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Merge pull request #2638 from plotly/hexbin
Finishing up Hexbin Mapbox PR
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‎CHANGELOG.md

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@@ -11,6 +11,7 @@ This project adheres to [Semantic Versioning](http://semver.org/).
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- `facet_row_spacing` and `facet_col_spacing` added to Plotly Express cartesian 2d functions ([#2614](https://github.com/plotly/plotly.py/pull/2614))
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- `base` added to Plotly Express `bar` and `bar_polar` functions
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- `plotly.express.timeline()` added as an official alternative to `plotly.figure_factories.create_gantt()`
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- `create_hexbin_mapbox()` added to Figure Factories, with thanks to [@RenaudLN](https://github.com/RenaudLN) for the contribution!
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### Fixed
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- `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))
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## [4.8.2] - 2020-06-26
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### Updated
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- `px.line` now sets `line_group=<variable>` in wide mode by default ([#2599](https://github.com/plotly/plotly.py/pull/2599))
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- Corrected some regex warnings ([#2577](https://github.com/plotly/plotly.py/pull/2577)), with thanks to [@georgevdd](https://github.com/georgevdd) for the contribution!
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## [4.8.1] - 2020-05-28
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### Fixed

‎doc/python/figure-factories.md

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* [Annotated Heatmaps](/python/annotated-heatmap/)
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* [Dendrograms](/python/dendrogram/)
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* [Hexagonal Binning Tile Map](/python/hexbin-mapbox/)
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* [Quiver Plots](/python/quiver-plots/)
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* [Streamline Plots](/python/streamline-plots/)
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* [Tables](/python/figure-factory-table/)

‎doc/python/hexbin-mapbox.md

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---
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jupyter:
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jupytext:
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notebook_metadata_filter: all
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text_representation:
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extension: .md
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format_name: markdown
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format_version: '1.2'
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jupytext_version: 1.4.2
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kernelspec:
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display_name: Python 3
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language: python
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name: python3
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language_info:
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codemirror_mode:
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name: ipython
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version: 3
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file_extension: .py
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mimetype: text/x-python
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.7.7
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plotly:
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description: How to make a map with Hexagonal Binning of data in Python with Plotly.
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display_as: maps
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language: python
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layout: base
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name: Hexbin Mapbox
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order: 13
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page_type: u-guide
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permalink: python/hexbin-mapbox/
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thumbnail: thumbnail/hexbin_mapbox.jpg
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---
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#### Simple Count Hexbin
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This page details the use of a [figure factory](/python/figure-factories/). For more examples with Choropleth maps, see [this page](/python/choropleth-maps/).
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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/).
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```python
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import plotly.figure_factory as ff
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import plotly.express as px
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px.set_mapbox_access_token(open(".mapbox_token").read())
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df = px.data.carshare()
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fig = ff.create_hexbin_mapbox(
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data_frame=df, lat="centroid_lat", lon="centroid_lon",
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nx_hexagon=10, opacity=0.9, labels={"color": "Point Count"},
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)
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fig.update_layout(margin=dict(b=0, t=0, l=0, r=0))
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fig.show()
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```
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#### Count Hexbin with Minimum Count and Opacity
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```python
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import plotly.figure_factory as ff
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import plotly.express as px
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px.set_mapbox_access_token(open(".mapbox_token").read())
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df = px.data.carshare()
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fig = ff.create_hexbin_mapbox(
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data_frame=df, lat="centroid_lat", lon="centroid_lon",
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nx_hexagon=10, opacity=0.5, labels={"color": "Point Count"},
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min_count=1,
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)
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fig.show()
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```
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#### Display the Underlying Data
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```python
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import plotly.figure_factory as ff
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import plotly.express as px
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px.set_mapbox_access_token(open(".mapbox_token").read())
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df = px.data.carshare()
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fig = ff.create_hexbin_mapbox(
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data_frame=df, lat="centroid_lat", lon="centroid_lon",
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nx_hexagon=10, opacity=0.5, labels={"color": "Point Count"},
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min_count=1, color_continuous_scale="Viridis",
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show_original_data=True,
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original_data_marker=dict(size=4, opacity=0.6, color="deeppink")
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)
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fig.show()
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```
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#### Compute the Mean Value per Hexbin
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```python
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import plotly.figure_factory as ff
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import plotly.express as px
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import numpy as np
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px.set_mapbox_access_token(open(".mapbox_token").read())
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df = px.data.carshare()
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fig = ff.create_hexbin_mapbox(
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data_frame=df, lat="centroid_lat", lon="centroid_lon",
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nx_hexagon=10, opacity=0.9, labels={"color": "Average Peak Hour"},
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color="peak_hour", agg_func=np.mean, color_continuous_scale="Icefire", range_color=[0,23]
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)
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fig.show()
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```
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#### Compute the Sum Value per Hexbin
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```python
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import plotly.figure_factory as ff
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import plotly.express as px
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import numpy as np
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px.set_mapbox_access_token(open(".mapbox_token").read())
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df = px.data.carshare()
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fig = ff.create_hexbin_mapbox(
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data_frame=df, lat="centroid_lat", lon="centroid_lon",
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nx_hexagon=10, opacity=0.9, labels={"color": "Summed Car.Hours"},
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color="car_hours", agg_func=np.sum, color_continuous_scale="Magma"
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)
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fig.show()
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```
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#### Hexbin with Animation
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```python
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import plotly.figure_factory as ff
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import plotly.express as px
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import numpy as np
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px.set_mapbox_access_token(open(".mapbox_token").read())
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np.random.seed(0)
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N = 500
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n_frames = 12
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lat = np.concatenate([
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np.random.randn(N) * 0.5 + np.cos(i / n_frames * 2 * np.pi) + 10
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for i in range(n_frames)
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])
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lon = np.concatenate([
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np.random.randn(N) * 0.5 + np.sin(i / n_frames * 2 * np.pi)
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for i in range(n_frames)
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])
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frame = np.concatenate([
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np.ones(N, int) * i for i in range(n_frames)
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])
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fig = ff.create_hexbin_mapbox(
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lat=lat, lon=lon, nx_hexagon=15, animation_frame=frame,
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color_continuous_scale="Cividis", labels={"color": "Point Count", "frame": "Period"},
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opacity=0.5, min_count=1,
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show_original_data=True, original_data_marker=dict(opacity=0.6, size=4, color="deeppink")
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)
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fig.update_layout(margin=dict(b=0, t=0, l=0, r=0))
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fig.layout.sliders[0].pad.t=20
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fig.layout.updatemenus[0].pad.t=40
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fig.show()
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```
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#### Reference
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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)

‎packages/python/plotly/plotly/figure_factory/__init__.py

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if optional_imports.get_module("pandas") is not None:
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from plotly.figure_factory._county_choropleth import create_choropleth
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from plotly.figure_factory._hexbin_mapbox import create_hexbin_mapbox
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else:
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def create_choropleth(*args, **kwargs):
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raise ImportError("Please install pandas to use `create_choropleth`")
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def create_hexbin_mapbox(*args, **kwargs):
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raise ImportError("Please install pandas to use `create_hexbin_mapbox`")
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if optional_imports.get_module("skimage") is not None:
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from plotly.figure_factory._ternary_contour import create_ternary_contour
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"create_distplot",
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"create_facet_grid",
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"create_gantt",
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"create_hexbin_mapbox",
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"create_ohlc",
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"create_quiver",
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"create_scatterplotmatrix",

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