.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "gallery/plot_dc_street_network.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_plot_dc_street_network.py: Sankey of traffic volumes in Washington DC ========================================== This example plots `annual average daily traffic volume `_ in Washington DC. .. GENERATED FROM PYTHON SOURCE LINES 9-23 .. image:: /gallery/images/sphx_glr_plot_dc_street_network_001.png :alt: Streets in Washington DC by Average Daily Traffic, 2015 :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none Text(0.5, 1.0, 'Streets in Washington DC by Average Daily Traffic, 2015') | .. code-block:: default import geopandas as gpd import geoplot as gplt import geoplot.crs as gcrs import matplotlib.pyplot as plt dc_roads = gpd.read_file(gplt.datasets.get_path('dc_roads')) gplt.sankey( dc_roads, projection=gcrs.AlbersEqualArea(), scale='aadt', limits=(0.1, 10), color='black' ) plt.title("Streets in Washington DC by Average Daily Traffic, 2015") .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 9.184 seconds) .. _sphx_glr_download_gallery_plot_dc_street_network.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_dc_street_network.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_dc_street_network.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_