Merge doc prod updates into master

doc/python/bubble-maps.md

@@ -85,7 +85,7 @@ df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_
 df.head()
 
 df['text'] = df['name'] + '<br>Population ' + (df['pop']/1e6).astype(str)+' million'
-limits = [(0,2),(3,10),(11,20),(21,50),(50,3000)]
+limits = [(0,3),(3,11),(11,21),(21,50),(50,3000)]
 colors = ["royalblue","crimson","lightseagreen","orange","lightgrey"]
 cities = []
 scale = 5000

doc/python/dendrogram.md

@@ -92,7 +92,7 @@ from scipy.spatial.distance import pdist, squareform
 # get data
 data = np.genfromtxt("http://files.figshare.com/2133304/ExpRawData_E_TABM_84_A_AFFY_44.tab",
                      names=True,usecols=tuple(range(1,30)),dtype=float, delimiter="\t")
-data_array = data.view((np.float, len(data.dtype.names)))
+data_array = data.view((float, len(data.dtype.names)))
 data_array = data_array.transpose()
 labels = data.dtype.names
 

doc/python/figure-labels.md

@@ -124,7 +124,7 @@ IFrame(snippet_url + 'figure-labels', width='100%', height=1200)
 
 ### Manual Labelling with Graph Objects
 
-When using (graph objects)[/python/graph-objects/] rather than [Plotly Express](/python/plotly-express/), you will need to explicitly label traces and axes:
+When using [graph objects](/python/graph-objects/) rather than [Plotly Express](/python/plotly-express/), you will need to explicitly label traces and axes:
 
 ```python
 import plotly.graph_objects as go

doc/python/filled-area-on-mapbox.md

@@ -60,7 +60,7 @@ fig = go.Figure(go.Scattermapbox(
 
 fig.update_layout(
     mapbox = {
-        'style': "stamen-terrain",
+        'style': "open-street-map",
         'center': {'lon': -73, 'lat': 46 },
         'zoom': 5},
     showlegend = False)
@@ -81,7 +81,7 @@ fig = go.Figure(go.Scattermapbox(
     lat = [30, 6, 6, 30, 30,    None, 20, 30, 30, 20, 20, None, 40, 50, 50, 40, 40]))
 
 fig.update_layout(
-    mapbox = {'style': "stamen-terrain", 'center': {'lon': 30, 'lat': 30}, 'zoom': 2},
+    mapbox = {'style': "open-street-map", 'center': {'lon': 30, 'lat': 30}, 'zoom': 2},
     showlegend = False,
     margin = {'l':0, 'r':0, 'b':0, 't':0})
 
@@ -102,7 +102,7 @@ fig = go.Figure(go.Scattermapbox(
 
 fig.update_layout(
     mapbox = {
-        'style': "stamen-terrain",
+        'style': "open-street-map",
         'center': { 'lon': -73.6, 'lat': 45.5},
         'zoom': 12, 'layers': [{
             'source': {

doc/python/icicle-charts.md

@@ -232,7 +232,7 @@ fig.show()
 
 ### Large Number of Slices
 
-This example uses a [plotly grid attribute](https://plotly.com/python/reference/layout/#layout-grid) for the suplots. Reference the row and column destination using the [domain](https://plotly.com/python/reference/icicle/#icicle-domain) attribute.
+This example uses a [plotly grid attribute](https://plotly.com/python/reference/layout/#layout-grid) for the subplots. Reference the row and column destination using the [domain](https://plotly.com/python/reference/icicle/#icicle-domain) attribute.
 
 ```python
 import plotly.graph_objects as go

doc/python/interactive-html-export.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: Plotly allows you to save interactive HTML versions of your figures
       to your local disk.
@@ -55,6 +55,45 @@ fig.write_html("path/to/file.html")
 
 By default, the resulting HTML file is a fully self-contained HTML file which can be uploaded to a web server or shared via email or other file-sharing mechanisms. The downside to this approach is that the file is very large (5Mb+) because it contains an inlined copy of the Plotly.js library required to make the figure interactive. This can be controlled via the `include_plotlyjs` argument (see below).
 
+### Inserting Plotly Output into HTML using a Jinja2 Template
+
+You can insert Plotly output and text related to your data into HTML templates using Jinja2. Use `.to_html` to send the HTML to a Python string variable rather than using `write_html` to send the HTML to a disk file.  Use the `full_html=False` option to output just the code necessary to add a figure to a template. We don't want to output a full HTML page, as the template will define the rest of the page's structure — for example, the page's `HTML` and `BODY` tags.  First create an HTML template file containing a Jinja `{{ variable }}`.  In this example, we customize the HTML in the template file by replacing the Jinja variable `{{ fig }}` with our graphic `fig`.
+
+<!-- #region -->
+
+```
+&lt;!DOCTYPE html&gt;
+&lt;html&gt;
+&lt;body&gt;
+&lt;h1&gt;Here's a Plotly graph!&lt;/h1&gt;
+{{ fig }}
+&lt;p&gt;And here's some text after the graph.&lt;/p&gt;
+&lt;/body&gt;
+&lt;/html&gt;
+```
+
+
+Then use the following Python to replace `{{ fig }}` in the template with HTML that will display the Plotly figure "fig":
+
+```python
+import plotly.express as px
+from jinja2 import Template
+
+data_canada = px.data.gapminder().query("country == 'Canada'")
+fig = px.bar(data_canada, x='year', y='pop')
+
+output_html_path=r"/path/to/output.html"
+input_template_path = r"/path/to/template.html"
+
+plotly_jinja_data = {"fig":fig.to_html(full_html=False)}
+#consider also defining the include_plotlyjs parameter to point to an external Plotly.js as described above
+
+with open(output_html_path, "w", encoding="utf-8") as output_file:
+    with open(input_template_path) as template_file:
+        j2_template = Template(template_file.read())
+        output_file.write(j2_template.render(plotly_jinja_data))
+```
+<!-- #endregion -->
 
 ### HTML export in Dash
 

doc/python/lines-on-mapbox.md

@@ -51,7 +51,7 @@ import plotly.express as px
 
 fig = px.line_mapbox(us_cities, lat="lat", lon="lon", color="State", zoom=3, height=300)
 
-fig.update_layout(mapbox_style="stamen-terrain", mapbox_zoom=4, mapbox_center_lat = 41,
+fig.update_layout(mapbox_style="open-street-map", mapbox_zoom=4, mapbox_center_lat = 41,
     margin={"r":0,"t":0,"l":0,"b":0})
 
 fig.show()
@@ -95,7 +95,7 @@ for feature, name in zip(geo_df.geometry, geo_df.name):
         names = np.append(names, None)
 
 fig = px.line_mapbox(lat=lats, lon=lons, hover_name=names,
-                     mapbox_style="stamen-terrain", zoom=1)
+                     mapbox_style="open-street-map", zoom=1)
 fig.show()
 ```
 
@@ -123,7 +123,7 @@ fig.update_layout(
     margin ={'l':0,'t':0,'b':0,'r':0},
     mapbox = {
         'center': {'lon': 10, 'lat': 10},
-        'style': "stamen-terrain",
+        'style': "open-street-map",
         'center': {'lon': -20, 'lat': -20},
         'zoom': 1})
 

doc/python/mapbox-density-heatmaps.md

@@ -37,7 +37,6 @@ jupyter:
 
 To plot on Mapbox maps with Plotly, you may need a [Mapbox account and token](https://www.mapbox.com/studio) or a [Stadia Maps account and token](https://www.stadiamaps.com), depending on base map (`mapbox_style`) you use. On this page, we show how to use the "open-street-map" base map, which doesn't require a token, and a "stamen" base map, which requires a Stadia Maps token. See our [Mapbox Map Layers](/python/mapbox-layers/) documentation for more examples.
 
-
 ### OpenStreetMap base map (no token needed): density mapbox with `plotly.express`
 
 [Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on a variety of types of data](/python/px-arguments/) and produces [easy-to-style figures](/python/styling-plotly-express/).

doc/python/mapbox-layers.md

@@ -67,7 +67,7 @@ If you basemap in `layout.mapbox.style` uses maps from the [Stadia Maps service]
 The accepted values for `layout.mapbox.style` are one of:
 
 - `"white-bg"` yields an empty white canvas which results in no external HTTP requests
-- `"open-street-map"`, `"carto-positron"`, or `"carto-darkmatter"` yield maps composed of _raster_ tiles from various public tile servers which do not require signups or access tokens.
+- `"open-street-map"`, `"carto-positron"`, and `"carto-darkmatter"` yield maps composed of _raster_ tiles from various public tile servers which do not require signups or access tokens.
 - `"basic"`, `"streets"`, `"outdoors"`, `"light"`, `"dark"`, `"satellite"`, or `"satellite-streets"` yield maps composed of _vector_ tiles from the Mapbox service, and _do_ require a Mapbox Access Token or an on-premise Mapbox installation.
 - `"stamen-terrain"`, `"stamen-toner"` or `"stamen-watercolor"` yield maps composed of _raster_ tiles from the [Stadia Maps service](https://www.stadiamaps.com), and require a Stadia Maps account and token. 
 - A Mapbox service style URL, which requires a Mapbox Access Token or an on-premise Mapbox installation.

doc/python/marker-style.md

@@ -6,7 +6,7 @@ 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 (ipykernel)
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.8.0
+    version: 3.10.11
   plotly:
     description: How to style markers in Python with Plotly.
     display_as: file_settings
@@ -361,7 +361,7 @@ fig.show()
 
 ### Using a Custom Marker
 
-To use a custom marker, set the `symbol` on the `marker`. Here we set it to `diamond`.
+To use a custom marker, set the `symbol` on the `marker`. Here we set it to `diamond`. 
 
 
 ```python
@@ -378,6 +378,31 @@ fig.show()
 
 ```
 
+#### Open Marker Colors
+
+In the previous example, each marker has two colors, a marker color (set in Plotly Express with `color="species"`)  and a line color (set on the line with `color="DarkSlateGrey"`. All open markers, like "diamond-open" in the following example, have a transparent fill, which means you can specify only one color.  Specify this color using the marker color parameter. This controls the outline color and any dot or cross. For open markers, the line color does nothing.
+
+```python
+import plotly.express as px
+
+df = px.data.iris()
+fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species")
+
+fig.update_traces(
+    marker=dict(
+        size=8, 
+        symbol="diamond-open", 
+        line=dict(
+            width=2, 
+#             color="DarkSlateGrey" Line colors don't apply to open markers
+        )
+    ),
+    selector=dict(mode="markers"),
+)
+
+fig.show()
+```
+
 ### Setting Marker Angles
 
 

doc/python/sunburst-charts.md

@@ -214,7 +214,7 @@ fig.show()
 
 ### Large Number of Slices
 
-This example uses a [plotly grid attribute](https://plotly.com/python/reference/layout/#layout-grid) for the suplots. Reference the row and column destination using the [domain](https://plotly.com/python/reference/sunburst/#sunburst-domain) attribute.
+This example uses a [plotly grid attribute](https://plotly.com/python/reference/layout/#layout-grid) for the subplots. Reference the row and column destination using the [domain](https://plotly.com/python/reference/sunburst/#sunburst-domain) attribute.
 
 ```python
 import plotly.graph_objects as go

doc/python/text-and-annotations.md

@@ -6,9 +6,9 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.14.1
+      jupytext_version: 1.16.1
   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 add text labels and annotations to plots in python.
     display_as: file_settings
@@ -207,6 +207,44 @@ fig.update_layout(showlegend=False)
 fig.show()
 ```
 
+#### Text Annotations with Log Axes
+
+If the `x` or `y` positions of an annotation reference a log axis, you need to provide that position as a `log10` value when adding the annotation. In this example, the `yaxis` is a log axis so we pass the `log10` value of `1000` to the annotation's `y` position.
+
+```python
+import plotly.graph_objects as go
+import math
+
+dates = [
+    "2024-01-01",
+    "2024-01-02",
+    "2024-01-03",
+    "2024-01-04",
+    "2024-01-05",
+    "2024-01-06",
+]
+y_values = [1, 30, 70, 100, 1000, 10000000]
+
+fig = go.Figure(
+    data=[go.Scatter(x=dates, y=y_values, mode="lines+markers")],
+    layout=go.Layout(
+        yaxis=dict(
+            type="log",
+        )
+    ),
+)
+
+fig.add_annotation(
+    x="2024-01-05",
+    y=math.log10(1000),
+    text="Log axis annotation",
+    showarrow=True,
+    xanchor="right",
+)
+
+fig.show()
+```
+
 ### 3D Annotations
 
 ```python