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https://github.com/wassname/geopandas.git
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89 lines
3.4 KiB
Markdown
89 lines
3.4 KiB
Markdown
Introduction
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------------
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GeoPandas is a project to add support for geographic data to
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[pandas](http://pandas.pydata.org) objects. It currently implements
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`GeoSeries` and `GeoDataFrame` types which is are subclasses of `pandas.Series`
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and `pandas.DataFrame` respectively. GeoPandas objects can act on
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[shapely](http://toblerity.github.io/shapely) geometry objects and perform geometric
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operations.
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Examples
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--------
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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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Some geographic operations return normal pandas object. Calling the `area()` method of a `GeoSeries` will generate a `pandas.Series` containing the area of each item in the `GeoSeries`:
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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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>>> 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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GeoPandas objects also know how to plot themselves. GeoPandas uses [descartes](https://pypi.python.org/pypi/descartes) to generate a [matplotlib](http://matplotlib.org) plot. To generate a plot of our GeoSeries, use:
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>>> g.plot()
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GeoPandas also implements a alternate constructors that can read any data format recognized by [fiona](http://toblerity.github.io/fiona). To read a [file containing the boroughs of New York City](http://www.nyc.gov/html/dcp/download/bytes/nybb_13a.zip):
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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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>>> 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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TODO
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----
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- Not all Shapely operations are yet exposed to a GeoSeries
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- The current GeoDataFrame does not do very much.
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- spatial joins, grouping and more...
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