scale_discrete#

scale_discrete(aesthetic, *, direction=None, name=None, breaks=None, labels=None, lablim=None, limits=None, na_value=None, guide=None, format=None, scale_mapper_kind=None, **kwargs)#

General purpose scale for discrete data. Use it to adjust most common properties of a default scale for given aesthetics.

Parameters:
aestheticstr or list

The name(s) of the aesthetic(s) that this scale works with.

direction{1, -1}, default=1

Set the order of colors in the scale. If 1, colors are as output by brewer palette. If -1, the order of colors is reversed.

namestr

The name of the scale - used as the axis label or the legend title. If None, the default, the name of the scale is taken from the first mapping used for that aesthetic.

breakslist or dict

A list of data values specifying the positions of ticks, or a dictionary which maps the tick labels to the breaks values.

labelslist of str or dict

A list of labels on ticks, or a dictionary which maps the breaks values to the tick labels.

lablimint, default=None

The maximum label length (in characters) before trimming is applied.

limitslist

A vector specifying the data range for the scale and the default order of their display in guides.

na_value

Missing values will be replaced with this value.

guide

Guide to use for this scale. It can either be a string (‘colorbar’, ‘legend’) or a call to a guide function (guide_colorbar(), guide_legend()) specifying additional arguments. ‘none’ will hide the guide.

formatstr

Define the format for labels on the scale. The syntax resembles Python’s:

  • ‘.2f’ -> ‘12.45’

  • ‘Num {}’ -> ‘Num 12.456789’

  • ‘TTL: {.2f}$’ -> ‘TTL: 12.45$’

For more info see Formatting.

scale_mapper_kind{‘identity’, ‘color_gradient’, ‘color_gradient2’, ‘color_gradientn’, ‘color_hue’, ‘color_grey’, ‘color_brewer’, ‘color_cmap’, ‘size_area’}

The type of the scale. If None (the default) and the scale is color, then ‘color_brewer’ will be used.

kwargs

Additional parameters for the specified scale type.

Returns:
FeatureSpec or FeatureSpecArray

Scales specification.

Notes

Define scale for discrete data to adjust properties for the specified aesthetics.

Examples

 1import numpy as np
 2from lets_plot import *
 3LetsPlot.setup_html()
 4np.random.seed(100)
 5n = 50
 6x = np.random.rand(n)
 7y = np.random.rand(n)
 8z = np.random.rand(n)
 9ggplot() + geom_point(aes(x, y, color=z, fill=z), shape=21, size=4) + \
10    scale_discrete(aesthetic=['color', 'fill'], guide='none')
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