plotnine.scales.scale_fill_brewer

class plotnine.scales.scale_fill_brewer(type='seq', palette=1, direction: Literal[1, -1] = 1, **kwargs)

Sequential, diverging and qualitative color scales

Parameters:

typestr in ['seq', 'div', 'qual']

Type of data. Sequential, diverging or qualitative

paletteint | str

If a string, will use that named palette. If a number, will index into the list of palettes of appropriate type. Default is 1

direction: int in ``[-1, 1]``

Sets the order of colors in the scale. If 1, the default, colors are as output by mizani.palettes.brewer_pal(). If -1, the order of colors is reversed.

breaksarray_like or callable(), optional

Major break points. Alternatively, a callable that takes a tuple of limits and returns a list of breaks. Default is to automatically calculate the breaks.

expandtuple, optional

Multiplicative and additive expansion constants that determine how the scale is expanded. If specified must be of length 2 or 4. Specifically the values are in this order:

(mul, add)
(mul_low, add_low, mul_high, add_high)

For example,

• (0, 0) - Do not expand.

• (0, 1) - Expand lower and upper limits by 1 unit.

• (1, 0) - Expand lower and upper limits by 100%.

• (0, 0, 0, 0) - Do not expand, as (0, 0).

• (0, 0, 0, 1) - Expand upper limit by 1 unit.

• (0, 1, 0.1, 0) - Expand lower limit by 1 unit and upper limit by 10%.

• (0, 0, 0.1, 2) - Expand upper limit by 10% plus 2 units.

If not specified, suitable defaults are chosen.

namestr, optional

Name used as the label of the scale. This is what shows up as the axis label or legend title. Suitable defaults are chosen depending on the type of scale.

labelslist or callable(), optional

List of str. Labels at the breaks. Alternatively, a callable that takes an array_like of break points as input and returns a list of strings.

aestheticslist, optional

list of str. Aesthetics covered by the scale. These are defined by each scale and the user should probably not change them. Have fun.

limitsarray_like, optional

Limits of the scale. For scales that deal with categoricals, these may be a subset or superset of the categories. Data values that are not in the limits will be treated as missing data and represented with the na_value.

dropbool

Whether to drop unused categories from the scale

na_translatebool

If True translate missing values and show them. If False remove missing values. Default value is True

na_valuestr

Color of missing values. Default is 'None'