plotly
diff --git a/‎CHANGELOG.md
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diff --git a/‎doc/python/figure-factories.md
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diff --git a/‎doc/python/hexbin-mapbox.md
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diff --git a/‎packages/python/plotly/plotly/figure_factory/__init__.py
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@@ -11,6 +11,7 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 - `facet_row_spacing` and `facet_col_spacing` added to Plotly Express cartesian 2d functions ([#2614](https://github.com/plotly/plotly.py/pull/2614))
 - `base` added to Plotly Express `bar` and `bar_polar` functions
 - `plotly.express.timeline()` added as an official alternative to `plotly.figure_factories.create_gantt()`
+-  `create_hexbin_mapbox()` added to Figure Factories, with thanks to [@RenaudLN](https://github.com/RenaudLN) for the contribution!
 
 ### Fixed
 
@@ -22,8 +23,6 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 - `plotly.express.imshow` now uses data frame index and columns names and values to populate axis parameters by default ([#2539](https://github.com/plotly/plotly.py/pull/2539))
 
 
-
-
 ## [4.8.2] - 2020-06-26
 
 ### Updated
@@ -43,6 +42,7 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 - `px.line` now sets `line_group=<variable>` in wide mode by default ([#2599](https://github.com/plotly/plotly.py/pull/2599))
 - Corrected some regex warnings ([#2577](https://github.com/plotly/plotly.py/pull/2577)), with thanks to [@georgevdd](https://github.com/georgevdd) for the contribution!
 
+
 ## [4.8.1] - 2020-05-28
 
 ### Fixed
 
@@ -41,6 +41,7 @@ The following types of plots are still difficult to create with Graph Objects or
 
   * [Annotated Heatmaps](/python/annotated-heatmap/)
   * [Dendrograms](/python/dendrogram/)
+  * [Hexagonal Binning Tile Map](/python/hexbin-mapbox/)
   * [Quiver Plots](/python/quiver-plots/)
   * [Streamline Plots](/python/streamline-plots/)
   * [Tables](/python/figure-factory-table/)
 
@@ -0,0 +1,167 @@
+---
+jupyter:
+  jupytext:
+    notebook_metadata_filter: all
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.2'
+      jupytext_version: 1.4.2
+  kernelspec:
+    display_name: Python 3
+    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: 3.7.7
+  plotly:
+    description: How to make a map with Hexagonal Binning of data in Python with Plotly.
+    display_as: maps
+    language: python
+    layout: base
+    name: Hexbin Mapbox
+    order: 13
+    page_type: u-guide
+    permalink: python/hexbin-mapbox/
+    thumbnail: thumbnail/hexbin_mapbox.jpg
+---
+
+#### Simple Count Hexbin
+
+This page details the use of a [figure factory](/python/figure-factories/). For more examples with Choropleth maps, see [this page](/python/choropleth-maps/).
+
+In order to use mapbox styles that require a mapbox token, set the token with `plotly.express`. You can also use styles that do not require a mapbox token. See more information on [this page](/python/mapbox-layers/).
+
+```python
+import plotly.figure_factory as ff
+import plotly.express as px
+
+px.set_mapbox_access_token(open(".mapbox_token").read())
+df = px.data.carshare()
+
+fig = ff.create_hexbin_mapbox(
+    data_frame=df, lat="centroid_lat", lon="centroid_lon",
+    nx_hexagon=10, opacity=0.9, labels={"color": "Point Count"},
+)
+fig.update_layout(margin=dict(b=0, t=0, l=0, r=0))
+fig.show()
+```
+
+#### Count Hexbin with Minimum Count and Opacity
+
+```python
+import plotly.figure_factory as ff
+import plotly.express as px
+
+px.set_mapbox_access_token(open(".mapbox_token").read())
+df = px.data.carshare()
+
+fig = ff.create_hexbin_mapbox(
+    data_frame=df, lat="centroid_lat", lon="centroid_lon",
+    nx_hexagon=10, opacity=0.5, labels={"color": "Point Count"},
+    min_count=1,
+)
+fig.show()
+```
+
+#### Display the Underlying Data
+
+```python
+import plotly.figure_factory as ff
+import plotly.express as px
+
+px.set_mapbox_access_token(open(".mapbox_token").read())
+df = px.data.carshare()
+
+fig = ff.create_hexbin_mapbox(
+    data_frame=df, lat="centroid_lat", lon="centroid_lon",
+    nx_hexagon=10, opacity=0.5, labels={"color": "Point Count"},
+    min_count=1, color_continuous_scale="Viridis",
+    show_original_data=True,
+    original_data_marker=dict(size=4, opacity=0.6, color="deeppink")
+)
+fig.show()
+```
+
+#### Compute the Mean Value per Hexbin
+
+```python
+import plotly.figure_factory as ff
+import plotly.express as px
+import numpy as np
+
+px.set_mapbox_access_token(open(".mapbox_token").read())
+df = px.data.carshare()
+
+fig = ff.create_hexbin_mapbox(
+    data_frame=df, lat="centroid_lat", lon="centroid_lon",
+    nx_hexagon=10, opacity=0.9, labels={"color": "Average Peak Hour"},
+    color="peak_hour", agg_func=np.mean, color_continuous_scale="Icefire", range_color=[0,23]
+)
+fig.show()
+```
+
+#### Compute the Sum Value per Hexbin
+
+```python
+import plotly.figure_factory as ff
+import plotly.express as px
+import numpy as np
+
+px.set_mapbox_access_token(open(".mapbox_token").read())
+df = px.data.carshare()
+
+fig = ff.create_hexbin_mapbox(
+    data_frame=df, lat="centroid_lat", lon="centroid_lon",
+    nx_hexagon=10, opacity=0.9, labels={"color": "Summed Car.Hours"},
+    color="car_hours", agg_func=np.sum, color_continuous_scale="Magma"
+)
+fig.show()
+```
+
+#### Hexbin with Animation
+
+```python
+import plotly.figure_factory as ff
+import plotly.express as px
+import numpy as np
+
+px.set_mapbox_access_token(open(".mapbox_token").read())
+np.random.seed(0)
+
+N = 500
+n_frames = 12
+lat = np.concatenate([
+    np.random.randn(N) * 0.5 + np.cos(i / n_frames * 2 * np.pi) + 10
+    for i in range(n_frames)
+])
+lon = np.concatenate([
+    np.random.randn(N) * 0.5 + np.sin(i / n_frames * 2 * np.pi)
+    for i in range(n_frames)
+])
+frame = np.concatenate([
+    np.ones(N, int) * i for i in range(n_frames)
+])
+
+fig = ff.create_hexbin_mapbox(
+    lat=lat, lon=lon, nx_hexagon=15, animation_frame=frame,
+    color_continuous_scale="Cividis", labels={"color": "Point Count", "frame": "Period"},
+    opacity=0.5, min_count=1,
+)
+fig.update_layout(margin=dict(b=0, t=0, l=0, r=0))
+fig.layout.sliders[0].pad.t=20
+fig.layout.updatemenus[0].pad.t=40
+fig.show()
+```
+
+#### Reference
+
+For more info on Plotly maps, see: https://plotly.com/python/maps.<br> For more info on using colorscales with Plotly see: https://plotly.com/python/heatmap-and-contour-colorscales/ <br>For more info on `ff.create_annotated_heatmap()`, see the [full function reference](https://plotly.com/python-api-reference/generated/plotly.figure_factory.create_hexbin_mapbox.html#plotly.figure_factory.create_hexbin_mapbox)
@@ -29,11 +29,15 @@
 
 if optional_imports.get_module("pandas") is not None:
     from plotly.figure_factory._county_choropleth import create_choropleth
+    from plotly.figure_factory._hexbin_mapbox import create_hexbin_mapbox
 else:
 
     def create_choropleth(*args, **kwargs):
         raise ImportError("Please install pandas to use `create_choropleth`")
 
+    def create_hexbin_mapbox(*args, **kwargs):
+        raise ImportError("Please install pandas to use `create_hexbin_mapbox`")
+
 
 if optional_imports.get_module("skimage") is not None:
     from plotly.figure_factory._ternary_contour import create_ternary_contour
@@ -53,6 +57,7 @@ def create_ternary_contour(*args, **kwargs):
     "create_distplot",
     "create_facet_grid",
     "create_gantt",
+    "create_hexbin_mapbox",
     "create_ohlc",
     "create_quiver",
     "create_scatterplotmatrix",