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description: A reference for the built-in named continuous (sequential, diverging and cylclical) colorscales in Plotly.

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name: Built-in Continuous Colorscales

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permalink: python/builtin-colorscales/

thumbnail: thumbnail/heatmap_colorscale.jpg

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Many Plotly Express functions accept a `color_continuous_scale` argument and many trace

types have a `colorscale` attribute in their schema. Plotly comes with a large number of

built-in continuous colorscales, which can be referred to in Python code when setting the above arguments,

either by name in a case-insensitive string e.g. `px.scatter(continuous_color_scale="Viridis"`) or by reference e.g.

`go.Scatter(marker_colorscale=plotly.colors.sequential.Viridis)`. They can also be reversed by adding `_r` at the end

e.g. `"Viridis_r"` or `plotly.colors.sequential.Viridis_r`.

The `plotly.colours` module is also available under `plotly.express.colors` so you can refer to it as `px.colors`.

When using continuous colorscales, you will often want to [configure various aspects of its range and colorbar](/python/colorscales/).

You can use any of the following names as string values to set `continuous_color_scale` or `colorscale` arguments.

These strings are case-insensitive and you can append `_r` to them to reverse the order of the scale.

import plotly.express as px

print("".join('{:<12}'.format(c) for c in px.colors.named_colorscales()))

A collection of predefined sequential colorscales is provided in the `plotly.colors.sequential` module. Sequential color scales are appropriate for most continuous data, but in some cases it can be helpful to use a diverging or cyclical color scale (see below).

Here are all the built-in scales in the `plotly.colors.sequential` module:

import plotly.express as px

fig = px.colors.sequential.swatches()

fig.show()

Note: `RdBu` was included in this module by mistake, even though it is a diverging color scale.

It is intentionally left in for backwards-compatibility reasons.

A collection of predefined diverging colorscales is provided in the `plotly.colors.diverging` module.

Diverging color scales are appropriate for continuous data that has a natural midpoint

other otherwise informative special value, such as 0 altitude, or the boiling point

of a liquid. These scales are intended to be used when [explicitly setting the midpoint of the scale](/python/colorscales/#setting-the-midpoint-of-a-diverging-colorscale).

Here are all the built-in scales in the `plotly.colors.diverging` module:

import plotly.express as px

fig = px.colors.diverging.swatches()

fig.show()

A collection of predefined cyclical colorscales is provided in the `plotly.colors.cyclical` module.

Cyclical color scales are appropriate for continuous data that has a natural cyclical

structure, such as temporal data (hour of day, day of week, day of year, seasons) or

complex numbers or other phase or angular data.

Here are all the built-in scales in the `plotly.colors.cyclical` module:

import plotly.express as px

fig = px.colors.cyclical.swatches()

fig.show()

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