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Library documentation at https://mapbox-mapboxgl-jupyter.readthedocs-hosted.com/en/latest/.
Create Mapbox GL JS <https://www.mapbox.com/mapbox-gl-js/api/>
data
visualizations natively in Jupyter Notebooks with Python and Pandas. mapboxgl
is a high-performance, interactive, WebGL-based data visualization tool that
drops directly into Jupyter. mapboxgl is similar to Folium <https://github.com/python-visualization/folium>
built on top of the raster
Leaflet <http://leafletjs.com/>
__ map library, but with much higher
performance for large data sets using WebGL and Mapbox Vector Tiles.
.. image:: https://cl.ly/3a0K2m1o2j1A/download/Image%202018-02-22%20at%207.16.58%20PM.png
Try out the interactive map example notebooks from the /examples directory in this repository
Categorical points <https://nbviewer.jupyter.org/github/mapbox/mapboxgl-jupyter/blob/master/examples/notebooks/point-viz-categorical-example.ipynb>
__All visualization types <https://nbviewer.jupyter.org/github/mapbox/mapboxgl-jupyter/blob/master/examples/notebooks/point-viz-types-example.ipynb>
__Choropleth Visualization types <https://nbviewer.jupyter.org/github/mapbox/mapboxgl-jupyter/blob/master/examples/notebooks/choropleth-viz-example.ipynb>
__Image Visualization types <https://nbviewer.jupyter.org/github/mapbox/mapboxgl-jupyter/blob/master/examples/notebooks/image-vis-type-example.ipynb>
__Raster Tile Visualization types <https://nbviewer.jupyter.org/github/mapbox/mapboxgl-jupyter/blob/master/examples/notebooks/rastertile-viz-type-example.ipynb>
__.. code-block:: bash
$ pip install mapboxgl
Documentation is on Read The Docs at https://mapbox-mapboxgl-jupyter.readthedocs-hosted.com/en/latest/.
The examples
directory contains sample Jupyter notebooks demonstrating usage.
.. code-block:: python
import os
import pandas as pd
from mapboxgl.utils import create_color_stops, df_to_geojson
from mapboxgl.viz import CircleViz
# Load data from sample csv
data_url = 'https://raw.githubusercontent.com/mapbox/mapboxgl-jupyter/master/examples/data/points.csv'
df = pd.read_csv(data_url)
# Must be a public token, starting with `pk`
token = os.getenv('MAPBOX_ACCESS_TOKEN')
# Create a geojson file export from a Pandas dataframe
df_to_geojson(df, filename='points.geojson',
properties=['Avg Medicare Payments', 'Avg Covered Charges', 'date'],
lat='lat', lon='lon', precision=3)
# Generate data breaks and color stops from colorBrewer
color_breaks = [0,10,100,1000,10000]
color_stops = create_color_stops(color_breaks, colors='YlGnBu')
# Create the viz from the dataframe
viz = CircleViz('points.geojson',
access_token=token,
height='400px',
color_property = "Avg Medicare Payments",
color_stops = color_stops,
center = (-95, 40),
zoom = 3,
below_layer = 'waterway-label'
)
viz.show()
Install the python library locally with pip:
.. code-block:: console
$ pip install -e .
To run tests use pytest:
.. code-block:: console
$ pip install mock pytest $ python -m pytest
To run the Jupyter examples,
.. code-block:: console
$ cd examples $ pip install jupyter $ jupyter notebook
We follow the PEP8 style guide for Python <http://www.python.org/dev/peps/pep-0008/>
__ for all Python code.
git checkout master
git pull
mapboxgl/__init__.py
and push directly to master.git tag <version>
git push --tags
pip install twine
and set up your credentials in a ~/.pypirc <https://docs.python.org/2/distutils/packageindex.html#pypirc>
file <https://docs.python.org/2/distutils/packageindex.html#pypirc>
.rm dist/*
# clean out old releases if they existpython setup.py sdist bdist_wheel
twine upload dist/mapboxgl-*