Color docs

doc/python/builtin-colorscales.md

@@ -5,7 +5,7 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.2'
+      format_version: "1.2"
       jupytext_version: 1.3.1
   kernelspec:
     display_name: Python 3
@@ -22,34 +22,39 @@ jupyter:
     pygments_lexer: ipython3
     version: 3.6.8
   plotly:
-    description: A reference for the built-in named continuous (sequential, diverging
-      and cylclical) colorscales in Plotly.
+    description:
+      A reference for the built-in named continuous (sequential, diverging
+      and cylclical) color scales in Plotly.
     display_as: file_settings
     has_thumbnail: true
     ipynb: ~notebook_demo/187
     language: python
     layout: base
-    name: Built-in Continuous Colorscales
+    name: Built-in Continuous Color Scales
     order: 27
     permalink: python/builtin-colorscales/
     thumbnail: thumbnail/heatmap_colorscale.jpg
     v4upgrade: true
 ---
 
-### Using Built-In Colorscales
+### Using Built-In Continuous Color Scales
 
 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,
+built-in continuous color scales, 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/).
+When using continuous color scales, you will often want to [configure various aspects of its range and colorbar](/python/colorscales/).
 
-### Named Built-In Colorscales
+### Discrete Color Sequences
+
+Plotly also comes with some built-in [discrete color sequences](/python/discrete-color/) which are _not intended_ to be used with the `color_continuous_scale` argument as they are not designed for interpolation to occur between adjacent colors.
+
+### Named Built-In Continuous Color Scales
 
 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.
@@ -62,7 +67,15 @@ named_colorscales = px.colors.named_colorscales()
 print("\n".join(wrap("".join('{:<12}'.format(c) for c in named_colorscales), 96)))
 ```
 
-### Built-In Sequential Colorscales
+Built-in color scales are stored as lists of CSS colors:
+
+```python
+import plotly.express as px
+
+print(px.colors.sequential.Plasma)
+```
+
+### Built-In Sequential Color scales
 
 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).
 
@@ -78,9 +91,9 @@ 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
+### Built-In Diverging Color scales
 
-A collection of predefined diverging colorscales is provided in the `plotly.colors.diverging` module.
+A collection of predefined diverging color scales 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).
@@ -94,9 +107,9 @@ fig = px.colors.diverging.swatches()
 fig.show()
 ```
 
-### Built-In Cyclical Colorscales
+### Built-In Cyclical Color scales
 
-A collection of predefined cyclical colorscales is provided in the `plotly.colors.cyclical` module.
+A collection of predefined cyclical color scales 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.