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tableau:tab10#

Aliases: seaborn:tab10

Tableau's classic "Tableau 10" palette, designed by Maureen Stone in 2004 for Tableau 1.5. Also d3's category10 and matplotlib's tab10 (its default color cycle).

collection category license authors source
tableau Qualitative UNKNOWN Maureen Stone https://public.tableau.com/app/profile/chris.gerrard/viz/TableauColors/ColorPaletteswithRGBValues 
from cmap import Colormap

cm = Colormap("tableau:tab10")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("tableau:tab10").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("tableau:tab10").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("tableau:tab10").to_napari())
napari.run()

background: #1F77B4;
background: linear-gradient(90deg, #1F77B4 10%, #FF7F0E 10%, #FF7F0E 20%, #2CA02C 20%, #2CA02C 30%, #D62728 30%, #D62728 40%, #9467BD 40%, #9467BD 50%, #8C564B 50%, #8C564B 60%, #E377C2 60%, #E377C2 70%, #7F7F7F 70%, #7F7F7F 80%, #BCBD22 80%, #BCBD22 90%, #17BECF 90%);

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:tab10").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:tab10").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:tab10").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:tab10").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("tableau:tab10").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:tab10").to_gee()
)

See also usage with external libraries.

tableau:tab10tableau:tab10 colormap
tableau:tab10tableau:tab10 colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#