forked from geopandas/geopandas
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geodataframe.py
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geodataframe.py
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try:
from collections import OrderedDict
except ImportError:
# Python 2.6
from ordereddict import OrderedDict
import json
import os
import sys
import numpy as np
from pandas import DataFrame, Series, Index
from shapely.geometry import mapping, shape
from shapely.geometry.base import BaseGeometry
from six import string_types
from geopandas import GeoSeries
from geopandas.base import GeoPandasBase
from geopandas.plotting import plot_dataframe
import geopandas.io
DEFAULT_GEO_COLUMN_NAME = 'geometry'
PY3 = sys.version_info[0] == 3
class GeoDataFrame(GeoPandasBase, DataFrame):
"""
A GeoDataFrame object is a pandas.DataFrame that has a column
with geometry. In addition to the standard DataFrame constructor arguments,
GeoDataFrame also accepts the following keyword arguments:
Keyword Arguments
-----------------
crs : str (optional)
Coordinate system
geometry : str or array (optional)
If str, column to use as geometry. If array, will be set as 'geometry'
column on GeoDataFrame.
"""
# XXX: This will no longer be necessary in pandas 0.17
_internal_names = ['_data', '_cacher', '_item_cache', '_cache',
'is_copy', '_subtyp', '_index',
'_default_kind', '_default_fill_value', '_metadata',
'__array_struct__', '__array_interface__']
_metadata = ['crs', '_geometry_column_name']
_geometry_column_name = DEFAULT_GEO_COLUMN_NAME
def __init__(self, *args, **kwargs):
crs = kwargs.pop('crs', None)
geometry = kwargs.pop('geometry', None)
super(GeoDataFrame, self).__init__(*args, **kwargs)
self.crs = crs
if geometry is not None:
self.set_geometry(geometry, inplace=True)
self._invalidate_sindex()
# Serialize metadata (will no longer be necessary in pandas 0.17+)
# See https://github.com/pydata/pandas/pull/10557
def __getstate__(self):
meta = dict((k, getattr(self, k, None)) for k in self._metadata)
return dict(_data=self._data, _typ=self._typ,
_metadata=self._metadata, **meta)
def __setattr__(self, attr, val):
# have to special case geometry b/c pandas tries to use as column...
if attr == 'geometry':
object.__setattr__(self, attr, val)
else:
super(GeoDataFrame, self).__setattr__(attr, val)
def _get_geometry(self):
if self._geometry_column_name not in self:
raise AttributeError("No geometry data set yet (expected in"
" column '%s'." % self._geometry_column_name)
return self[self._geometry_column_name]
def _set_geometry(self, col):
# TODO: Use pandas' core.common.is_list_like() here.
if not isinstance(col, (list, np.ndarray, Series)):
raise ValueError("Must use a list-like to set the geometry"
" property")
self.set_geometry(col, inplace=True)
geometry = property(fget=_get_geometry, fset=_set_geometry,
doc="Geometry data for GeoDataFrame")
def set_geometry(self, col, drop=False, inplace=False, crs=None):
"""
Set the GeoDataFrame geometry using either an existing column or
the specified input. By default yields a new object.
The original geometry column is replaced with the input.
Parameters
----------
keys : column label or array
drop : boolean, default True
Delete column to be used as the new geometry
inplace : boolean, default False
Modify the GeoDataFrame in place (do not create a new object)
crs : str/result of fion.get_crs (optional)
Coordinate system to use. If passed, overrides both DataFrame and
col's crs. Otherwise, tries to get crs from passed col values or
DataFrame.
Examples
--------
>>> df1 = df.set_geometry([Point(0,0), Point(1,1), Point(2,2)])
>>> df2 = df.set_geometry('geom1')
Returns
-------
geodataframe : GeoDataFrame
"""
# Most of the code here is taken from DataFrame.set_index()
if inplace:
frame = self
else:
frame = self.copy()
if not crs:
crs = getattr(col, 'crs', self.crs)
to_remove = None
geo_column_name = self._geometry_column_name
if isinstance(col, (Series, list, np.ndarray)):
level = col
elif hasattr(col, 'ndim') and col.ndim != 1:
raise ValueError("Must pass array with one dimension only.")
else:
try:
level = frame[col].values
except KeyError:
raise ValueError("Unknown column %s" % col)
except:
raise
if drop:
to_remove = col
geo_column_name = self._geometry_column_name
else:
geo_column_name = col
if to_remove:
del frame[to_remove]
if isinstance(level, GeoSeries) and level.crs != crs:
# Avoids caching issues/crs sharing issues
level = level.copy()
level.crs = crs
# Check that we are using a listlike of geometries
if not all(isinstance(item, BaseGeometry) or not item for item in level):
raise TypeError("Input geometry column must contain valid geometry objects.")
frame[geo_column_name] = level
frame._geometry_column_name = geo_column_name
frame.crs = crs
frame._invalidate_sindex()
if not inplace:
return frame
@classmethod
def from_file(cls, filename, **kwargs):
"""
Alternate constructor to create a GeoDataFrame from a file.
Example:
df = geopandas.GeoDataFrame.from_file('nybb.shp')
Wraps geopandas.read_file(). For additional help, see read_file()
"""
return geopandas.io.file.read_file(filename, **kwargs)
@classmethod
def from_features(cls, features, crs=None):
"""
Alternate constructor to create GeoDataFrame from an iterable of
features. Each element must be a feature dictionary or implement
the __geo_interface__.
See: https://gist.github.com/sgillies/2217756
"""
rows = []
for f in features:
if hasattr(f, "__geo_interface__"):
f = f.__geo_interface__
else:
f = f
d = {'geometry': shape(f['geometry']) if f['geometry'] else None}
d.update(f['properties'])
rows.append(d)
df = GeoDataFrame.from_dict(rows)
df.crs = crs
return df
@classmethod
def from_postgis(cls, sql, con, geom_col='geom', crs=None, index_col=None,
coerce_float=True, params=None):
"""
Alternate constructor to create a GeoDataFrame from a sql query
containing a geometry column.
Example:
df = geopandas.GeoDataFrame.from_postgis(con,
"SELECT geom, highway FROM roads;")
Wraps geopandas.read_postgis(). For additional help, see read_postgis()
"""
return geopandas.io.sql.read_postgis(sql, con, geom_col, crs, index_col,
coerce_float, params)
def to_json(self, na='null', show_bbox=False, **kwargs):
"""
Returns a GeoJSON string representation of the GeoDataFrame.
Parameters
----------
na : {'null', 'drop', 'keep'}, default 'null'
Indicates how to output missing (NaN) values in the GeoDataFrame
* null: output the missing entries as JSON null
* drop: remove the property from the feature. This applies to
each feature individually so that features may have
different properties
* keep: output the missing entries as NaN
show_bbox : include bbox (bounds) in the geojson
The remaining *kwargs* are passed to json.dumps().
"""
return json.dumps(self._to_geo(na=na, show_bbox=show_bbox), **kwargs)
@property
def __geo_interface__(self):
"""
Returns a python feature collection (i.e. the geointerface)
representation of the GeoDataFrame.
This differs from `_to_geo()` only in that it is a property with
default args instead of a method
"""
return self._to_geo(na='null', show_bbox=True)
def iterfeatures(self, na='null', show_bbox=False):
"""
Returns an iterator that yields feature dictionaries that comply with
__geo_interface__
Parameters
----------
na : {'null', 'drop', 'keep'}, default 'null'
Indicates how to output missing (NaN) values in the GeoDataFrame
* null: ouput the missing entries as JSON null
* drop: remove the property from the feature. This applies to
each feature individually so that features may have
different properties
* keep: output the missing entries as NaN
show_bbox : include bbox (bounds) in the geojson. default False
"""
def fill_none(row):
"""
Takes in a Series, converts to a dictionary with null values
set to None
"""
na_keys = row.index[row.isnull()]
d = row.to_dict()
for k in na_keys:
d[k] = None
return d
# na_methods must take in a Series and return dict
na_methods = {'null': fill_none,
'drop': lambda row: row.dropna().to_dict(),
'keep': lambda row: row.to_dict()}
if na not in na_methods:
raise ValueError('Unknown na method {0}'.format(na))
f = na_methods[na]
for i, row in self.iterrows():
properties = f(row)
del properties[self._geometry_column_name]
feature = {
'id': str(i),
'type': 'Feature',
'properties': properties,
'geometry': mapping(row[self._geometry_column_name])
if row[self._geometry_column_name] else None
}
if show_bbox:
feature['bbox'] = row.geometry.bounds
yield feature
def _to_geo(self, **kwargs):
"""
Returns a python feature collection (i.e. the geointerface)
representation of the GeoDataFrame.
"""
geo = {'type': 'FeatureCollection',
'features': list(self.iterfeatures(**kwargs))}
if kwargs.get('show_bbox', False):
geo['bbox'] = self.total_bounds
return geo
def to_file(self, filename, driver="ESRI Shapefile", schema=None,
**kwargs):
"""
Write this GeoDataFrame to an OGR data source
A dictionary of supported OGR providers is available via:
>>> import fiona
>>> fiona.supported_drivers
Parameters
----------
filename : string
File path or file handle to write to.
driver : string, default 'ESRI Shapefile'
The OGR format driver used to write the vector file.
schema : dict, default None
If specified, the schema dictionary is passed to Fiona to
better control how the file is written.
The *kwargs* are passed to fiona.open and can be used to write
to multi-layer data, store data within archives (zip files), etc.
"""
from geopandas.io.file import to_file
to_file(self, filename, driver, schema, **kwargs)
def to_crs(self, crs=None, epsg=None, inplace=False):
"""Transform geometries to a new coordinate reference system
This method will transform all points in all objects. It has
no notion or projecting entire geometries. All segments
joining points are assumed to be lines in the current
projection, not geodesics. Objects crossing the dateline (or
other projection boundary) will have undesirable behavior.
`to_crs` passes the `crs` argument to the `Proj` function from the
`pyproj` library (with the option `preserve_units=True`). It can
therefore accept proj4 projections in any format
supported by `Proj`, including dictionaries, or proj4 strings.
"""
if inplace:
df = self
else:
df = self.copy()
geom = df.geometry.to_crs(crs=crs, epsg=epsg)
df.geometry = geom
df.crs = geom.crs
if not inplace:
return df
def __getitem__(self, key):
"""
If the result is a column containing only 'geometry', return a
GeoSeries. If it's a DataFrame with a 'geometry' column, return a
GeoDataFrame.
"""
result = super(GeoDataFrame, self).__getitem__(key)
geo_col = self._geometry_column_name
if isinstance(key, string_types) and key == geo_col:
result.__class__ = GeoSeries
result.crs = self.crs
result._invalidate_sindex()
elif isinstance(result, DataFrame) and geo_col in result:
result.__class__ = GeoDataFrame
result.crs = self.crs
result._geometry_column_name = geo_col
result._invalidate_sindex()
elif isinstance(result, DataFrame) and geo_col not in result:
result.__class__ = DataFrame
return result
#
# Implement pandas methods
#
def merge(self, *args, **kwargs):
result = DataFrame.merge(self, *args, **kwargs)
geo_col = self._geometry_column_name
if isinstance(result, DataFrame) and geo_col in result:
result.__class__ = GeoDataFrame
result.crs = self.crs
result._geometry_column_name = geo_col
result._invalidate_sindex()
elif isinstance(result, DataFrame) and geo_col not in result:
result.__class__ = DataFrame
return result
@property
def _constructor(self):
return GeoDataFrame
def __finalize__(self, other, method=None, **kwargs):
"""propagate metadata from other to self """
# merge operation: using metadata of the left object
if method == 'merge':
for name in self._metadata:
object.__setattr__(self, name, getattr(other.left, name, None))
# concat operation: using metadata of the first object
elif method == 'concat':
for name in self._metadata:
object.__setattr__(self, name, getattr(other.objs[0], name, None))
else:
for name in self._metadata:
object.__setattr__(self, name, getattr(other, name, None))
return self
def copy(self, deep=True):
"""
Make a copy of this GeoDataFrame object
Parameters
----------
deep : boolean, default True
Make a deep copy, i.e. also copy data
Returns
-------
copy : GeoDataFrame
"""
# FIXME: this will likely be unnecessary in pandas >= 0.13
data = self._data
if deep:
data = data.copy()
return GeoDataFrame(data).__finalize__(self)
def plot(self, *args, **kwargs):
return plot_dataframe(self, *args, **kwargs)
plot.__doc__ = plot_dataframe.__doc__
def dissolve(self, by=None, aggfunc='first', as_index=True):
"""
Dissolve geometries within `groupby` into single observation.
This is accomplished by applying the `unary_union` method
to all geometries within a groupself.
Observations associated with each `groupby` group will be aggregated
using the `aggfunc`.
Parameters
----------
by : string, default None
Column whose values define groups to be dissolved
aggfunc : function or string, default "first"
Aggregation function for manipulation of data associated
with each group. Passed to pandas `groupby.agg` method.
as_index : boolean, default True
If true, groupby columns become index of result.
Returns
-------
GeoDataFrame
"""
# Process non-spatial component
data = self.drop(labels=self.geometry.name, axis=1)
aggregated_data = data.groupby(by=by).agg(aggfunc)
# Process spatial component
def merge_geometries(block):
merged_geom = block.unary_union
return merged_geom
g = self.groupby(by=by, group_keys=False)[self.geometry.name].agg(merge_geometries)
# Aggregate
aggregated_geometry = GeoDataFrame(g, geometry=self.geometry.name)
# Recombine
aggregated = aggregated_geometry.join(aggregated_data)
# Reset if requested
if not as_index:
aggregated = aggregated.reset_index()
return aggregated
def _dataframe_set_geometry(self, col, drop=False, inplace=False, crs=None):
if inplace:
raise ValueError("Can't do inplace setting when converting from"
" DataFrame to GeoDataFrame")
gf = GeoDataFrame(self)
# this will copy so that BlockManager gets copied
return gf.set_geometry(col, drop=drop, inplace=False, crs=crs)
if PY3:
DataFrame.set_geometry = _dataframe_set_geometry
else:
import types
DataFrame.set_geometry = types.MethodType(_dataframe_set_geometry, None,
DataFrame)