Colormaps¶

A palette is named wherever a theme asks for colors: the two general palettes, the heatmap colormap, and the parallel-coordinates hues. The name is resolved through pypalettes, which gives access to over 2500 palettes; the COLORS constant is a curated selection of them, rendered on this page. Which kind of palette a role wants:

Role	Attribute	Kind
Series sharing one axes	color_general_multiple	Categorical
Single-color roles (network nodes, parallel ramp)	color_general_singular	Sequential
Heatmap cells	plot_heatmap_cmap	Sequential
Heatmap cells under a centred norm	plot_heatmap_cmap_diverging	Diverging
Parallel-coordinates hue	color_parallel_hue, color_parallel_hue_continuous	Categorical, sequential

A palette asked for one color gives its last one, so a sequential palette yields one strong color and a graded set when several are asked for. The calendar heatmap, hexbin, and contour colormaps follow the heatmap's unless set. A heatmap drawn with norm="centered" or norm="twoslope" takes plot_heatmap_cmap_diverging in place of plot_heatmap_cmap, so a signed matrix reads its sign as a hue; see the Heatmap guide. See the Themes guide for setting these attributes and building a theme around them.

Each palette below is shown as a continuous strip and as the six colors a chart with six series receives; hover a swatch for its hex code. A palette is passed as its COLORS value, or as the plain name string.

In [1]:

from datachart.constants import COLORS

from datachart.constants import COLORS

Sequential, Single Hue¶

One hue from light to dark, ordered by magnitude. The natural color_general_singular palette: a role that needs one color takes the dark end. Also the safest heatmap colormap.

COLORS.Blues

COLORS.Greens

COLORS.Oranges

COLORS.Purples

COLORS.Reds

Sequential, Multiple Hues¶

Light to dark through two or more hues, which separates neighbouring values better than a single hue. Suited to heatmaps and value scales; the last color still serves a single series.

COLORS.YlGnBu

COLORS.YlOrRd

COLORS.YlOrBr

COLORS.PuBuGn

COLORS.GnBu

COLORS.BuPu

COLORS.PuBu

COLORS.Sunset2

COLORS.Egypt

COLORS.Hiroshige

COLORS.Lake

COLORS.Neon

Diverging¶

Two hues meeting at a neutral center, for values with a meaningful midpoint: differences from a baseline, correlations, gains and losses. Use with a heatmap norm centred on that value.

COLORS.RdBu

COLORS.BrBG

COLORS.PuOr

COLORS.Spectral

COLORS.RdYlBu

COLORS.RdYlGn

COLORS.Coolwarmcoolwarm

Categorical¶

Distinct hues of similar weight, for series that are different in kind rather than in amount: the color_general_multiple palette. The six colors shown are the ones six series receive.

COLORS.Set1

COLORS.Set2

COLORS.Dark2

COLORS.Accent

COLORS.Paired

COLORS.Pastel

COLORS.Tab10tab10

COLORS.Tab20tab20

Perceptually Uniform and Color-Blind Safe¶

Equal steps in value read as equal steps in color, and the palettes stay distinguishable under the common forms of color-vision deficiency. The first six are sequential, the Okabe-Ito pair categorical.

COLORS.Viridis

COLORS.Cividis

COLORS.Inferno

COLORS.Plasma

COLORS.Magmamagma

COLORS.Turboturbo

COLORS.OkabeIto

COLORS.OkabeIto_BlackOkabeIto_black

Greyscale¶

For print and black-and-white reproduction; the greyscale themes pair it with hatching or markers to keep series apart.

COLORS.Greys

Datachart's Own¶

Palettes registered by datachart rather than pypalettes: the two publication palettes of the ink theme, and the tuned categorical leads of the derived themes (harbor, muted, contrast, hatch and slate-hatch), each stepped so every pair of series stays apart for colour-blind readers. They cycle through their exact colors instead of interpolating, so the series colors are always the ones listed.

COLORS.PaperYlGnBu

COLORS.PaperAccent

COLORS.Harbor

COLORS.TolMuted

COLORS.Contrast

COLORS.Rust

COLORS.Slate

Beyond the Constant¶

Any pypalettes name works where a COLORS value does. So does a single matplotlib color, which is a palette of one and repeats for every series, and a list of hex colors, which cycles through its exact colors like datachart's own palettes. The list is how the predefined themes define most of their series palettes, and how a custom theme states its own:

In [11]:

palettes("Antique", "#B5651D", ["#0B3954", "#FF6663", "#E0FF4F"])

palettes("Antique", "#B5651D", ["#0B3954", "#FF6663", "#E0FF4F"])

"Antique"

"#B5651D"

[...]list of colors

Using a Palette in a Theme¶

A palette is set through the attributes in the table above, here for one figure with override; a theme sets the same attributes once. The heatmap takes its own colormap, the bars the general series palette:

In [12]:

from datachart.charts import BarChart, Heatmap
from datachart.config import config
from datachart.utils import Grid

CELLS = {"z": [[r * c for c in range(1, 8)] for r in range(1, 7)]}
BARS = [[{"label": f"Q{q}", "y": 30 + 12 * s + 7 * q} for q in range(1, 5)] for s in range(4)]

with config.override(plot_heatmap_cmap=COLORS.Cividis, color_general_multiple=COLORS.OkabeIto):
    Grid(
        [[
            Heatmap(data=CELLS, title="Cividis cells", show_values=True),
            BarChart(data=BARS, title="Okabe-Ito series", subtitle=["A", "B", "C", "D"], show_legend=True),
        ]],
        figsize=(9, 3.2),
    ).show()

from datachart.charts import BarChart, Heatmap from datachart.config import config from datachart.utils import Grid CELLS = {"z": [[r * c for c in range(1, 8)] for r in range(1, 7)]} BARS = [[{"label": f"Q{q}", "y": 30 + 12 * s + 7 * q} for q in range(1, 5)] for s in range(4)] with config.override(plot_heatmap_cmap=COLORS.Cividis, color_general_multiple=COLORS.OkabeIto): Grid( [[ Heatmap(data=CELLS, title="Cividis cells", show_values=True), BarChart(data=BARS, title="Okabe-Ito series", subtitle=["A", "B", "C", "D"], show_legend=True), ]], figsize=(9, 3.2), ).show()