mirror of
https://github.com/wassname/geopandas.git
synced 2026-09-23 13:20:36 +08:00
Murat Can ÜsteandMartin Fleischmann
e2c5b0d978
* DOC: added API links to intersphinx mapping * DOC: updated mergingdata.rst links * DOC: updated aggregation_with_dissolve.rst links * DOC: updated data_structures.rst links * DOC: updated geocoding.rst links * DOC: updated geometric_manipulations.rst links * DOC: updated indexing.rst links * DOC: updated io.rst links * DOC: updated projections.rst links * DOC: updated set_operations.rst links * DOC: updated mapping.rst links * DOC: updated missing_empty.rst links * DOC: updated geoplot intersphinx links * DOC: make 'unary_union' attr instead of method Co-authored-by: Martin Fleischmann <martin@martinfleischmann.net> * DOC: remove link to GeoDataFrame.geometry Co-authored-by: Martin Fleischmann <martin@martinfleischmann.net> * DOC: convert pandas indexers to attrs instead of methods Co-authored-by: Martin Fleischmann <martin@martinfleischmann.net> * DOC: convert indexer 'cx' to attr instead of method Co-authored-by: Martin Fleischmann <martin@martinfleischmann.net> * DOC: refer GeoSeries.buffer instead of shapely buffer Co-authored-by: Martin Fleischmann <martin@martinfleischmann.net> * DOC: make 'unary_union' attr instead of method on missing_empty.rst Co-authored-by: Martin Fleischmann <martin@martinfleischmann.net> * DOC: refer to DataFrame.merge instead of pandas.merge Co-authored-by: Martin Fleischmann <martin@martinfleischmann.net> * DOC: link pyproj.CRS * DOC: changed API links to 'stable' from 'latest' * DOC: fixed separator length * DOC: uppercase CRS in pyproj.crs Co-authored-by: Martin Fleischmann <martin@martinfleischmann.net>
233 lines
7.8 KiB
ReStructuredText
233 lines
7.8 KiB
ReStructuredText
.. _geometric_manipulations:
|
|
|
|
Geometric Manipulations
|
|
========================
|
|
|
|
*geopandas* makes available all the tools for geometric manipulations in the `shapely library <http://shapely.readthedocs.io/en/latest/manual.html>`_.
|
|
|
|
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.
|
|
|
|
Constructive Methods
|
|
~~~~~~~~~~~~~~~~~~~~
|
|
|
|
.. method:: GeoSeries.buffer(distance, resolution=16)
|
|
|
|
Returns a :class:`~geopandas.GeoSeries` of geometries representing all points within a given `distance`
|
|
of each geometric object.
|
|
|
|
.. attribute:: GeoSeries.boundary
|
|
|
|
Returns a :class:`~geopandas.GeoSeries` of lower dimensional objects representing
|
|
each geometries's set-theoretic `boundary`.
|
|
|
|
.. attribute:: GeoSeries.centroid
|
|
|
|
Returns a :class:`~geopandas.GeoSeries` of points for each geometric centroid.
|
|
|
|
.. attribute:: GeoSeries.convex_hull
|
|
|
|
Returns a :class:`~geopandas.GeoSeries` of geometries representing the smallest
|
|
convex `Polygon` containing all the points in each object unless the
|
|
number of points in the object is less than three. For two points,
|
|
the convex hull collapses to a `LineString`; for 1, a `Point`.
|
|
|
|
.. attribute:: GeoSeries.envelope
|
|
|
|
Returns a :class:`~geopandas.GeoSeries` of geometries representing the point or
|
|
smallest rectangular polygon (with sides parallel to the coordinate
|
|
axes) that contains each object.
|
|
|
|
.. method:: GeoSeries.simplify(tolerance, preserve_topology=True)
|
|
|
|
Returns a :class:`~geopandas.GeoSeries` containing a simplified representation of
|
|
each object.
|
|
|
|
.. attribute:: GeoSeries.unary_union
|
|
|
|
Return a geometry containing the union of all geometries in the :class:`~geopandas.GeoSeries`.
|
|
|
|
|
|
Affine transformations
|
|
~~~~~~~~~~~~~~~~~~~~~~~~
|
|
|
|
.. method:: GeoSeries.affine_transform(self, matrix)
|
|
|
|
Transform the geometries of the :class:`~geopandas.GeoSeries` using an affine transformation matrix
|
|
|
|
.. method:: GeoSeries.rotate(self, angle, origin='center', use_radians=False)
|
|
|
|
Rotate the coordinates of the :class:`~geopandas.GeoSeries`.
|
|
|
|
.. method:: GeoSeries.scale(self, xfact=1.0, yfact=1.0, zfact=1.0, origin='center')
|
|
|
|
Scale the geometries of the :class:`~geopandas.GeoSeries` along each (x, y, z) dimensio.
|
|
|
|
.. method:: GeoSeries.skew(self, angle, origin='center', use_radians=False)
|
|
|
|
Shear/Skew the geometries of the :class:`~geopandas.GeoSeries` by angles along x and y dimensions.
|
|
|
|
.. method:: GeoSeries.translate(self, xoff=0.0, yoff=0.0, zoff=0.0)
|
|
|
|
Shift the coordinates of the :class:`~geopandas.GeoSeries`.
|
|
|
|
|
|
|
|
Examples of Geometric Manipulations
|
|
------------------------------------
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> import geopandas
|
|
>>> from geopandas import GeoSeries
|
|
>>> from shapely.geometry import Polygon
|
|
>>> p1 = Polygon([(0, 0), (1, 0), (1, 1)])
|
|
>>> p2 = Polygon([(0, 0), (1, 0), (1, 1), (0, 1)])
|
|
>>> p3 = Polygon([(2, 0), (3, 0), (3, 1), (2, 1)])
|
|
>>> g = GeoSeries([p1, p2, p3])
|
|
>>> g
|
|
0 POLYGON ((0 0, 1 0, 1 1, 0 0))
|
|
1 POLYGON ((0 0, 1 0, 1 1, 0 1, 0 0))
|
|
2 POLYGON ((2 0, 3 0, 3 1, 2 1, 2 0))
|
|
dtype: geometry
|
|
|
|
.. image:: ../../_static/test.png
|
|
|
|
Some geographic operations return normal pandas object. The :attr:`~geopandas.GeoSeries.area` property of a :class:`~geopandas.GeoSeries` will return a :class:`pandas.Series` containing the area of each item in the :class:`~geopandas.GeoSeries`:
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> print(g.area)
|
|
0 0.5
|
|
1 1.0
|
|
2 1.0
|
|
dtype: float64
|
|
|
|
Other operations return GeoPandas objects:
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> g.buffer(0.5)
|
|
0 POLYGON ((-0.3535533905932737 0.35355339059327...
|
|
1 POLYGON ((-0.5 0, -0.5 1, -0.4975923633360985 ...
|
|
2 POLYGON ((1.5 0, 1.5 1, 1.502407636663901 1.04...
|
|
dtype: geometry
|
|
|
|
.. image:: ../../_static/test_buffer.png
|
|
|
|
GeoPandas objects also know how to plot themselves. GeoPandas uses `matplotlib`_ for plotting. To generate a plot of our GeoSeries, use:
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> g.plot()
|
|
|
|
GeoPandas also implements alternate constructors that can read any data format recognized by `fiona`_. To read a zip file containing an ESRI shapefile with the `borough boundaries of New York City`_ (GeoPandas includes this as an example dataset):
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> nybb_path = geopandas.datasets.get_path('nybb')
|
|
>>> boros = geopandas.read_file(nybb_path)
|
|
>>> boros.set_index('BoroCode', inplace=True)
|
|
>>> boros.sort_index(inplace=True)
|
|
>>> boros
|
|
BoroName Shape_Leng Shape_Area \
|
|
BoroCode
|
|
1 Manhattan 359299.096471 6.364715e+08
|
|
2 Bronx 464392.991824 1.186925e+09
|
|
3 Brooklyn 741080.523166 1.937479e+09
|
|
4 Queens 896344.047763 3.045213e+09
|
|
5 Staten Island 330470.010332 1.623820e+09
|
|
|
|
geometry
|
|
BoroCode
|
|
1 MULTIPOLYGON (((981219.0557861328 188655.31579...
|
|
2 MULTIPOLYGON (((1012821.805786133 229228.26458...
|
|
3 MULTIPOLYGON (((1021176.479003906 151374.79699...
|
|
4 MULTIPOLYGON (((1029606.076599121 156073.81420...
|
|
5 MULTIPOLYGON (((970217.0223999023 145643.33221...
|
|
|
|
.. image:: ../../_static/nyc.png
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> boros['geometry'].convex_hull
|
|
BoroCode
|
|
1 POLYGON ((977855.4451904297 188082.3223876953,...
|
|
2 POLYGON ((1017949.977600098 225426.8845825195,...
|
|
3 POLYGON ((988872.8212280273 146772.0317993164,...
|
|
4 POLYGON ((1000721.531799316 136681.776184082, ...
|
|
5 POLYGON ((915517.6877458114 120121.8812543372,...
|
|
dtype: geometry
|
|
|
|
.. image:: ../../_static/nyc_hull.png
|
|
|
|
To demonstrate a more complex operation, we'll generate a
|
|
:class:`~geopandas.GeoSeries` containing 2000 random points:
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> import numpy as np
|
|
>>> from shapely.geometry import Point
|
|
>>> xmin, xmax, ymin, ymax = 900000, 1080000, 120000, 280000
|
|
>>> xc = (xmax - xmin) * np.random.random(2000) + xmin
|
|
>>> yc = (ymax - ymin) * np.random.random(2000) + ymin
|
|
>>> pts = GeoSeries([Point(x, y) for x, y in zip(xc, yc)])
|
|
|
|
Now draw a circle with fixed radius around each point:
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> circles = pts.buffer(2000)
|
|
|
|
We can collapse these circles into a single :class:`MultiPolygon`
|
|
geometry with
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> mp = circles.unary_union
|
|
|
|
To extract the part of this geometry contained in each borough, we can
|
|
just use:
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> holes = boros['geometry'].intersection(mp)
|
|
|
|
.. image:: ../../_static/holes.png
|
|
|
|
and to get the area outside of the holes:
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> boros_with_holes = boros['geometry'].difference(mp)
|
|
|
|
.. image:: ../../_static/boros_with_holes.png
|
|
|
|
Note that this can be simplified a bit, since ``geometry`` is
|
|
available as an attribute on a :class:`~geopandas.GeoDataFrame`, and the
|
|
:meth:`~geopandas.GeoSeries.intersection` and :meth:`~geopandas.GeoSeries.difference` methods are implemented with the
|
|
"&" and "-" operators, respectively. For example, the latter could
|
|
have been expressed simply as ``boros.geometry - mp``.
|
|
|
|
It's easy to do things like calculate the fractional area in each
|
|
borough that are in the holes:
|
|
|
|
.. sourcecode:: python
|
|
|
|
>>> holes.area / boros.geometry.area
|
|
BoroCode
|
|
1 0.579939
|
|
2 0.586833
|
|
3 0.608174
|
|
4 0.582172
|
|
5 0.558075
|
|
dtype: float64
|
|
|
|
.. _matplotlib: http://matplotlib.org
|
|
.. _fiona: http://fiona.readthedocs.io/en/latest/
|
|
.. _geopy: https://github.com/geopy/geopy
|
|
.. _geo_interface: https://gist.github.com/sgillies/2217756
|
|
.. _borough boundaries of New York City: https://data.cityofnewyork.us/City-Government/Borough-Boundaries/tqmj-j8zm
|
|
|
|
.. toctree::
|
|
:maxdepth: 2
|