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fixing up docs
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doc/python/hexbin-mapbox.md

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@@ -6,7 +6,7 @@ jupyter:
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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: 1.5.1
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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
@@ -20,14 +20,14 @@ jupyter:
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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: 3.7.4
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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: scientific
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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: 7
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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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redirect_from: python/hexbin-mapbox/
@@ -55,7 +55,7 @@ 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
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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
@@ -66,13 +66,13 @@ 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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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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#### Display the Underlying Data
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```python
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import plotly.figure_factory as ff
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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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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")
@@ -96,6 +96,7 @@ fig.show()
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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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```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()
@@ -138,7 +140,7 @@ 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)
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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([
@@ -152,6 +154,7 @@ frame = np.concatenate([
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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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