are different, and because only regular, premium and diesel fuels are represented in the data the colours are mapped inconsistently. To ensure a consistent mapping for the colour aesthetic, we can use lims to manually set the limits. As discussed in Section The nice thing about lims is that we can set the limits for multiple aesthetics at once. To ensure that x, y, and colour all use consistent limits we can do this:.
There are two potential limitations to these plots. First, while setting the scale limits does ensure that colours are mapped identically in both plots, it also means that the plot for the data displays labels for all five fuel types, despite the fact that ethanol and compressed natural gas fuels were not in use at that time. We can address this by manually setting the scale breaks, ensuring that only those fuel types that appear in the data are shown in the legend.
The second limitation is that the labels are not particularly helpful, which we can address by specifying them manually. When setting multiple properties of a single scale, it can be more useful to customise using the arguments to the scale function rather than using the lims helper function:.
Legends for discrete colour scales can be customised using the guide argument to the scale function or with the guides helper function, described in Section The most useful options are:. Colour scales also come in binned versions. As with the binned position scales discussed in Section Counterintuitively—because the human visual system is very good at detecting edges—this can sometimes make a continuous colour gradient easier to perceive:.
In most respects setting limits, breaks, and labels for a binned scale follows the same logic that applies to continuous scales Sections Like a continuous scale, the limits argument is typically a numeric vector of length two specifying the end points, breaks is a numeric vector specifying the break points, and labels is a character vector specifying the labels. All three arguments will accept functions as input discussed in Section The main difference between binned and continuous scales is that the breaks argument defines the edges of the bins rather than simply specifying locations of tick marks.
A colour step legend shows the area between breaks as a single constant colour, rather than displaying a colour gradient that varies smoothly along the bar. These are designed to handle date data, analogous to the date scales discussed in Section Alpha scales map the transparency of a shade to a value in the data. They are not often useful, but can be a convenient way to visually down-weight less important observations.
An example of an alpha scale using the eruptions data is shown below:. A number of settings that affect the overall display of the legends are controlled through the theme system. The position and justification of legends are controlled by the theme setting legend. If needed, you can adjust those options independently:. You can do this by setting legend. The numbers represent a relative location in the panel area: c 0, 1 is the top-left corner and c 1, 0 is the bottom-right corner.
You control which corner of the legend the legend. Unfortunately positioning the legend exactly where you want it requires a lot of trial and error.
Luminance is the lightness of the colour, ranging from 0 black to 1 white. Also accepts rlang lambda function notation. Should unused factor levels be omitted from the scale? Unlike continuous scales, discrete scales can easily show missing values, and do so by default. If you want to remove missing values from a discrete scale, specify na. The name of the scale.
Used as the axis or legend title. If waiver , the default, the name of the scale is taken from the first mapping used for that aesthetic. If NULL , the legend title will be omitted. A function that takes the breaks as input and returns labels as output. The values will be matched in order usually alphabetical with the limits of the scale, or with breaks if provided. If this is a named vector, then the values will be matched based on the names instead.
Data values that don't match will be given na. Character string or vector of character strings listing the name s of the aesthetic s that this scale works with. Many color palettes derived from RGB combinations like the "rainbow" color palette are not suitable to support all viewers, especially those with color vision deficiencies. Using viridis type, which is perceptually uniform in both colour and black-and-white display is an easy option to ensure good perceptive properties of your visulizations.
The colorspace package offers functionalities. For more information on color vision deficiencies and suitable color choices see the paper on the colorspace package and references therein. For more information on customizing the embed code, read Embedding Snippets. Functions Source code Man pages
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