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223 lines
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223 lines
7.1 KiB
ReStructuredText
Geometric Manipulations
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========================
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*geopandas* makes available all the tools for geometric manipulations in the `*shapely* library <http://toblerity.org/shapely/manual.html>`_.
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Note that documentation for all set-theoretic tools for creating new shapes using the relationship between two different spatial datasets -- like creating intersections, or differences -- can be found on the :doc:`set operations <set_operations>` page.
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Constructive Methods
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~~~~~~~~~~~~~~~~~~~~
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.. method:: GeoSeries.buffer(distance, resolution=16)
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Returns a ``GeoSeries`` of geometries representing all points within a given `distance`
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of each geometric object.
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.. attribute:: GeoSeries.boundary
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Returns a ``GeoSeries`` of lower dimensional objects representing
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each geometries's set-theoretic `boundary`.
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.. attribute:: GeoSeries.centroid
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Returns a ``GeoSeries`` of points for each geometric centroid.
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.. attribute:: GeoSeries.convex_hull
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Returns a ``GeoSeries`` of geometries representing the smallest
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convex `Polygon` containing all the points in each object unless the
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number of points in the object is less than three. For two points,
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the convex hull collapses to a `LineString`; for 1, a `Point`.
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.. attribute:: GeoSeries.envelope
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Returns a ``GeoSeries`` of geometries representing the point or
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smallest rectangular polygon (with sides parallel to the coordinate
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axes) that contains each object.
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.. method:: GeoSeries.simplify(tolerance, preserve_topology=True)
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Returns a ``GeoSeries`` containing a simplified representation of
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each object.
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.. attribute:: GeoSeries.unary_union
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Return a geometry containing the union of all geometries in the ``GeoSeries``.
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Affine transformations
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~~~~~~~~~~~~~~~~~~~~~~~~
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.. method:: GeoSeries.rotate(self, angle, origin='center', use_radians=False)
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Rotate the coordinates of the GeoSeries.
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.. method:: GeoSeries.scale(self, xfact=1.0, yfact=1.0, zfact=1.0, origin='center')
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Scale the geometries of the GeoSeries along each (x, y, z) dimensio.
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.. method:: GeoSeries.skew(self, angle, origin='center', use_radians=False)
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Shear/Skew the geometries of the GeoSeries by angles along x and y dimensions.
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.. method:: GeoSeries.translate(self, angle, origin='center', use_radians=False)
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Shift the coordinates of the GeoSeries.
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Examples of Geometric Manipulations
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------------------------------------
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.. sourcecode:: python
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>>> p1 = Polygon([(0, 0), (1, 0), (1, 1)])
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>>> p2 = Polygon([(0, 0), (1, 0), (1, 1), (0, 1)])
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>>> p3 = Polygon([(2, 0), (3, 0), (3, 1), (2, 1)])
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>>> g = GeoSeries([p1, p2, p3])
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>>> g
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0 POLYGON ((0.0000000000000000 0.000000000000000...
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1 POLYGON ((0.0000000000000000 0.000000000000000...
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2 POLYGON ((2.0000000000000000 0.000000000000000...
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dtype: object
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.. image:: _static/test.png
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Some geographic operations return normal pandas object. The ``area`` property of a ``GeoSeries`` will return a ``pandas.Series`` containing the area of each item in the ``GeoSeries``:
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.. sourcecode:: python
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>>> print g.area
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0 0.5
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1 1.0
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2 1.0
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dtype: float64
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Other operations return GeoPandas objects:
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.. sourcecode:: python
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>>> g.buffer(0.5)
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Out[15]:
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0 POLYGON ((-0.3535533905932737 0.35355339059327...
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1 POLYGON ((-0.5000000000000000 0.00000000000000...
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2 POLYGON ((1.5000000000000000 0.000000000000000...
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dtype: object
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.. image:: _static/test_buffer.png
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GeoPandas objects also know how to plot themselves. GeoPandas uses `descartes`_ to generate a `matplotlib`_ plot. To generate a plot of our GeoSeries, use:
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.. sourcecode:: python
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>>> g.plot()
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GeoPandas also implements alternate constructors that can read any data format recognized by `fiona`_. To read a `file containing the boroughs of New York City`_:
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.. sourcecode:: python
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>>> boros = GeoDataFrame.from_file('nybb.shp')
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>>> boros.set_index('BoroCode', inplace=True)
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>>> boros.sort()
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>>> boros
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BoroName Shape_Area Shape_Leng \
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BoroCode
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1 Manhattan 6.364422e+08 358532.956418
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2 Bronx 1.186804e+09 464517.890553
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3 Brooklyn 1.959432e+09 726568.946340
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4 Queens 3.049947e+09 861038.479299
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5 Staten Island 1.623853e+09 330385.036974
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geometry
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BoroCode
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1 (POLYGON ((981219.0557861328125000 188655.3157...
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2 (POLYGON ((1012821.8057861328125000 229228.264...
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3 (POLYGON ((1021176.4790039062500000 151374.796...
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4 (POLYGON ((1029606.0765991210937500 156073.814...
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5 (POLYGON ((970217.0223999023437500 145643.3322...
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.. image:: _static/nyc.png
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.. sourcecode:: python
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>>> boros['geometry'].convex_hull
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0 POLYGON ((915517.6877458114176989 120121.88125...
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1 POLYGON ((1000721.5317993164062500 136681.7761...
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2 POLYGON ((988872.8212280273437500 146772.03179...
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3 POLYGON ((977855.4451904296875000 188082.32238...
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4 POLYGON ((1017949.9776000976562500 225426.8845...
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dtype: object
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.. image:: _static/nyc_hull.png
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To demonstrate a more complex operation, we'll generate a
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``GeoSeries`` containing 2000 random points:
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.. sourcecode:: python
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>>> from shapely.geometry import Point
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>>> xmin, xmax, ymin, ymax = 900000, 1080000, 120000, 280000
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>>> xc = (xmax - xmin) * np.random.random(2000) + xmin
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>>> yc = (ymax - ymin) * np.random.random(2000) + ymin
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>>> pts = GeoSeries([Point(x, y) for x, y in zip(xc, yc)])
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Now draw a circle with fixed radius around each point:
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.. sourcecode:: python
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>>> circles = pts.buffer(2000)
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We can collapse these circles into a single shapely MultiPolygon
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geometry with
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.. sourcecode:: python
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>>> mp = circles.unary_union
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To extract the part of this geometry contained in each borough, we can
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just use:
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.. sourcecode:: python
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>>> holes = boros['geometry'].intersection(mp)
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.. image:: _static/holes.png
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and to get the area outside of the holes:
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.. sourcecode:: python
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>>> boros_with_holes = boros['geometry'].difference(mp)
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.. image:: _static/boros_with_holes.png
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Note that this can be simplified a bit, since ``geometry`` is
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available as an attribute on a ``GeoDataFrame``, and the
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``intersection`` and ``difference`` methods are implemented with the
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"&" and "-" operators, respectively. For example, the latter could
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have been expressed simply as ``boros.geometry - mp``.
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It's easy to do things like calculate the fractional area in each
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borough that are in the holes:
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.. sourcecode:: python
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>>> holes.area / boros.geometry.area
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BoroCode
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1 0.602015
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2 0.523457
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3 0.585901
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4 0.577020
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5 0.559507
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dtype: float64
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.. _Descartes: https://pypi.python.org/pypi/descartes
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.. _matplotlib: http://matplotlib.org
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.. _fiona: http://toblerity.github.io/fiona
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.. _geopy: https://github.com/geopy/geopy
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.. _geo_interface: https://gist.github.com/sgillies/2217756
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.. _file containing the boroughs of New York City: http://www.nyc.gov/html/dcp/download/bytes/nybb_14aav.zip
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.. toctree::
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:maxdepth: 2
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