lets_plot.scale_color_discrete#
- lets_plot.scale_color_discrete(direction=None, name=None, breaks=None, labels=None, lablim=None, limits=None, na_value=None, guide=None, format=None, scale_mapper_kind=None, **kwargs)#
Color scale for color aesthetic and discrete data.
- Parameters:
- direction{1, -1}, default=1
Set the order of colors in the scale. If 1, colors are as output by original 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 https://lets-plot.org/python/pages/formats.html.
- scale_mapper_kind{‘color_gradient’, ‘color_gradient2’, ‘color_gradientn’, ‘color_hue’, ‘color_grey’, ‘color_brewer’, ‘color_cmap’}
The type of color scale. If None (the default), then ‘color_brewer’ will be used.
- kwargs:
Additional parameters for the specified scale type.
- Returns:
- FeatureSpec
Scale specification.
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), size=4) + \ 10 scale_color_discrete(guide='none')