GeoPandas [](https://travis-ci.org/geopandas/geopandas) [](https://codecov.io/gh/geopandas/geopandas) [](https://gitter.im/geopandas/geopandas?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [](https://mybinder.org/v2/gh/geopandas/geopandas/master)
=========
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://toblerity.github.io/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](http://geopandas.org)
(current release) and
[Read the Docs](http://geopandas.readthedocs.io/en/latest/)
(release and development versions).
Install
--------
**Requirements**
For the installation of GeoPandas, the following packages are required:
- ``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). If using brew, you can install using ``brew install Spatialindex``.
**Install**
GeoPandas depends on several low-level libraries for geospatial analysis. Depending on the system and package
manager that you use, this may cause dependency conflicts if you are not careful.
*Using `conda`*
We suggest that you use the [anaconda distribution](https://conda.io/docs/user-guide/install/download.html)
to install GeoPandas (``miniconda`` is fine as well).
Use ``conda`` and the ``conda-forge`` channel to install GeoPandas on a clean environment:
```bash
conda create -n geopandas
source activate geopandas # 'activate geopandas' on Windows
conda install -c conda-forge geopandas
```
**NOTE:** Creating a new environment is not strictly necessary, but installing other geospatial packages
from a *different* channel than ``conda-forge`` may cause dependency conflicts, so we recommend starting
fresh if possible. See the [conda-forge gotcha page](https://conda-forge.org/docs/conda-forge_gotchas.html)
for more information.
*Using `pip`*
GeoPandas is also pip-installable. If you choose to use `pip`, make sure that you have the proper non-python
libraries installed and linked properly.
```bash
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 = geopandas.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
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
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://toblerity.github.io/fiona). 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()
>>> 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...
>>> 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
