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.. currentmodule:: geopandas
.. ipython:: python
:suppress:
import geopandas
Indexing and selecting data
===========================
GeoPandas inherits the standard pandas_ methods for indexing/selecting data. This includes label based indexing with :attr:`~pandas.DataFrame.loc` and integer position based indexing with :attr:`~pandas.DataFrame.iloc`, which apply to both :class:`GeoSeries` and :class:`GeoDataFrame` objects. For more information on indexing/selecting, see the pandas_ documentation.
.. _pandas: http://pandas.pydata.org/pandas-docs/stable/indexing.html
In addition to the standard pandas_ methods, GeoPandas also provides
coordinate based indexing with the :attr:`~GeoDataFrame.cx` indexer, which slices using a bounding
box. Geometries in the :class:`GeoSeries` or :class:`GeoDataFrame` that intersect the
bounding box will be returned.
Using the ``geoda.chile_labor`` dataset, you can use this functionality to quickly select parts
of Chile whose boundaries extend south of the -50 degrees latitude. You can first check the original GeoDataFrame.
.. ipython:: python
import geodatasets
chile = geopandas.read_file(geodatasets.get_path('geoda.chile_labor'))
@savefig chile.png
chile.plot(figsize=(8, 8));
And then select only the southern part of the country.
.. ipython:: python
southern_chile = chile.cx[:, :-50]
@savefig chile_southern.png
southern_chile.plot(figsize=(8, 8));
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