- `create_hexbin_mapbox()` added to Figure Factories, with thanks to [@RenaudLN](https://github.com/RenaudLN) for the contribution!

* [Hexagonal Binning Tile Map](/python/hexbin-mapbox/)

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

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/).

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()

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()

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()

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()

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()

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,

show_original_data=True, original_data_marker=dict(opacity=0.6, size=4, color="deeppink")

)

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()

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)

from plotly.figure_factory._hexbin_mapbox import create_hexbin_mapbox

def create_hexbin_mapbox(*args, **kwargs):

raise ImportError("Please install pandas to use `create_hexbin_mapbox`")

"create_hexbin_mapbox",