scale_fill_identity#

scale_fill_identity(name=None, breaks=None, labels=None, lablim=None, limits=None, na_value=None, guide='none', format=None)#

Use this scale when your data has already been scaled. I.e. it already represents aesthetic values that the library can handle directly. This will not produce a legend unless you also supply the breaks and labels.

Parameters:
namestr

The name of the scale - used as the axis label or the legend title.

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

Continuous scale: a numeric vector of length two providing limits of the scale. Discrete scale: a vector specifying the data range for the scale and the default order of their display in guides.

guide, default=’none’

Guide to use for this scale.

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.

Returns:
FeatureSpec

Scale specification.

Notes

For more info about input data format, see Color and Fill.

Examples

 1import numpy as np
 2from lets_plot import *
 3LetsPlot.setup_html()
 4np.random.seed(42)
 5colors = {'red': '#e41a1c', 'green': '#4daf4a', 'blue': '#377eb8'}
 6c = np.random.choice(list(colors.values()), size=20)
 7ggplot({'c': c}, aes(x='c')) + geom_bar(aes(fill='c')) + \
 8    scale_fill_identity(guide=guide_legend(), name='color', \
 9                        breaks=list(colors.values()), \
10                        labels=list(colors.keys()))
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