adding built-in colorscales reference page

Author: nicolaskruchten

Diff for: doc/python/builtin-colorscales.md

@@ -0,0 +1,108 @@
+---
+jupyter:
+  jupytext:
+    notebook_metadata_filter: all
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: "1.2"
+      jupytext_version: 1.3.0
+  kernelspec:
+    display_name: Python 3
+    language: python
+    name: python3
+  language_info:
+    codemirror_mode:
+      name: ipython
+      version: 3
+    file_extension: .py
+    mimetype: text/x-python
+    name: python
+    nbconvert_exporter: python
+    pygments_lexer: ipython3
+    version: 3.7.3
+  plotly:
+    description: A reference for the built-in named continuous (sequential, diverging and cylclical) colorscales in Plotly.
+    display_as: file_settings
+    has_thumbnail: true
+    ipynb: ~notebook_demo/187
+    language: python
+    layout: base
+    name: Built-in Continuous Colorscales
+    order: 26
+    permalink: python/builtin-colorscales/
+    thumbnail: thumbnail/heatmap_colorscale.jpg
+    v4upgrade: true
+---
+
+### Using Built-In Colorscales
+
+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/).
+
+### Named Built-In 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.
+
+```python
+import plotly.express as px
+
+print("".join('{:<12}'.format(c) for c in px.colors.named_colorscales()))
+```
+
+### Built-In Sequential 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:
+
+```python
+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.
+
+### Built-In Diverging Colorscales
+
+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:
+
+```python
+import plotly.express as px
+
+fig = px.colors.diverging.swatches()
+fig.show()
+```
+
+### Built-In Cyclical Colorscales
+
+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:
+
+```python
+import plotly.express as px
+
+fig = px.colors.cyclical.swatches()
+fig.show()
+```

Diff for: doc/python/colorscales.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: "1.2"
-      jupytext_version: 1.3.0
+      jupytext_version: 1.3.1
   kernelspec:
     display_name: Python 3
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.7.3
+    version: 3.6.8
   plotly:
     description:
       How to set colorscales and heatmap colorscales in Python and Plotly.