.. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_plot_choropleth_map_unemployment_by_state.py: Unemployment rate by state ========================== In this example we'll visualize the most recent data on brazilian unemployment per state. Let's again retrieve the data with the `seriesbr `_ package. .. code-block:: default from seriesbr import ibge df = ibge.get_series( 4095, 4099, last_n=1, states=True ) Now let's convert this ``DataFrame`` into a ``GeoDataFrame`` after getting the geometric objects for each state. .. code-block:: default import geopandas as gpd from mapsbr import ibgemaps df = df.assign(geometry=ibgemaps.geocode(df["Unidade da Federação (Código)"])) gdf = gpd.GeoDataFrame(df) Now let's plot it. .. code-block:: default import matplotlib.pyplot as plt fig, ax = plt.subplots() ax.axis("off") gdf.plot(column="Valor", cmap="OrRd", legend=True, ax=ax) plt.show() .. image:: /auto_examples/images/sphx_glr_plot_choropleth_map_unemployment_by_state_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 8.666 seconds) **Estimated memory usage:** 9 MB .. _sphx_glr_download_auto_examples_plot_choropleth_map_unemployment_by_state.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download :download:`Download Python source code: plot_choropleth_map_unemployment_by_state.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: plot_choropleth_map_unemployment_by_state.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_