docs and changelog

Author: nicolaskruchten

Diff for: CHANGELOG.md

@@ -3,6 +3,16 @@ All notable changes to this project will be documented in this file.
 This project adheres to [Semantic Versioning](http://semver.org/).
 
 
+##  [5.7.0] - UNRELEASED
+
+### Added
+  - added `pattern_shape` options to `px.area()` [#3668](https://github.com/plotly/plotly.py/issues/3668)
+
+### Updated
+  - Updated Plotly.js to from version 2.9.0 to version 2.11.1. See the [plotly.js CHANGELOG](https://github.com/plotly/plotly.js/blob/master/CHANGELOG.md#2111----2022-03-15) for more information. Notable changes include:
+    - Add `fillpattern` options to `scatter` trace
+    - Various JS-specific improvements such as MathJax 3.0 support
+
 ##  [5.6.0] - 2022-02-09
 
 ### Updated

Diff for: doc/python/filled-area-plots.md

@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.2'
-      jupytext_version: 1.6.0
+      format_version: '1.3'
+      jupytext_version: 1.13.7
   kernelspec:
-    display_name: Python 3
+    display_name: Python 3 (ipykernel)
     language: python
     name: python3
   language_info:
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.7.6
+    version: 3.9.7
   plotly:
     description: How to make filled area plots in Python with Plotly.
     display_as: basic
@@ -44,8 +44,7 @@ This example shows how to fill the area enclosed by traces.
 ```python
 import plotly.express as px
 df = px.data.gapminder()
-fig = px.area(df, x="year", y="pop", color="continent",
-	      line_group="country")
+fig = px.area(df, x="year", y="pop", color="continent", line_group="country")
 fig.show()
 ```
 
@@ -62,11 +61,28 @@ snippet_url = 'https://python-docs-dash-snippets.herokuapp.com/python-docs-dash-
 IFrame(snippet_url + 'filled-area-plots', width='100%', height=1200)
 ```
 
+### Pattern Fills
+
+*New in v5.0*
+
+Area charts afford the use of [patterns (also known as hatching or texture)](/python/pattern-hatching-texture/) in addition to color:
+
+```python
+import plotly.express as px
+df = px.data.medals_long()
+
+fig = px.area(df, x="medal", y="count", color="nation",
+             pattern_shape="nation", pattern_shape_sequence=[".", "x", "+"])
+fig.show()
+```
+
+<!-- #region tags=[] -->
 ### Filled area chart with plotly.graph_objects
 
 #### Basic Overlaid Area Chart
+<!-- #endregion -->
 
-```python
+```python tags=[]
 import plotly.graph_objects as go
 
 fig = go.Figure()

Diff for: doc/python/pattern-hatching-texture.md

@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.2'
-      jupytext_version: 1.4.2
+      format_version: '1.3'
+      jupytext_version: 1.13.7
   kernelspec:
-    display_name: Python 3
+    display_name: Python 3 (ipykernel)
     language: python
     name: python3
   language_info:
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.7.7
+    version: 3.9.7
   plotly:
     description: How to use patterns (also known as hatching or texture) with bar
       charts.
@@ -36,16 +36,16 @@ jupyter:
 
 *New in v5.0*
 
-[Bar charts](/python/bar-charts/), [histograms](/python/histograms/) and [polar bar charts](/python/wind-rose-charts/) have large markers which support not only a fill color, but also an optional **pattern** (also known as "hatching" or "texture"). This can be used for a variety of reasons:
+[Bar charts](/python/bar-charts/), [histograms](/python/histograms/), [polar bar charts](/python/wind-rose-charts/) and [area charts](/python/filled-area-plots/) have large markers or areas which support not only a fill color, but also an optional **pattern** (also known as "hatching" or "texture"). This can be used for a variety of reasons:
 
 * to double-encode variables (i.e. using both color and pattern) to improve accessibility for visually-impaired end-users
 * to encode an additional variable beyond just using color
 * to make charts that are easier to print in black and white
 
 
-### Patterned Bar Charts with Plotly Express
+### Patterned Charts with Plotly Express
 
-the `px.bar()`, `px.histogram()` and `px.bar_polar()` functions support the `pattern_shape` argument. In the chart below, we double-encode `nation` using color and pattern:
+the `px.bar()`, `px.histogram()`, `px.bar_polar()` and `px.area()` functions support the `pattern_shape` argument. In the chart below, we double-encode `nation` using color and pattern:
 
 ```python
 import plotly.express as px
@@ -55,6 +55,14 @@ fig = px.bar(df, x="medal", y="count", color="nation", pattern_shape="nation")
 fig.show()
 ```
 
+```python
+import plotly.express as px
+df = px.data.medals_long()
+
+fig = px.area(df, x="medal", y="count", color="nation", pattern_shape="nation")
+fig.show()
+```
+
 In the chart below we use `px.histogram()` instead of `px.bar()` to aggregate multiple values together, and encode one variable (sex) using both color and x-position and another (smoker) using patterns:
 
 ```python