scale_color_discrete ¶

scale_color_discrete(
    direction: int | None = None,
    name: str | None = None,
    breaks: Breaks | None = None,
    labels: Labels | None = None,
    lablim: int | None = None,
    limits: Limits | None = None,
    na_value: Color | None = None,
    guide: Guide | None = None,
    format: str | None = None,
    scale_mapper_kind: str | None = None,
) -> FeatureSpec

Map color as categories with the default discrete palette.

Numbers become categories too, in order of first appearance.

Parameters:

direction ((1, -1), default: 1 ) –

-1 reverses the colors.
name (str, default: None ) –

Legend title.
breaks (list, default: None ) –

Categories that get a legend key.
labels (list of str or dict, default: None ) –

One label per break (a dict maps breaks to labels).
lablim (int, default: None ) –

Maximum label length in characters; longer labels are cut.
limits (list, default: None ) –

The categories and their order. Data outside the limits gets na_value.
na_value (str, default: None ) –

Color drawn for missing data and data outside limits.
guide (str or FeatureSpec, default: None ) –

"legend", "none", or a guide_legend() spec.
format (str, default: None ) –

Label format, e.g. ".1f". labels take precedence.
scale_mapper_kind (str, default: None ) –

Mapper that builds the colors, e.g. "color_brewer" or "color_hue".

Returns:

FeatureSpec –

The scale.

Examples:

>>> from ggrust import *
>>> data = {"age": [1, 3, 5, 7, 2, 4, 6, 8, 3, 9],
...         "weight": [4, 6, 6, 7, 8, 12, 14, 15, 2, 3],
...         "pet": ["cat"] * 4 + ["dog"] * 4 + ["rabbit"] * 2}
>>> plot = ggplot(data, aes("age", "weight", color="pet")) + geom_point(size=5)
>>> plot = plot + scale_color_discrete(name="Animal")