Skip to content
Python tools for geographic data
Python HTML
Branch: master
Clone or download
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
benchmarks ENH: Add affine_transform method to GeoSeries (#1008) Jun 13, 2019
ci/travis CI: pin python to 3.7.3 (pip install issues with 3.7.4) (#1092) Aug 12, 2019
doc ENH: pass legend_kwds to colorbar when relevant (#1102) Aug 18, 2019
examples DOC: fix plotting in 'pandas to geopandas' example (#1108) Aug 19, 2019
geopandas ENH: pass legend_kwds to colorbar when relevant (#1102) Aug 18, 2019
.coveragerc TST: clean requirements.txt, add pysal on travis, omit _versions.py f… Aug 25, 2017
.gitattributes MNT/BLD: use versioneer May 31, 2016
.gitignore ENH: write GeoDataFrame with mixed geometry types (#870) Apr 17, 2019
.travis.yml CI: disable 27-latest-defaults (#1103) Aug 16, 2019
CHANGELOG.md Add initial changelog for 0.6.0 (#1099) Aug 13, 2019
CONTRIBUTING.md Contributing file updates python 2.7 instead of 2.6 + a few other syn… Nov 8, 2018
LICENSE.txt Update copyright date Jun 10, 2016
MANIFEST.in Ensure to package license file (#795) Aug 14, 2018
README.md DOC: refresh with Python 3 syntax, and modern outputs (#1065) Jul 21, 2019
appveyor.yml CI: re-enable conda 4.7 (#1029) Jul 6, 2019
asv.conf.json Start adding an asv benchmark suite (#497) Aug 20, 2017
constraints.txt Create constraints.txt: rtree Dec 3, 2015
readthedocs.yml DOC/BLD: readthedocs version 2 config file (#934) Mar 6, 2019
requirements.test.txt TST: fix to_csv test on Windows (#904) Jan 26, 2019
requirements.txt BUG/COMPAT: fix fillna by filling with Polygon instead of Point (#512) Aug 28, 2017
setup.cfg TST: pytest configuration (#1021) Jun 23, 2019
setup.py Update minimal dependencies for pandas (>=0.23.4) and matplotlib (>=2… May 24, 2019
versioneer.py MNT/BLD: use versioneer May 31, 2016

README.md

GeoPandas build status Coverage Status Join the chat at https://gitter.im/geopandas/geopandas Binder DOI

Python tools for geographic data

Introduction

GeoPandas is a project to add support for geographic data to pandas objects. It currently implements GeoSeries and GeoDataFrame types which are subclasses of pandas.Series and pandas.DataFrame respectively. GeoPandas objects can act on shapely geometry objects and perform geometric operations.

GeoPandas geometry operations are cartesian. The coordinate reference system (crs) can be stored as an attribute on an object, and is automatically set when loading from a file. Objects may be transformed to new coordinate systems with the to_crs() method. There is currently no enforcement of like coordinates for operations, but that may change in the future.

Documentation is available at geopandas.org (current release) and Read the Docs (release and development versions).

Install

See the installation docs for all details. GeoPandas depends on the following packages:

  • pandas
  • shapely
  • fiona
  • pyproj

Further, descartes and matplotlib are optional dependencies, required for plotting, and rtree is an optional dependency, required for spatial joins. rtree requires the C library libspatialindex.

Those packages depend on several low-level libraries for geospatial analysis, which can be a challenge to install. Therefore, we recommend to install GeoPandas using the conda package manager. See the installation docs for more details.

Get in touch

  • Ask usage questions ("How do I?") on StackOverflow or GIS StackExchange.
  • Report bugs, suggest features or view the source code on GitHub.
  • For a quick question about a bug report or feature request, or Pull Request, head over to the gitter channel.
  • For less well defined questions or ideas, or to announce other projects of interest to GeoPandas users, ... use the mailing list.

Examples

>>> import geopandas
>>> 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 = geopandas.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

Example 1

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:

>>> print(g.area)
0    0.5
1    1.0
2    1.0
dtype: float64

Other operations return GeoPandas objects:

>>> 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

Example 2

GeoPandas objects also know how to plot themselves. GeoPandas uses descartes to generate a matplotlib plot. To generate a plot of our GeoSeries, use:

>>> 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 boroughs boundaries of New York City (GeoPandas includes this as an example dataset):

>>> 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...  

New York City boroughs

>>> 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

Convex hulls of New York City boroughs

You can’t perform that action at this time.