.. currentmodule:: geomappy.. note:: This tutorial was generated from an IPython notebook that can be
          downloaded `here <../../../source/notebooks/geopandas_integration.ipynb>`_.

.. _geopandas_integration:


Integration of Geomappy into GeoPandas
======================================

.. code:: python

    import geopandas as gpd
    import matplotlib.pyplot as plt
    import geomappy as mp
    import os

.. code:: python

    os.chdir("../../../")

Loading data on river plastic mobilisation when flood events happen
(Roebroek et al., 2021).

.. code:: python

    df1 = gpd.read_file("data/countries/plastic_mobilisation.shp")
    df1.columns




.. parsed-literal::

    Index(['featurecla', 'scalerank', 'LABELRANK', 'SOVEREIGNT', 'SOV_A3',
           'ADM0_DIF', 'LEVEL', 'TYPE', 'ADMIN', 'ADM0_A3',
           ...
           'NAME_ZH', 'e_1', 'e_10', 'e_20', 'e_50', 'e_100', 'e_200', 'e_500',
           'jump', 'geometry'],
          dtype='object', length=103)



Loading data on riverbank plastic observations in the Netherlands (Van
Emmerik et al., 2020)

.. code:: python

    df2 = gpd.read_file("data/processed_data_SDN/df_locations.geojson")
    df2.columns




.. parsed-literal::

    Index(['Gebiedscode', 'river', 'x_maas', 'x_waal', 'geometry'], dtype='object')



Outline on a world map
----------------------

The first file covers the world, while the second file covers the
Netherlands. Both have different projections. Geomappy allows to
visualise it like this:

.. code:: python

    df1.plot_world()
    df2.plot_world()
    plt.show()



.. image:: geopandas_integration_files/geopandas_integration_9_0.png



.. image:: geopandas_integration_files/geopandas_integration_9_1.png


Plotting the data
-----------------

The geomappy plotting functionality (``plot_shapes``) is directly
integrated into geopandas by loading geomappy. This results in the same
figure as seen before:

.. code:: python

    df1.plot_shapes()
    plt.show()



.. image:: geopandas_integration_files/geopandas_integration_12_0.png


.. code:: python

    df2.plot_shapes()
    plt.show()



.. image:: geopandas_integration_files/geopandas_integration_13_0.png


Again all plotting functionaly of ``plot_shapes`` is available. This is
shown here by reproducing the same map as in the tutorial on choropleth
continues shapes tutorial

.. code:: python

    im, cbar = df1.plot_shapes(
        values='e_10',
        cmap="Reds",
        bins=[0,100,1000,10000,100000,1000000, 10000000, 100000000]
    )
    cbar.ax.set_yticklabels([0, "E2", "E3", "E4", "E5", "E6", "E7", "E8"], fontsize=8)
    cbar.set_label("Plastic mobilisation", labelpad=15, rotation=270, fontsize=8)
    plt.show()



.. image:: geopandas_integration_files/geopandas_integration_15_0.png