Tree @upstream/0.7.0 (Download .tar.gz)
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 | GeoPandas [![build status](https://secure.travis-ci.org/geopandas/geopandas.png?branch=master)](https://travis-ci.org/geopandas/geopandas) [![Coverage Status](https://codecov.io/gh/geopandas/geopandas/branch/master/graph/badge.svg)](https://codecov.io/gh/geopandas/geopandas) [![Join the chat at https://gitter.im/geopandas/geopandas](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/geopandas/geopandas?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/geopandas/geopandas/master) [![DOI](https://zenodo.org/badge/11002815.svg)](https://zenodo.org/badge/latestdoi/11002815) ========= Python tools for geographic data Introduction ------------ GeoPandas is a project to add support for geographic data to [pandas](http://pandas.pydata.org) objects. It currently implements `GeoSeries` and `GeoDataFrame` types which are subclasses of `pandas.Series` and `pandas.DataFrame` respectively. GeoPandas objects can act on [shapely](http://shapely.readthedocs.io/en/latest/) 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](http://geopandas.org) (current release) and [Read the Docs](http://geopandas.readthedocs.io/en/latest/) (release and development versions). Install -------- See the [installation docs](https://geopandas.readthedocs.io/en/latest/install.html) 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``](https://github.com/Toblerity/rtree) is an optional dependency, required for spatial joins. ``rtree`` requires the C library [``libspatialindex``](https://github.com/libspatialindex/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](https://conda.io/en/latest/). See the [installation docs](https://geopandas.readthedocs.io/en/latest/install.html) for more details. Get in touch ------------ - Ask usage questions ("How do I?") on [StackOverflow](https://stackoverflow.com/questions/tagged/geopandas) or [GIS StackExchange](https://gis.stackexchange.com/questions/tagged/geopandas). - Report bugs, suggest features or view the source code [on GitHub](https://github.com/geopandas/geopandas). - For a quick question about a bug report or feature request, or Pull Request, head over to the [gitter channel](https://gitter.im/geopandas/geopandas). - For less well defined questions or ideas, or to announce other projects of interest to GeoPandas users, ... use the [mailing list](https://groups.google.com/forum/#!forum/geopandas). 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](examples/test.png) 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](examples/test_buffer.png) 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: >>> g.plot() GeoPandas also implements alternate constructors that can read any data format recognized by [fiona](http://fiona.readthedocs.io/en/latest/). To read a zip file containing an ESRI shapefile with the [boroughs boundaries of New York City](https://data.cityofnewyork.us/City-Government/Borough-Boundaries/tqmj-j8zm) (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](examples/nyc.png) >>> 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](examples/nyc_hull.png) |
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