text: from distutils.version import LooseVersion
  from functools import partial
  import json
  
  import numpy as np
  import pandas as pd
  from pandas import Series
  from pandas.core.internals import SingleBlockManager
  
  import pyproj
  from shapely.geometry import shape, Point
  from shapely.geometry.base import BaseGeometry
  from shapely.ops import transform
  
  from geopandas.plotting import plot_series
  from geopandas.base import (
      GeoPandasBase, _delegate_property, _CoordinateIndexer)
  
  from .array import GeometryArray, GeometryDtype, from_shapely
  from .base import is_geometry_type
  from ._compat import PANDAS_GE_024
  
  
  _PYPROJ2 = LooseVersion(pyproj.__version__) >= LooseVersion('2.1.0')
  
  
  def _is_empty(x):
      try:
          return x.is_empty
      except:
          return False
  
  
  class GeoSeries(GeoPandasBase, Series):
      """
      A Series object designed to store shapely geometry objects.
  
      Parameters
      ----------
      data : array-like, dict, scalar value
          The geometries to store in the GeoSeries.
      index : array-like or Index
          The index for the GeoSeries.
      crs : str, dict (optional)
          Coordinate Reference System of the geometry objects.
      kwargs
          Additional arguments passed to the Series constructor,
           e.g. ``name``.
  
      Examples
      --------
  
      >>> from shapely.geometry import Point
      >>> s = geopandas.GeoSeries([Point(1, 1), Point(2, 2), Point(3, 3)])
      >>> s
      0    POINT (1 1)
      1    POINT (2 2)
      2    POINT (3 3)
      dtype: object
  
      See Also
      --------
      GeoDataFrame
      pandas.Series
  
      """
      _metadata = ['name', 'crs']
  
      def __new__(cls, data=None, index=None, crs=None, **kwargs):
          # we need to use __new__ because we want to return Series instance
          # instead of GeoSeries instance in case of non-geometry data
          if isinstance(data, SingleBlockManager):
              if isinstance(data.blocks[0].dtype, GeometryDtype):
                  if not PANDAS_GE_024 and (data.blocks[0].ndim == 2):
                      # bug in pandas 0.23 where in certain indexing operations
                      # (such as .loc) a 2D ExtensionBlock (still with 1D values
                      # is created) which results in other failures
                      from pandas.core.internals import ExtensionBlock
                      values = data.blocks[0].values
                      block = ExtensionBlock(values, slice(0, len(values), 1))
                      data = SingleBlockManager(
                          [block], data.axes[0], fastpath=True)
                  self = super(GeoSeries, cls).__new__(cls)
                  super(GeoSeries, self).__init__(data, index=index, **kwargs)
                  self.crs = crs
                  return self
              return Series(data, index=index, **kwargs)
  
          if isinstance(data, BaseGeometry):
              # fix problem for scalar geometries passed, ensure the list of
              # scalars is of correct length if index is specified
              n = len(index) if index is not None else 1
              data = [data] * n
  
          name = kwargs.pop('name', None)
  
          if not is_geometry_type(data):
              # if data is None and dtype is specified (eg from empty overlay
              # test), specifying dtype raises an error:
              # https://github.com/pandas-dev/pandas/issues/26469
              kwargs.pop('dtype', None)
              # Use Series constructor to handle input data
              s = pd.Series(data, index=index, name=name, **kwargs)
              # prevent trying to convert non-geometry objects
              if s.dtype != object:
                  if s.empty:
                      s = s.astype(object)
                  else:
                      return s
              # try to convert to GeometryArray, if fails return plain Series
              try:
                  data = from_shapely(s.values)
              except TypeError:
                  return s
              index = s.index
              name = s.name
  
          self = super(GeoSeries, cls).__new__(cls)
          super(GeoSeries, self).__init__(data, index=index, name=name, **kwargs)
          self.crs = crs
          self._invalidate_sindex()
          return self
  
      def __init__(self, *args, **kwargs):
          # need to overwrite Series init to prevent calling it for GeoSeries
          # (doesn't know crs, all work is already done above)
          pass
  
      def append(self, *args, **kwargs):
          return self._wrapped_pandas_method('append', *args, **kwargs)
  
      @property
      def geometry(self):
          return self
  
      @property
      def x(self):
          """Return the x location of point geometries in a GeoSeries"""
          return _delegate_property('x', self)
  
      @property
      def y(self):
          """Return the y location of point geometries in a GeoSeries"""
          return _delegate_property('y', self)
  
      @classmethod
      def from_file(cls, filename, **kwargs):
          """Alternate constructor to create a ``GeoSeries`` from a file.
  
          Can load a ``GeoSeries`` from a file from any format recognized by
          `fiona`. See http://fiona.readthedocs.io/en/latest/manual.html for details.
  
          Parameters
          ----------
          filename : str
              File path or file handle to read from. Depending on which kwargs
              are included, the content of filename may vary. See
              http://fiona.readthedocs.io/en/latest/README.html#usage for usage details.
          kwargs : key-word arguments
              These arguments are passed to fiona.open, and can be used to
              access multi-layer data, data stored within archives (zip files),
              etc.
          """
  
          from geopandas import GeoDataFrame
          df = GeoDataFrame.from_file(filename, **kwargs)
  
          return GeoSeries(df.geometry, crs=df.crs)
  
      @property
      def __geo_interface__(self):
          """Returns a ``GeoSeries`` as a python feature collection.
  
          Implements the `geo_interface`. The returned python data structure
          represents the ``GeoSeries`` as a GeoJSON-like ``FeatureCollection``.
          Note that the features will have an empty ``properties`` dict as they
          don't have associated attributes (geometry only).
          """
          from geopandas import GeoDataFrame
          return GeoDataFrame({'geometry': self}).__geo_interface__
  
      def to_file(self, filename, driver="ESRI Shapefile", **kwargs):
          from geopandas import GeoDataFrame
          data = GeoDataFrame({"geometry": self,
                               "id": self.index.values},
                              index=self.index)
          data.crs = self.crs
          data.to_file(filename, driver, **kwargs)
  
      #
      # Implement pandas methods
      #
  
      @property
      def _constructor(self):
          return GeoSeries
  
      def _wrapped_pandas_method(self, mtd, *args, **kwargs):
          """Wrap a generic pandas method to ensure it returns a GeoSeries"""
          val = getattr(super(GeoSeries, self), mtd)(*args, **kwargs)
          if type(val) == Series:
              val.__class__ = GeoSeries
              val.crs = self.crs
              val._invalidate_sindex()
          return val
  
      def __getitem__(self, key):
          return self._wrapped_pandas_method('__getitem__', key)
  
      def sort_index(self, *args, **kwargs):
          return self._wrapped_pandas_method('sort_index', *args, **kwargs)
  
      def take(self, *args, **kwargs):
          return self._wrapped_pandas_method('take', *args, **kwargs)
  
      def select(self, *args, **kwargs):
          return self._wrapped_pandas_method('select', *args, **kwargs)
  
      @property
      def _can_hold_na(self):
          return False
  
      def __finalize__(self, other, method=None, **kwargs):
          """ propagate metadata from other to self """
          # NOTE: backported from pandas master (upcoming v0.13)
          for name in self._metadata:
              object.__setattr__(self, name, getattr(other, name, None))
          return self
  
      def copy(self, order='C'):
          """
          Make a copy of this GeoSeries object
  
          Parameters
          ----------
          deep : boolean, default True
              Make a deep copy, i.e. also copy data
  
          Returns
          -------
          copy : GeoSeries
          """
          # FIXME: this will likely be unnecessary in pandas >= 0.13
          return GeoSeries(self.values.copy(order), index=self.index,
                        name=self.name).__finalize__(self)
  
      def isna(self):
          """
          N/A values in a GeoSeries can be represented by empty geometric
          objects, in addition to standard representations such as None and
          np.nan.
  
          Returns
          -------
          A boolean pandas Series of the same size as the GeoSeries,
          True where a value is N/A.
  
          See Also
          --------
          GeoSereies.notna : inverse of isna
          """
          non_geo_null = super(GeoSeries, self).isnull()
          val = self.apply(_is_empty)
          return Series(np.logical_or(non_geo_null, val))
  
      def isnull(self):
          """Alias for `isna` method. See `isna` for more detail."""
          return self.isna()
  
      def notna(self):
          """
          N/A values in a GeoSeries can be represented by empty geometric
          objects, in addition to standard representations such as None and
          np.nan.
  
          Returns
          -------
          A boolean pandas Series of the same size as the GeoSeries,
          False where a value is N/A.
  
          See Also
          --------
          GeoSeries.isna : inverse of notna
          """
          return ~self.isna()
  
      def notnull(self):
          """Alias for `notna` method. See `notna` for more detail."""
          return self.notna()
  
      def fillna(self, value=None, method=None, inplace=False,
                 **kwargs):
          """Fill NA/NaN values with a geometry (empty polygon by default).
  
          "method" is currently not implemented for pandas <= 0.12.
          """
          if value is None:
              value = BaseGeometry()
          return super(GeoSeries, self).fillna(value=value, method=method,
                                               inplace=inplace, **kwargs)
  
      def align(self, other, join='outer', level=None, copy=True,
                fill_value=None, **kwargs):
          if fill_value is None:
              fill_value = BaseGeometry()
          left, right = super(GeoSeries, self).align(other, join=join,
                                                     level=level, copy=copy,
                                                     fill_value=fill_value,
                                                     **kwargs)
          return left, right
  
      def __contains__(self, other):
          """Allow tests of the form "geom in s"
  
          Tests whether a GeoSeries contains a geometry.
  
          Note: This is not the same as the geometric method "contains".
          """
          if isinstance(other, BaseGeometry):
              return np.any(self.geom_equals(other))
          else:
              return False
  
      def plot(self, *args, **kwargs):
          """Generate a plot of the geometries in the ``GeoSeries``.
  
          Wraps the ``plot_series()`` function, and documentation is copied from
          there.
          """
          return plot_series(self, *args, **kwargs)
  
      plot.__doc__ = plot_series.__doc__
  
      #
      # Additional methods
      #
  
      def to_crs(self, crs=None, epsg=None):
          """Returns a ``GeoSeries`` with all geometries transformed to a new
          coordinate reference system.
  
          Transform all geometries in a GeoSeries to a different coordinate
          reference system.  The ``crs`` attribute on the current GeoSeries must
          be set.  Either ``crs`` in string or dictionary form or an EPSG code
          may be specified for output.
  
          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.
  
          Parameters
          ----------
          crs : dict or str
              Output projection parameters as string or in dictionary form.
          epsg : int
              EPSG code specifying output projection.
          """
          from fiona.crs import from_epsg
          if self.crs is None:
              raise ValueError('Cannot transform naive geometries.  '
                               'Please set a crs on the object first.')
          if crs is None:
              try:
                  crs = from_epsg(epsg)
              except TypeError:
                  raise TypeError('Must set either crs or epsg for output.')
          proj_in = pyproj.Proj(self.crs, preserve_units=True)
          proj_out = pyproj.Proj(crs, preserve_units=True)
          if _PYPROJ2:
              transformer = pyproj.Transformer.from_proj(proj_in, proj_out)
              project = transformer.transform
          else:
              project = partial(pyproj.transform, proj_in, proj_out)
          result = self.apply(lambda geom: transform(project, geom))
          result.__class__ = GeoSeries
          result.crs = crs
          result._invalidate_sindex()
          return result
  
      def to_json(self, **kwargs):
          """
          Returns a GeoJSON string representation of the GeoSeries.
  
          Parameters
          ----------
          *kwargs* that will be passed to json.dumps().
          """
          return json.dumps(self.__geo_interface__, **kwargs)
  
      #
      # Implement standard operators for GeoSeries
      #
  
      def __xor__(self, other):
          """Implement ^ operator as for builtin set type"""
          return self.symmetric_difference(other)
  
      def __or__(self, other):
          """Implement | operator as for builtin set type"""
          return self.union(other)
  
      def __and__(self, other):
          """Implement & operator as for builtin set type"""
          return self.intersection(other)
  
      def __sub__(self, other):
          """Implement - operator as for builtin set type"""
          return self.difference(other)
  
  
  GeoSeries._create_indexer('cx', _CoordinateIndexer)
  