Update plotly.js to 2.24.1 and add docs for new features

CHANGELOG.md

@@ -4,6 +4,18 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 
 ## [UNRELEASED]
 
+### Updated
+  - Updated Plotly.js from version 2.20.0 to version 2.23.1. See the [plotly.js CHANGELOG](https://github.com/plotly/plotly.js/blob/master/CHANGELOG.md#2231----2023-05-16) for more information. Notable changes include:
+    - Add `texttemplate` to shape.label for parametric shapes i.e. line, rect and circle [[#6527](https://github.com/plotly/plotly.js/pull/6527)],
+   with thanks to the [Volkswagen](https://www.volkswagenag.com) Center of Excellence for Battery Systems for sponsoring development!
+    - Add strict option to custom bundle command [[#6557](https://github.com/plotly/plotly.js/pull/6557)],
+   with thanks to @CallumNZ for the contribution!
+    - Add `legend` references to traces and `legend2`, `legend3`, etc. to layout,
+   also add `visible` to legend i.e. to allow positioning multiple legends on a graph [[#6535](https://github.com/plotly/plotly.js/pull/6535)],
+   this feature was anonymously sponsored: thank you to our sponsor!
+    - Add `legend.xref` and `legend.yref` to enable container-referenced positioning of legends [[#6589](https://github.com/plotly/plotly.js/pull/6589)], with thanks to [Gamma Technologies](https://www.gtisoft.com/) for sponsoring the related development.
+    - Add `colorbar.xref` and `colorbar.yref` to enable container-referenced positioning of colorbars [[#6593](https://github.com/plotly/plotly.js/pull/6593)], with thanks to [Gamma Technologies](https://www.gtisoft.com/) for sponsoring the related development.
+
 ### Fixed
   - Fixed another compatibility issue with Pandas 2.0, just affecting `px.*(line_close=True)` [[#4190](https://github.com/plotly/plotly.py/pull/4190)]
   - Added some rounding to the `make_subplots` function to handle situations where the user-input specs cause the domain to exceed 1 by small amounts [[#4153](https://github.com/plotly/plotly.py/pull/4153)]

doc/python/colorscales.md

@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.10.9
+    version: 3.10.11
   plotly:
     description: How to set, create and control continuous color scales and color
       bars in scatter, bar, map and heatmap figures.
@@ -632,6 +632,36 @@ fig = go.Figure(go.Heatmap(
 fig.show()
 ```
 
+### Positioning Colorbars
+
+Colorbars can be positioned by specifying x and y coordinates. By default, the x and y values are "paper" coordinates, which refer to the plot area. You can also use coordinates based on the "container" by setting `xref="container"` or `yref="container"`. The following example uses a container reference for the x position.
+
+See the positioning section of [the figure data structure page](/python/figure-structure/#positioning-with-paper-container-coordinates-or-axis-domain-coordinates) for more details on "paper" vs "container" coordinates.
+
+```python
+import plotly.graph_objects as go
+
+import urllib
+import json
+
+# Load heatmap data
+response = urllib.request.urlopen(
+    "https://raw.githubusercontent.com/plotly/datasets/master/custom_heatmap_colorscale.json")
+dataset = json.load(response)
+
+# Create and show figure
+fig = go.Figure(go.Heatmap(
+    z=dataset["z"],
+    colorbar=dict(
+        x=0.2,
+        xref="container",
+        title="Surface Heat"
+    )
+))
+
+fig.show()
+```
+
 ### Reference
 
 See https://plotly.com/python/reference/ for more information and chart attribute options!

doc/python/legend.md

@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.8.8
+    version: 3.10.11
   plotly:
     description: How to configure and style the legend in Plotly with Python.
     display_as: file_settings
@@ -638,6 +638,43 @@ fig.show()
 
 ```
 
+### Positioning Legends
+
+In the previous example, we position the second legend by specifying x and y values. By default, these values are based on the width and height of the plot area. It is also possible to specify values that reference the container width and height by setting "xref=container" and "yref="container" (the default values are "xref=paper" and "yref="paper"). When set to "container", the margin grows so the legend and plot don't overlap.
+
+```python
+import plotly.graph_objects as go
+from plotly import data
+
+df = data.gapminder()
+
+df_germany = df.loc[(df.country.isin(["Germany"]))]
+df_france = df.loc[(df.country.isin(["France"]))]
+df_uk = df.loc[(df.country.isin(["United Kingdom"]))]
+
+fig = go.Figure(
+    data=[
+        go.Scatter(x=df_germany.year, y=df_germany.gdpPercap, name="Germany"),
+        go.Scatter(x=df_france.year, y=df_france.gdpPercap, name="France"),
+        go.Scatter(x=df_uk.year, y=df_uk.gdpPercap, name="UK"),
+    ],
+    layout=dict(
+        title="GDP Per Capita",
+        legend={
+            "x": 0.9,
+            "y": 0.9,
+            "xref": "container",
+            "yref": "container",
+            "bgcolor": "Gold",
+            "title": {"text": "By continent"},
+        },
+    ),
+)
+
+fig.show()
+
+```
+
 #### Reference
 
 See https://plotly.com/python/reference/layout/#layout-legend for more information!

doc/python/pie-charts.md

@@ -6,9 +6,9 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.14.1
+      jupytext_version: 1.14.6
   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: 3.8.8
+    version: 3.10.11
   plotly:
     description: How to make Pie Charts.
     display_as: basic
@@ -300,6 +300,32 @@ fig.update_layout(title_text='World GDP')
 fig.show()
 ```
 
+### Pattern Fills
+
+*New in 5.15*
+
+Pie charts support [patterns](/python/pattern-hatching-texture/) (also known as hatching or texture) in addition to color.
+
+```python
+import plotly.graph_objects as go
+
+labels = ["Oxygen", "Hydrogen", "Carbon_Dioxide", "Nitrogen"]
+values = [4500, 2500, 1053, 500]
+colors = ["gold", "mediumturquoise", "darkorange", "lightgreen"]
+fig = go.Figure(
+    data=[
+        go.Pie(
+            labels=labels,
+            values=values,
+            textfont_size=20,
+            marker={"colors": colors, "pattern": {"shape": [".", "x", "+", "-"]}},
+        )
+    ]
+)
+fig.show()
+
+```
+
 ### See Also: Sunburst charts
 
 For multilevel pie charts representing hierarchical data, you can use the `Sunburst` chart. A simple example is given below, for more information see the [tutorial on Sunburst charts](/python/sunburst-charts/).