tableau:tab20b#

Aliases: seaborn:tab20b

d3's category20b palette (also matplotlib's tab20b).

collection	category	license	authors	source
tableau	Qualitative	UNKNOWN		https://github.com/d3/d3-3.x-api-reference/blob/master/Ordinal-Scales.md

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

cm = Colormap("tableau:tab20b")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("tableau:tab20b").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("tableau:tab20b").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("tableau:tab20b").to_napari())
napari.run()

background: #393B79;
background: linear-gradient(90deg, #393B79 5%, #5254A3 5%, #5254A3 10%, #6B6ECF 10%, #6B6ECF 15%, #9C9EDE 15%, #9C9EDE 20%, #637939 20%, #637939 25%, #8CA252 25%, #8CA252 30%, #B5CF6B 30%, #B5CF6B 35%, #CEDB9C 35%, #CEDB9C 40%, #8C6D31 40%, #8C6D31 45%, #BD9E39 45%, #BD9E39 50%, #E7BA52 50%, #E7BA52 55%, #E7CB94 55%, #E7CB94 60%, #843C39 60%, #843C39 65%, #AD494A 65%, #AD494A 70%, #D6616B 70%, #D6616B 75%, #E7969C 75%, #E7969C 80%, #7B4173 80%, #7B4173 85%, #A55194 85%, #A55194 90%, #CE6DBD 90%, #CE6DBD 95%, #DE9ED6 95%);

altairbokehvispypygfxpyqtgraphEarth Engine

import altair as alt
from cmap import Colormap

# df: a DataFrame with columns x, y and value
alt.Chart(df).mark_rect().encode(
    x="x:O",
    y="y:O",
    color=alt.Color(
        "value:Q", scale=alt.Scale(range=Colormap("tableau:tab20b").to_altair())
    ),
)

from bokeh.plotting import figure, show
from cmap import Colormap

p = figure()
p.image(
    image=[data], x=0, y=0, dw=1, dh=1,
    color_mapper=Colormap("tableau:tab20b").to_bokeh(),
)
show(p)

from vispy import app, scene
from cmap import Colormap

canvas = scene.SceneCanvas(show=True)
view = canvas.central_widget.add_view()
scene.visuals.Image(data, cmap=Colormap("tableau:tab20b").to_vispy(), parent=view.scene)
view.camera = scene.PanZoomCamera(aspect=1)
view.camera.set_range()
app.run()

import pygfx as gfx
from cmap import Colormap

image = gfx.Image(
    gfx.Geometry(grid=gfx.Texture(data, dim=2)),
    gfx.ImageBasicMaterial(
        clim=(data.min(), data.max()), map=Colormap("tableau:tab20b").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("tableau:tab20b").to_pyqtgraph())
pg.exec()

import ee
from cmap import Colormap

ee.Initialize(project="my-project")  # your Google Cloud project
elevation = ee.Image("CGIAR/SRTM90_V4")
image = elevation.visualize(
    min=0, max=3000, palette=Colormap("tableau:tab20b").to_gee()
)

Perceptual lightness#

Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)

tableau:tab20b#

Perceptual lightness#

RGB components#

Hue & saturation#