Python tools for geographic data
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README.md

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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

Requirements

For the installation of GeoPandas, the following packages are required:

  • pandas
  • shapely
  • fiona
  • descartes
  • pyproj

Further, rtree is an optional dependency. rtree requires the C library libspatialindex. If using brew, you can install using brew install Spatialindex.

Install

Then, installation works as normal: pip install geopandas

Examples

>>> 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 ((0.0000000000000000 0.000000000000000...
1    POLYGON ((0.0000000000000000 0.000000000000000...
2    POLYGON ((2.0000000000000000 0.000000000000000...
dtype: object

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)
Out[15]:
0    POLYGON ((-0.3535533905932737 0.35355339059327...
1    POLYGON ((-0.5000000000000000 0.00000000000000...
2    POLYGON ((1.5000000000000000 0.000000000000000...
dtype: object

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 file containing the boroughs of New York City:

>>> boros = GeoDataFrame.from_file('nybb.shp')
>>> boros.set_index('BoroCode', inplace=True)
>>> boros.sort()
>>> boros
               BoroName    Shape_Area     Shape_Leng  \
BoroCode
1             Manhattan  6.364422e+08  358532.956418
2                 Bronx  1.186804e+09  464517.890553
3              Brooklyn  1.959432e+09  726568.946340
4                Queens  3.049947e+09  861038.479299
5         Staten Island  1.623853e+09  330385.036974

                                                   geometry
BoroCode
1         (POLYGON ((981219.0557861328125000 188655.3157...
2         (POLYGON ((1012821.8057861328125000 229228.264...
3         (POLYGON ((1021176.4790039062500000 151374.796...
4         (POLYGON ((1029606.0765991210937500 156073.814...
5         (POLYGON ((970217.0223999023437500 145643.3322...

New York City boroughs

>>> boros['geometry'].convex_hull
0    POLYGON ((915517.6877458114176989 120121.88125...
1    POLYGON ((1000721.5317993164062500 136681.7761...
2    POLYGON ((988872.8212280273437500 146772.03179...
3    POLYGON ((977855.4451904296875000 188082.32238...
4    POLYGON ((1017949.9776000976562500 225426.8845...
dtype: object

Convex hulls of New York City boroughs