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adding built-in colorscales reference page
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‎doc/python/builtin-colorscales.md

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---
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jupyter:
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jupytext:
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notebook_metadata_filter: all
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text_representation:
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extension: .md
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format_name: markdown
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format_version: "1.2"
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jupytext_version: 1.3.0
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kernelspec:
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display_name: Python 3
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language: python
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name: python3
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language_info:
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codemirror_mode:
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name: ipython
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version: 3
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file_extension: .py
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mimetype: text/x-python
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.7.3
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plotly:
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description: A reference for the built-in named continuous (sequential, diverging and cylclical) colorscales in Plotly.
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display_as: file_settings
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has_thumbnail: true
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ipynb: ~notebook_demo/187
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language: python
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layout: base
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name: Built-in Continuous Colorscales
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order: 26
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permalink: python/builtin-colorscales/
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thumbnail: thumbnail/heatmap_colorscale.jpg
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v4upgrade: true
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---
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### Using Built-In Colorscales
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Many Plotly Express functions accept a `color_continuous_scale` argument and many trace
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types have a `colorscale` attribute in their schema. Plotly comes with a large number of
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built-in continuous colorscales, which can be referred to in Python code when setting the above arguments,
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either by name in a case-insensitive string e.g. `px.scatter(continuous_color_scale="Viridis"`) or by reference e.g.
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`go.Scatter(marker_colorscale=plotly.colors.sequential.Viridis)`. They can also be reversed by adding `_r` at the end
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e.g. `"Viridis_r"` or `plotly.colors.sequential.Viridis_r`.
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The `plotly.colours` module is also available under `plotly.express.colors` so you can refer to it as `px.colors`.
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When using continuous colorscales, you will often want to [configure various aspects of its range and colorbar](/python/colorscales/).
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### Named Built-In Colorscales
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You can use any of the following names as string values to set `continuous_color_scale` or `colorscale` arguments.
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These strings are case-insensitive and you can append `_r` to them to reverse the order of the scale.
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```python
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import plotly.express as px
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print("".join('{:<12}'.format(c) for c in px.colors.named_colorscales()))
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```
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### Built-In Sequential Colorscales
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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).
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Here are all the built-in scales in the `plotly.colors.sequential` module:
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```python
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import plotly.express as px
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fig = px.colors.sequential.swatches()
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fig.show()
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```
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Note: `RdBu` was included in this module by mistake, even though it is a diverging color scale.
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It is intentionally left in for backwards-compatibility reasons.
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### Built-In Diverging Colorscales
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A collection of predefined diverging colorscales is provided in the `plotly.colors.diverging` module.
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Diverging color scales are appropriate for continuous data that has a natural midpoint
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other otherwise informative special value, such as 0 altitude, or the boiling point
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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).
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Here are all the built-in scales in the `plotly.colors.diverging` module:
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```python
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import plotly.express as px
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fig = px.colors.diverging.swatches()
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fig.show()
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```
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### Built-In Cyclical Colorscales
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A collection of predefined cyclical colorscales is provided in the `plotly.colors.cyclical` module.
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Cyclical color scales are appropriate for continuous data that has a natural cyclical
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structure, such as temporal data (hour of day, day of week, day of year, seasons) or
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complex numbers or other phase or angular data.
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Here are all the built-in scales in the `plotly.colors.cyclical` module:
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```python
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import plotly.express as px
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fig = px.colors.cyclical.swatches()
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fig.show()
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```

‎doc/python/colorscales.md

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extension: .md
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format_name: markdown
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format_version: "1.2"
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jupytext_version: 1.3.0
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jupytext_version: 1.3.1
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kernelspec:
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display_name: Python 3
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language: python
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.7.3
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version: 3.6.8
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plotly:
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description:
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How to set colorscales and heatmap colorscales in Python and Plotly.

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