diff --git a/doc/python/dumbbell-plots.md b/doc/python/dumbbell-plots.md
new file mode 100644
index 00000000000..f3ff1f8dc51
--- /dev/null
+++ b/doc/python/dumbbell-plots.md
@@ -0,0 +1,176 @@
+---
+jupyter:
+  jupytext:
+    notebook_metadata_filter: all
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.3'
+      jupytext_version: 1.14.1
+  kernelspec:
+    display_name: Python 3 (ipykernel)
+    language: python
+    name: python3
+  language_info:
+    codemirror_mode:
+      name: ipython
+      version: 3
+    file_extension: .py
+    mimetype: text/x-python
+    name: python
+    nbconvert_exporter: python
+    pygments_lexer: ipython3
+    version: 3.8.0
+  plotly:
+    description: How to create dumbbell plots in Python with Plotly.
+    display_as: basic
+    language: python
+    layout: base
+    name: Dumbbell Plots
+    order: 19
+    page_type: example_index
+    permalink: python/dumbbell-plots/
+    thumbnail: thumbnail/dumbbell-plot.jpg
+---
+
+## Basic Dumbbell Plot
+
+
+Dumbbell plots are useful for demonstrating change between two sets of data points, for example, the population change for a selection of countries for two different years
+
+In this example, we compare life expectancy in 1952 with life expectancy in 2002 for countries in Europe.
+
+```python
+import plotly.graph_objects as go
+from plotly import data
+
+import pandas as pd
+
+df = data.gapminder()
+df = df.loc[(df.continent == "Europe") & (df.year.isin([1952, 2002]))]
+
+countries = (
+    df.loc[(df.continent == "Europe") & (df.year.isin([2002]))]
+    .sort_values(by=["lifeExp"], ascending=True)["country"]
+    .unique()
+)
+
+data = {"x": [], "y": [], "colors": [], "years": []}
+
+for country in countries:
+    data["x"].extend(
+        [
+            df.loc[(df.year == 1952) & (df.country == country)]["lifeExp"].values[0],
+            df.loc[(df.year == 2002) & (df.country == country)]["lifeExp"].values[0],
+            None,
+        ]
+    )
+    data["y"].extend([country, country, None]),
+    data["colors"].extend(["green", "blue", "brown"]),
+    data["years"].extend(["1952", "2002", None])
+
+fig = go.Figure(
+    data=[
+        go.Scatter(
+            x=data["x"],
+            y=data["y"],
+            mode="lines",
+            marker=dict(
+                color="grey",
+            ),
+        ),
+        go.Scatter(
+            x=data["x"],
+            y=data["y"],
+            mode="markers+text",
+            marker=dict(
+                color=data["colors"],
+                size=10,
+            ),
+            hovertemplate="""Country: %{y} <br> Life Expectancy: %{x} <br><extra></extra>""",
+        ),
+    ]
+)
+
+fig.update_layout(
+    title="Life Expectancy in Europe: 1952 and 2002",
+    width=1000,
+    height=1000,
+    showlegend=False,
+)
+
+fig.show()
+
+```
+
+## Dumbbell Plot with Arrow Markers
+
+*Note: The `arrow`, `angleref`, and `standoff` properties used on the `marker` in this example are new in 5.11*
+
+In this example, we add arrow markers to the plot. The first trace adds the lines connecting the data points and arrow markers. 
+The second trace adds circle markers. On the first trace, we use `standoff=8` to position the arrow marker back from the data point.
+For the arrow marker to point directly at the circle marker, this value should be half the circle marker size. 
+
+```python
+import pandas as pd
+import plotly.graph_objects as go
+from plotly import data
+
+df = data.gapminder()
+df = df.loc[(df.continent == "Europe") & (df.year.isin([1952, 2002]))]
+
+countries = (
+    df.loc[(df.continent == "Europe") & (df.year.isin([2002]))]
+    .sort_values(by=["lifeExp"], ascending=True)["country"]
+    .unique()
+)
+
+data = {"x": [], "y": [], "colors": [], "years": []}
+
+for country in countries:
+    data["x"].extend(
+        [
+            df.loc[(df.year == 1952) & (df.country == country)]["lifeExp"].values[0],
+            df.loc[(df.year == 2002) & (df.country == country)]["lifeExp"].values[0],
+            None,
+        ]
+    )
+    data["y"].extend([country, country, None]),
+    data["colors"].extend(["silver", "lightskyblue", "white"]),
+    data["years"].extend(["1952", "2002", None])
+
+fig = go.Figure(
+    data=[
+        go.Scatter(
+            x=data["x"],
+            y=data["y"],
+            mode="markers+lines",
+            marker=dict(
+                symbol="arrow", color="black", size=16, angleref="previous", standoff=8
+            ),
+        ),
+        go.Scatter(
+            x=data["x"],
+            y=data["y"],
+            text=data["years"],
+            mode="markers",
+            marker=dict(
+                color=data["colors"],
+                size=16,
+            ),
+            hovertemplate="""Country: %{y} <br> Life Expectancy: %{x} <br> Year: %{text} <br><extra></extra>""",
+        ),
+    ]
+)
+
+fig.update_layout(
+    title="Life Expectancy in Europe: 1952 and 2002",
+    width=1000,
+    height=1000,
+    showlegend=False,
+)
+
+
+fig.show()
+
+```
diff --git a/doc/python/legend.md b/doc/python/legend.md
index a83ab1e7c45..7fafadd107a 100644
--- a/doc/python/legend.md
+++ b/doc/python/legend.md
@@ -8,7 +8,7 @@ jupyter:
       format_version: '1.3'
       jupytext_version: 1.14.1
   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: 3.8.0
   plotly:
     description: How to configure and style the legend in Plotly with Python.
     display_as: file_settings
@@ -189,6 +189,31 @@ fig.update_layout(legend=dict(
 fig.show()
 ```
 
+#### Horizontal Legend Entry Width
+
+*New in 5.11*
+
+Set the width of hozitonal legend entries by setting `entrywidth`. Here we set it to `70` pixels. Pixels is the default unit for `entrywidth`, but you can set it to be a fraction of the plot width using `entrywidthmode='fraction`.
+
+```python
+import plotly.express as px
+
+df = px.data.gapminder().query("year==2007")
+fig = px.scatter(df, x="gdpPercap", y="lifeExp", color="continent",
+    size="pop", size_max=45, log_x=True)
+
+fig.update_layout(legend=dict(
+    orientation="h",
+    entrywidth=70,
+    yanchor="bottom",
+    y=1.02,
+    xanchor="right",
+    x=1
+))
+
+fig.show()
+```
+
 #### Styling Legends
 
 Legends support many styling options.
diff --git a/doc/python/mapbox-layers.md b/doc/python/mapbox-layers.md
index 70cbaad4d7d..be8d238bef4 100644
--- a/doc/python/mapbox-layers.md
+++ b/doc/python/mapbox-layers.md
@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.2'
-      jupytext_version: 1.3.1
+      format_version: '1.3'
+      jupytext_version: 1.14.1
   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: 3.6.8
+    version: 3.8.0
   plotly:
     description: How to make Mapbox maps in Python with various base layers, with
       or without needing a Mapbox Access token.
@@ -192,6 +192,37 @@ fig.show()
 
 See the example in the [plotly and datashader tutorial](/python/datashader).
 
+
+#### Setting Map Bounds
+
+*New in 5.11*
+
+Set bounds for a map to specify an area outside which a user interacting with the map can't pan or zoom. Here we set a maximum longitude of `-180`, a minimum longitude of `-50`, a maximum latitude of `90`, and a minimum latitude of `20`.
+
+```python
+import plotly.express as px
+import pandas as pd
+
+us_cities = pd.read_csv(
+    "https://raw.githubusercontent.com/plotly/datasets/master/us-cities-top-1k.csv"
+)
+
+fig = px.scatter_mapbox(
+    us_cities,
+    lat="lat",
+    lon="lon",
+    hover_name="City",
+    hover_data=["State", "Population"],
+    color_discrete_sequence=["fuchsia"],
+    zoom=3,
+    height=300,
+)
+fig.update_layout(mapbox_style="open-street-map")
+fig.update_layout(margin={"r": 0, "t": 0, "l": 0, "b": 0})
+fig.update_layout(mapbox_bounds={"west": -180, "east": -50, "south": 20, "north": 90})
+fig.show()
+```
+
 #### Reference
 
 See https://plotly.com/python/reference/layout/mapbox/ for more information and options!
diff --git a/doc/python/marker-style.md b/doc/python/marker-style.md
index e51e564bb3a..128b22d04c5 100644
--- a/doc/python/marker-style.md
+++ b/doc/python/marker-style.md
@@ -8,7 +8,7 @@ jupyter:
       format_version: '1.3'
       jupytext_version: 1.14.1
   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: 3.8.0
   plotly:
     description: How to style markers in Python with Plotly.
     display_as: file_settings
@@ -332,6 +332,8 @@ Each basic symbol is also represented by a number. Adding 100 to that number is
 
 In the following figure, hover over a symbol to see its name or number. Set the `marker_symbol` attribute equal to that name or number to change the marker symbol in your figure.
 
+> The `arrow-wide` and `arrow` marker symbols are new in 5.11
+
 ```python
 import plotly.graph_objects as go
 from plotly.validators.scatter.marker import SymbolValidator
@@ -357,6 +359,158 @@ fig.show()
 ```
 
 
+### Using a Custom Marker
+
+To use a custom marker, set the `symbol` on the `marker`. Here we set it to `diamond`.
+
+
+```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", line=dict(width=2, color="DarkSlateGrey")),
+    selector=dict(mode="markers"),
+)
+fig.show()
+
+```
+
+### Setting Marker Angles
+
+
+*New in 5.11*
+
+Change the angle of markers by setting `angle`. Here we set the angle on the `arrow` markers to `45`.
+
+```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=12, symbol="arrow", angle=45, line=dict(width=2, color="DarkSlateGrey")
+    ),
+    selector=dict(mode="markers"),
+)
+fig.show()
+
+```
+
+### Setting Angle Reference
+
+*New in 5.11*
+
+In the previous example the angle reference is the default `up`, which
+means all makers start at the angle reference point of 0. Set `angleref` to `previous` and a marker will take its angle reference from the previous data point.
+
+```python
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+
+df = px.data.gapminder()
+
+fig = go.Figure()
+
+for x in df.loc[df.continent.isin(["Europe"])].country.unique()[:5]:
+    fil = df.loc[(df.country.str.contains(x))]
+    fig.add_trace(
+        go.Scatter(
+            x=fil["year"],
+            y=fil["pop"],
+            mode="lines+markers",
+            marker=dict(
+                symbol="arrow",
+                size=15,
+                angleref="previous",
+            ),
+            name=x,
+        )
+    )
+fig.show()
+
+```
+
+### Using Standoff to Position a Marker
+
+*New in 5.11*
+
+When you have multiple markers at one location, you can use `standoff` on a marker to move it away from the other marker in the direction of the `angle`. 
+In this example, we set `standoff=8` on the `arrow` marker, which is half the size of the other `circle` marker, meaning it points exactly at the `circle`.
+
+```python
+import pandas as pd
+import plotly.graph_objects as go
+from plotly import data
+
+df = data.gapminder()
+df = df.loc[(df.continent == "Americas") & (df.year.isin([1987, 2007]))]
+
+countries = (
+    df.loc[(df.continent == "Americas") & (df.year.isin([2007]))]
+    .sort_values(by=["pop"], ascending=True)["country"]
+    .unique()
+)[5:-10]
+
+data = {"x": [], "y": [], "colors": [], "years": []}
+
+for country in countries:
+    data["x"].extend(
+        [
+            df.loc[(df.year == 1987) & (df.country == country)]["pop"].values[0],
+            df.loc[(df.year == 2007) & (df.country == country)]["pop"].values[0],
+            None,
+        ]
+    )
+    data["y"].extend([country, country, None]),
+    data["colors"].extend(["cyan", "darkblue", "white"]),
+    data["years"].extend(["1987", "2007", None])
+
+fig = go.Figure(
+    data=[
+        go.Scatter(
+            x=data["x"],
+            y=data["y"],
+            mode="markers+lines",
+            marker=dict(
+                symbol="arrow",
+                color="royalblue",
+                size=16,
+                angleref="previous",
+                standoff=8,
+            ),
+        ),
+        go.Scatter(
+            x=data["x"],
+            y=data["y"],
+            text=data["years"],
+            mode="markers",
+            marker=dict(
+                color=data["colors"],
+                size=16,
+            ),
+            hovertemplate="""Country: %{y} <br> Population: %{x} <br> Year: %{text} <br><extra></extra>""",
+        ),
+    ]
+)
+
+fig.update_layout(
+    title="Population changes 1987 to 2007",
+    width=1000,
+    height=1000,
+    showlegend=False,
+)
+
+
+fig.show()
+
+```
+
 ### Reference
 
 See https://plotly.com/python/reference/ for more information and chart attribute options!
diff --git a/doc/python/scattermapbox.md b/doc/python/scattermapbox.md
index 57e95452a69..05ff49c7b45 100644
--- a/doc/python/scattermapbox.md
+++ b/doc/python/scattermapbox.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: 1.14.1
   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: 3.7.7
+    version: 3.8.0
   plotly:
     description: How to make scatter plots on Mapbox maps in Python.
     display_as: maps
@@ -245,7 +245,26 @@ fig.update_layout(
 fig.show()
 ```
 
+#### Add Clusters
+
+*New in 5.11*
+
+Display clusters of data points by setting `cluster`. Here, we enable clusters with `enabled=True`. You can also enable clusters by setting other `cluster` properties. Other available properties include `color` (for setting the color of the clusters), `size` (for setting the size of a cluster step), and `step` (for configuring how many points it takes to create a cluster or advance to the next cluster step.
+
+```python
+import plotly.express as px
+import pandas as pd
+
+px.set_mapbox_access_token(open(".mapbox_token").read())
+df = pd.read_csv(
+    "https://raw.githubusercontent.com/plotly/datasets/master/2011_february_us_airport_traffic.csv"
+)
+fig = px.scatter_mapbox(df, lat="lat", lon="long", size="cnt", zoom=3)
+fig.update_traces(cluster=dict(enabled=True))
+fig.show()
+
+```
+
 #### Reference
 
 See [function reference for `px.(scatter_mapbox)`](https://plotly.com/python-api-reference/generated/plotly.express.scatter_mapbox) or https://plotly.com/python/reference/scattermapbox/ for more information and options!
-
diff --git a/doc/python/setting-graph-size.md b/doc/python/setting-graph-size.md
index 65a632dd37a..611e0e29825 100644
--- a/doc/python/setting-graph-size.md
+++ b/doc/python/setting-graph-size.md
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.8.8
+    version: 3.8.0
   plotly:
     description: How to manipulate the graph size, margins and background color.
     display_as: file_settings
@@ -163,6 +163,42 @@ fig.update_layout(
 
 fig.update_yaxes(automargin='left+top')
 
+fig.show()
+```
+
+### Setting a Minimum Plot Size with Automargins
+
+*New in 5.11*
+
+To set a minimum width and height for a plot to be after automargin is applied, use `minreducedwidth` and `minreducedheight`. Here we set both to `250`.
+
+```python
+import plotly.graph_objects as go
+
+
+fig = go.Figure()
+
+fig.add_trace(go.Bar(
+    x=["Apples", "Oranges", "Watermelon", "Pears"],
+    y=[3, 2, 1, 4]
+))
+
+fig.update_layout(
+    autosize=False,
+    minreducedwidth=250,
+    minreducedheight=250,
+    width=450,
+    height=450,
+    yaxis=dict(
+        title_text="Y-axis Title",
+        ticktext=["Label", "Very long label", "Other label", "Very very long label"],
+        tickvals=[1, 2, 3, 4],
+        tickmode="array",
+        titlefont=dict(size=30),
+    )
+)
+
+
 fig.show()
 ```