Add Plotly.js docs updates for 6.3

doc/python/axes.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.16.3
+      jupytext_version: 1.17.2
   kernelspec:
     display_name: Python 3 (ipykernel)
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.10.14
+    version: 3.9.0
   plotly:
     description: How to adjust axes properties in Python - axes titles, styling and
       coloring axes and grid lines, ticks, tick labels and more.
@@ -619,6 +619,38 @@ fig.update_yaxes(zeroline=True, zerolinewidth=2, zerolinecolor='LightPink')
 fig.show()
 ```
 
+##### Controlling zero line layer
+
+*New in 6.3*
+
+By default, zero lines are displayed below traces. Set `zerolinelayer="above traces"` on an axis to display its zero line above traces:
+
+```python
+import plotly.graph_objects as go
+
+x = ['A', 'B', 'C', 'D', 'A']
+y = [2, 0, 4, -3, 2]
+
+fig = go.Figure(
+    data=[
+        go.Scatter(
+            x=x,
+            y=y,
+            fill='toself',
+            mode='none',
+            fillcolor='lightpink'
+        )
+    ],
+    layout=dict(
+        yaxis=dict(
+            zerolinelayer="above traces"  # Change to "below traces" to see the difference
+        ),
+    )
+)
+
+fig.show()
+```
+
 #### Setting the Range of Axes Manually
 
 The visible x and y axis range can be configured manually by setting the `range` axis property to a list of two values, the lower and upper bound.

doc/python/legend.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.16.1
+      jupytext_version: 1.17.2
   kernelspec:
     display_name: Python 3 (ipykernel)
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.10.11
+    version: 3.9.0
   plotly:
     description: How to configure and style the legend in Plotly with Python.
     display_as: file_settings
@@ -254,6 +254,46 @@ fig.update_layout(legend=dict(
 fig.show()
 ```
 
+#### Legend Max Height
+
+*New in 6.3*
+
+By default, a legend can expand to fill up to half of the layout area height for a horizontal legend and the full height for a vertical legend. You can specify the maximum height of a legend with the `maxheight` parameter. In the following plot with many legend items, we set `maxheight` to a ratio of 0.10, giving the plot more space.
+
+```python
+import plotly.express as px
+from plotly import data
+
+df = data.gapminder().query("year==2007 and continent == 'Europe'")
+
+fig = px.scatter(df, 
+                 x="gdpPercap", 
+                 y="lifeExp", 
+                 color="country",
+                 size="pop", 
+                 size_max=45, 
+                 title="Life Expectancy vs. GDP per Capita in 2007 (by Country)",
+                 labels={"gdpPercap": "GDP per Capita"},
+                )
+
+fig.update_layout(
+    xaxis=dict(
+        side="top"
+    ),
+    legend=dict(
+        orientation="h",
+        yanchor="bottom",
+        y=-0.35,
+        xanchor="center",
+        x=0.5,
+        maxheight=0.1, # Comment maxheight to see legend take up 0.5 of plotting area
+        title_text="Country"
+    ),
+)
+
+fig.show()
+```
+
 #### Styling Legends
 
 Legends support many styling options.

doc/python/pattern-hatching-texture.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.14.6
+      jupytext_version: 1.17.2
   kernelspec:
     display_name: Python 3 (ipykernel)
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.10.11
+    version: 3.9.0
   plotly:
     description: How to use patterns (also known as hatching or texture) with bar
       charts.
@@ -150,6 +150,55 @@ fig.add_trace(go.Bar(x=["a","b"], y=[2,3], marker_pattern_shape="+"))
 fig.show()
 ```
 
+### Patterns Using SVG Paths
+
+*New in 6.3*
+
+You can make custom patterns for graphs by using an SVG path. Set `marker.pattern.path` to the SVG path to use:
+
+```python
+import plotly.graph_objects as go
+import plotly.data
+
+df = plotly.data.gapminder().query("year == 2007 and continent == 'Europe'").copy()
+df['gdp'] = df['gdpPercap'] * df['pop']
+df = df.sort_values('gdp', ascending=False).head(4)
+
+fig = go.Figure(
+    data=[go.Bar(
+        x=df['country'],
+        y=df['gdp'],
+        marker=dict(
+            color=["lightsteelblue", "mistyrose", "palegreen", "thistle"],
+            pattern=dict(
+                path=[
+                    "M0,0H4V4H0Z",
+                    "M0,0H6V6Z",
+                    "M0,0V4H4Z",
+                    "M0,0C0,2,4,2,4,4C4,6,0,6,0,8H2C2,6,6,6,6,4C6,2,2,2,2,0Z"
+                ],
+                fgcolor=["midnightblue", "crimson", "seagreen", "indigo"],
+                bgcolor=["mintcream", "lavenderblush", "azure", "honeydew"],
+                size=20,
+                solidity=0.7
+            )
+        ),
+        name="GDP (2007)"
+    )],
+    layout=dict(
+        title="Top 4 European Countries by GDP (Gapminder 2007) with Custom SVG Path Patterns",
+        xaxis_title="Country",
+        yaxis_title="GDP (USD)",
+        yaxis_tickformat="$.2s",
+        width=800,
+        height=500,
+        bargap=0.3
+    )
+)
+
+fig.show()
+```
+
 #### Reference
 
 See https://plotly.com/python/reference/bar/ for more information and chart attribute options!