tableau:tab20c#

Aliases: seaborn:tab20c

d3's category20c palette (also matplotlib's tab20c).

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:tab20c")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("tableau:tab20c").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("tableau:tab20c").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("tableau:tab20c").to_napari())
napari.run()

background: #3182BD;
background: linear-gradient(90deg, #3182BD 5%, #6BAED6 5%, #6BAED6 10%, #9ECAE1 10%, #9ECAE1 15%, #C6DBEF 15%, #C6DBEF 20%, #E6550D 20%, #E6550D 25%, #FD8D3C 25%, #FD8D3C 30%, #FDAE6B 30%, #FDAE6B 35%, #FDD0A2 35%, #FDD0A2 40%, #31A354 40%, #31A354 45%, #74C476 45%, #74C476 50%, #A1D99B 50%, #A1D99B 55%, #C7E9C0 55%, #C7E9C0 60%, #756BB1 60%, #756BB1 65%, #9E9AC8 65%, #9E9AC8 70%, #BCBDDC 70%, #BCBDDC 75%, #DADAEB 75%, #DADAEB 80%, #636363 80%, #636363 85%, #969696 85%, #969696 90%, #BDBDBD 90%, #BDBDBD 95%, #D9D9D9 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:tab20c").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:tab20c").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:tab20c").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:tab20c").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("tableau:tab20c").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:tab20c").to_gee()
)

Perceptual lightness#

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

tableau:tab20c#

Perceptual lightness#

RGB components#

Hue & saturation#