from __future__ import annotations import typing import warnings from packaging.version import Version from typing import Any, Callable, Dict, Optional import numpy as np import pandas as pd from pandas import Series from pandas.core.internals import SingleBlockManager import shapely from shapely.geometry import GeometryCollection from shapely.geometry.base import BaseGeometry import geopandas from geopandas.base import GeoPandasBase, _delegate_property from geopandas.explore import _explore_geoseries from geopandas.plotting import plot_series from . import _compat as compat from ._decorator import doc from .array import ( GeometryDtype, from_shapely, from_wkb, from_wkt, points_from_xy, to_wkb, to_wkt, ) from .base import is_geometry_type if typing.TYPE_CHECKING: import os def _geoseries_constructor_with_fallback( data=None, index=None, crs: Optional[Any] = None, **kwargs ): """ A flexible constructor for GeoSeries._constructor, which needs to be able to fall back to a Series (if a certain operation does not produce geometries) """ try: return GeoSeries(data=data, index=index, crs=crs, **kwargs) except TypeError: return Series(data=data, index=index, **kwargs) def _expanddim_logic(df): """Shared logic for _constructor_expanddim and _constructor_from_mgr_expanddim.""" from geopandas import GeoDataFrame if (df.dtypes == "geometry").sum() > 0: if df.shape[1] == 1: geo_col_name = df.columns[0] else: geo_col_name = None if geo_col_name is None or not is_geometry_type(df[geo_col_name]): df = GeoDataFrame(df) df._geometry_column_name = None else: df = df.set_geometry(geo_col_name) return df def _geoseries_expanddim(data=None, *args, **kwargs): # pd.Series._constructor_expanddim == pd.DataFrame, we start # with that then specialize. df = pd.DataFrame(data, *args, **kwargs) return _expanddim_logic(df) 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 : value (optional) Coordinate Reference System of the geometry objects. Can be anything accepted by :meth:`pyproj.CRS.from_user_input() `, such as an authority string (eg "EPSG:4326") or a WKT string. 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: geometry >>> s = geopandas.GeoSeries( ... [Point(1, 1), Point(2, 2), Point(3, 3)], crs="EPSG:3857" ... ) >>> s.crs # doctest: +SKIP Name: WGS 84 / Pseudo-Mercator Axis Info [cartesian]: - X[east]: Easting (metre) - Y[north]: Northing (metre) Area of Use: - name: World - 85°S to 85°N - bounds: (-180.0, -85.06, 180.0, 85.06) Coordinate Operation: - name: Popular Visualisation Pseudo-Mercator - method: Popular Visualisation Pseudo Mercator Datum: World Geodetic System 1984 - Ellipsoid: WGS 84 - Prime Meridian: Greenwich >>> s = geopandas.GeoSeries( ... [Point(1, 1), Point(2, 2), Point(3, 3)], index=["a", "b", "c"], crs=4326 ... ) >>> s a POINT (1 1) b POINT (2 2) c POINT (3 3) dtype: geometry >>> s.crs Name: WGS 84 Axis Info [ellipsoidal]: - Lat[north]: Geodetic latitude (degree) - Lon[east]: Geodetic longitude (degree) Area of Use: - name: World. - bounds: (-180.0, -90.0, 180.0, 90.0) Datum: World Geodetic System 1984 ensemble - Ellipsoid: WGS 84 - Prime Meridian: Greenwich See Also -------- GeoDataFrame pandas.Series """ def __init__(self, data=None, index=None, crs: Optional[Any] = None, **kwargs): if ( hasattr(data, "crs") or (isinstance(data, pd.Series) and hasattr(data.array, "crs")) ) and crs: data_crs = data.crs if hasattr(data, "crs") else data.array.crs if not data_crs: # make a copy to avoid setting CRS to passed GeometryArray data = data.copy() else: if not data.crs == crs: raise ValueError( "CRS mismatch between CRS of the passed geometries " "and 'crs'. Use 'GeoSeries.set_crs(crs, " "allow_override=True)' to overwrite CRS or " "'GeoSeries.to_crs(crs)' to reproject geometries. " ) if isinstance(data, SingleBlockManager): if not isinstance(data.blocks[0].dtype, GeometryDtype): raise TypeError( "Non geometry data passed to GeoSeries constructor, " f"received data of dtype '{data.blocks[0].dtype}'" ) 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 with warnings.catch_warnings(): # suppress additional warning from pandas for empty data # (will always give object dtype instead of float dtype in the future, # making the `if s.empty: s = s.astype(object)` below unnecessary) empty_msg = "The default dtype for empty Series" warnings.filterwarnings("ignore", empty_msg, DeprecationWarning) warnings.filterwarnings("ignore", empty_msg, FutureWarning) s = pd.Series(data, index=index, name=name, **kwargs) # prevent trying to convert non-geometry objects if s.dtype != object: if (s.empty and s.dtype == "float64") or data is None: # pd.Series with empty data gives float64 for older pandas versions s = s.astype(object) else: raise TypeError( "Non geometry data passed to GeoSeries constructor, " f"received data of dtype '{s.dtype}'" ) # extract object-dtype numpy array from pandas Series; with CoW this # gives a read-only array, so we try to set the flag back to writeable data = s.to_numpy() try: data.flags.writeable = True except ValueError: pass # try to convert to GeometryArray try: data = from_shapely(data, crs) except TypeError: raise TypeError( "Non geometry data passed to GeoSeries constructor, " f"received data of dtype '{s.dtype}'" ) index = s.index name = s.name super().__init__(data, index=index, name=name, **kwargs) if not self.crs: self.crs = crs def append(self, *args, **kwargs) -> GeoSeries: return self._wrapped_pandas_method("append", *args, **kwargs) @GeoPandasBase.crs.setter def crs(self, value): if self.crs is not None: warnings.warn( "Overriding the CRS of a GeoSeries that already has CRS. " "This unsafe behavior will be deprecated in future versions. " "Use GeoSeries.set_crs method instead.", stacklevel=2, category=DeprecationWarning, ) self.geometry.values.crs = value @property def geometry(self) -> GeoSeries: return self @property def x(self) -> Series: """Return the x location of point geometries in a GeoSeries Returns ------- pandas.Series Examples -------- >>> from shapely.geometry import Point >>> s = geopandas.GeoSeries([Point(1, 1), Point(2, 2), Point(3, 3)]) >>> s.x 0 1.0 1 2.0 2 3.0 dtype: float64 See Also -------- GeoSeries.y GeoSeries.z """ return _delegate_property("x", self) @property def y(self) -> Series: """Return the y location of point geometries in a GeoSeries Returns ------- pandas.Series Examples -------- >>> from shapely.geometry import Point >>> s = geopandas.GeoSeries([Point(1, 1), Point(2, 2), Point(3, 3)]) >>> s.y 0 1.0 1 2.0 2 3.0 dtype: float64 See Also -------- GeoSeries.x GeoSeries.z """ return _delegate_property("y", self) @property def z(self) -> Series: """Return the z location of point geometries in a GeoSeries Returns ------- pandas.Series Examples -------- >>> from shapely.geometry import Point >>> s = geopandas.GeoSeries([Point(1, 1, 1), Point(2, 2, 2), Point(3, 3, 3)]) >>> s.z 0 1.0 1 2.0 2 3.0 dtype: float64 See Also -------- GeoSeries.x GeoSeries.y """ return _delegate_property("z", self) @classmethod def from_file(cls, filename: os.PathLike | typing.IO, **kwargs) -> GeoSeries: """Alternate constructor to create a ``GeoSeries`` from a file. Can load a ``GeoSeries`` from a file from any format recognized by `pyogrio`. See http://pyogrio.readthedocs.io/ for details. From a file with attributes loads only geometry column. Note that to do that, GeoPandas first loads the whole GeoDataFrame. Parameters ---------- filename : str File path or file handle to read from. Depending on which kwargs are included, the content of filename may vary. See :func:`pyogrio.read_dataframe` for usage details. kwargs : key-word arguments These arguments are passed to :func:`pyogrio.read_dataframe`, and can be used to access multi-layer data, data stored within archives (zip files), etc. Examples -------- >>> import geodatasets >>> path = geodatasets.get_path('nybb') >>> s = geopandas.GeoSeries.from_file(path) >>> s 0 MULTIPOLYGON (((970217.022 145643.332, 970227.... 1 MULTIPOLYGON (((1029606.077 156073.814, 102957... 2 MULTIPOLYGON (((1021176.479 151374.797, 102100... 3 MULTIPOLYGON (((981219.056 188655.316, 980940.... 4 MULTIPOLYGON (((1012821.806 229228.265, 101278... Name: geometry, dtype: geometry See Also -------- read_file : read file to GeoDataFrame """ from geopandas import GeoDataFrame df = GeoDataFrame.from_file(filename, **kwargs) return GeoSeries(df.geometry, crs=df.crs) @classmethod def from_wkb( cls, data, index=None, crs: Optional[Any] = None, on_invalid="raise", **kwargs ) -> GeoSeries: """ Alternate constructor to create a ``GeoSeries`` from a list or array of WKB objects Parameters ---------- data : array-like or Series Series, list or array of WKB objects index : array-like or Index The index for the GeoSeries. crs : value, optional Coordinate Reference System of the geometry objects. Can be anything accepted by :meth:`pyproj.CRS.from_user_input() `, such as an authority string (eg "EPSG:4326") or a WKT string. on_invalid: {"raise", "warn", "ignore"}, default "raise" - raise: an exception will be raised if a WKB input geometry is invalid. - warn: a warning will be raised and invalid WKB geometries will be returned as None. - ignore: invalid WKB geometries will be returned as None without a warning. kwargs Additional arguments passed to the Series constructor, e.g. ``name``. Returns ------- GeoSeries See Also -------- GeoSeries.from_wkt """ return cls._from_wkb_or_wkt( from_wkb, data, index=index, crs=crs, on_invalid=on_invalid, **kwargs ) @classmethod def from_wkt( cls, data, index=None, crs: Optional[Any] = None, on_invalid="raise", **kwargs ) -> GeoSeries: """ Alternate constructor to create a ``GeoSeries`` from a list or array of WKT objects Parameters ---------- data : array-like, Series Series, list, or array of WKT objects index : array-like or Index The index for the GeoSeries. crs : value, optional Coordinate Reference System of the geometry objects. Can be anything accepted by :meth:`pyproj.CRS.from_user_input() `, such as an authority string (eg "EPSG:4326") or a WKT string. on_invalid : {"raise", "warn", "ignore"}, default "raise" - raise: an exception will be raised if a WKT input geometry is invalid. - warn: a warning will be raised and invalid WKT geometries will be returned as ``None``. - ignore: invalid WKT geometries will be returned as ``None`` without a warning. kwargs Additional arguments passed to the Series constructor, e.g. ``name``. Returns ------- GeoSeries See Also -------- GeoSeries.from_wkb Examples -------- >>> wkts = [ ... 'POINT (1 1)', ... 'POINT (2 2)', ... 'POINT (3 3)', ... ] >>> s = geopandas.GeoSeries.from_wkt(wkts) >>> s 0 POINT (1 1) 1 POINT (2 2) 2 POINT (3 3) dtype: geometry """ return cls._from_wkb_or_wkt( from_wkt, data, index=index, crs=crs, on_invalid=on_invalid, **kwargs ) @classmethod def from_xy(cls, x, y, z=None, index=None, crs=None, **kwargs) -> GeoSeries: """ Alternate constructor to create a :class:`~geopandas.GeoSeries` of Point geometries from lists or arrays of x, y(, z) coordinates In case of geographic coordinates, it is assumed that longitude is captured by ``x`` coordinates and latitude by ``y``. Parameters ---------- x, y, z : iterable index : array-like or Index, optional The index for the GeoSeries. If not given and all coordinate inputs are Series with an equal index, that index is used. crs : value, optional Coordinate Reference System of the geometry objects. Can be anything accepted by :meth:`pyproj.CRS.from_user_input() `, such as an authority string (eg "EPSG:4326") or a WKT string. **kwargs Additional arguments passed to the Series constructor, e.g. ``name``. Returns ------- GeoSeries See Also -------- GeoSeries.from_wkt points_from_xy Examples -------- >>> x = [2.5, 5, -3.0] >>> y = [0.5, 1, 1.5] >>> s = geopandas.GeoSeries.from_xy(x, y, crs="EPSG:4326") >>> s 0 POINT (2.5 0.5) 1 POINT (5 1) 2 POINT (-3 1.5) dtype: geometry """ if index is None: if ( isinstance(x, Series) and isinstance(y, Series) and x.index.equals(y.index) and (z is None or (isinstance(z, Series) and x.index.equals(z.index))) ): # check if we can reuse index index = x.index return cls(points_from_xy(x, y, z, crs=crs), index=index, crs=crs, **kwargs) @classmethod def _from_wkb_or_wkt( cls, from_wkb_or_wkt_function: Callable, data, index=None, crs: Optional[Any] = None, on_invalid: str = "raise", **kwargs, ) -> GeoSeries: """Create a GeoSeries from either WKT or WKB values""" if isinstance(data, Series): if index is not None: data = data.reindex(index) else: index = data.index data = data.values return cls( from_wkb_or_wkt_function(data, crs=crs, on_invalid=on_invalid), index=index, **kwargs, ) @classmethod def from_arrow(cls, arr, **kwargs) -> GeoSeries: """ Construct a GeoSeries from a Arrow array object with a GeoArrow extension type. See https://geoarrow.org/ for details on the GeoArrow specification. This functions accepts any Arrow array object implementing the `Arrow PyCapsule Protocol`_ (i.e. having an ``__arrow_c_array__`` method). .. _Arrow PyCapsule Protocol: https://arrow.apache.org/docs/format/CDataInterface/PyCapsuleInterface.html .. versionadded:: 1.0 Parameters ---------- arr : pyarrow.Array, Arrow array Any array object implementing the Arrow PyCapsule Protocol (i.e. has an ``__arrow_c_array__`` or ``__arrow_c_stream__`` method). The type of the array should be one of the geoarrow geometry types. **kwargs Other parameters passed to the GeoSeries constructor. Returns ------- GeoSeries """ from geopandas.io._geoarrow import arrow_to_geometry_array return cls(arrow_to_geometry_array(arr), **kwargs) @property def __geo_interface__(self) -> Dict: """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). Examples -------- >>> from shapely.geometry import Point >>> s = geopandas.GeoSeries([Point(1, 1), Point(2, 2), Point(3, 3)]) >>> s.__geo_interface__ {'type': 'FeatureCollection', 'features': [{'id': '0', 'type': 'Feature', \ 'properties': {}, 'geometry': {'type': 'Point', 'coordinates': (1.0, 1.0)}, \ 'bbox': (1.0, 1.0, 1.0, 1.0)}, {'id': '1', 'type': 'Feature', \ 'properties': {}, 'geometry': {'type': 'Point', 'coordinates': (2.0, 2.0)}, \ 'bbox': (2.0, 2.0, 2.0, 2.0)}, {'id': '2', 'type': 'Feature', 'properties': \ {}, 'geometry': {'type': 'Point', 'coordinates': (3.0, 3.0)}, 'bbox': (3.0, \ 3.0, 3.0, 3.0)}], 'bbox': (1.0, 1.0, 3.0, 3.0)} """ from geopandas import GeoDataFrame return GeoDataFrame({"geometry": self}).__geo_interface__ def to_file( self, filename: os.PathLike | typing.IO, driver: Optional[str] = None, index: Optional[bool] = None, **kwargs, ): """Write the ``GeoSeries`` to a file. By default, an ESRI shapefile is written, but any OGR data source supported by Pyogrio or Fiona can be written. Parameters ---------- filename : string File path or file handle to write to. The path may specify a GDAL VSI scheme. driver : string, default None The OGR format driver used to write the vector file. If not specified, it attempts to infer it from the file extension. If no extension is specified, it saves ESRI Shapefile to a folder. index : bool, default None If True, write index into one or more columns (for MultiIndex). Default None writes the index into one or more columns only if the index is named, is a MultiIndex, or has a non-integer data type. If False, no index is written. .. versionadded:: 0.7 Previously the index was not written. mode : string, default 'w' The write mode, 'w' to overwrite the existing file and 'a' to append. Not all drivers support appending. The drivers that support appending are listed in fiona.supported_drivers or https://github.com/Toblerity/Fiona/blob/master/fiona/drvsupport.py crs : pyproj.CRS, default None If specified, the CRS is passed to Fiona to better control how the file is written. If None, GeoPandas will determine the crs based on crs df attribute. The value can be anything accepted by :meth:`pyproj.CRS.from_user_input() `, such as an authority string (eg "EPSG:4326") or a WKT string. The keyword is not supported for the "pyogrio" engine. engine : str, "pyogrio" or "fiona" The underlying library that is used to write the file. Currently, the supported options are "pyogrio" and "fiona". Defaults to "pyogrio" if installed, otherwise tries "fiona". **kwargs : Keyword args to be passed to the engine, and can be used to write to multi-layer data, store data within archives (zip files), etc. In case of the "pyogrio" engine, the keyword arguments are passed to `pyogrio.write_dataframe`. In case of the "fiona" engine, the keyword arguments are passed to fiona.open`. For more information on possible keywords, type: ``import pyogrio; help(pyogrio.write_dataframe)``. See Also -------- GeoDataFrame.to_file : write GeoDataFrame to file read_file : read file to GeoDataFrame Examples -------- >>> s.to_file('series.shp') # doctest: +SKIP >>> s.to_file('series.gpkg', driver='GPKG', layer='name1') # doctest: +SKIP >>> s.to_file('series.geojson', driver='GeoJSON') # doctest: +SKIP """ from geopandas import GeoDataFrame data = GeoDataFrame({"geometry": self}, index=self.index) data.to_file(filename, driver, index=index, **kwargs) # # Implement pandas methods # @property def _constructor(self): return _geoseries_constructor_with_fallback def _constructor_from_mgr(self, mgr, axes): assert isinstance(mgr, SingleBlockManager) if not isinstance(mgr.blocks[0].dtype, GeometryDtype): return Series._from_mgr(mgr, axes) return GeoSeries._from_mgr(mgr, axes) @property def _constructor_expanddim(self): return _geoseries_expanddim def _constructor_expanddim_from_mgr(self, mgr, axes): df = pd.DataFrame._from_mgr(mgr, axes) return _expanddim_logic(df) def _wrapped_pandas_method(self, mtd, *args, **kwargs): """Wrap a generic pandas method to ensure it returns a GeoSeries""" val = getattr(super(), mtd)(*args, **kwargs) if type(val) == Series: val.__class__ = GeoSeries val.crs = self.crs return val def __getitem__(self, key): return self._wrapped_pandas_method("__getitem__", key) @doc(pd.Series) def sort_index(self, *args, **kwargs): return self._wrapped_pandas_method("sort_index", *args, **kwargs) @doc(pd.Series) def take(self, *args, **kwargs): return self._wrapped_pandas_method("take", *args, **kwargs) @doc(pd.Series) def select(self, *args, **kwargs): return self._wrapped_pandas_method("select", *args, **kwargs) @doc(pd.Series) def apply(self, func, convert_dtype: Optional[bool] = None, args=(), **kwargs): if convert_dtype is not None: kwargs["convert_dtype"] = convert_dtype else: # if compat.PANDAS_GE_21 don't pass through, use pandas default # of true to avoid internally triggering the pandas warning if not compat.PANDAS_GE_21: kwargs["convert_dtype"] = True # to avoid warning result = super().apply(func, args=args, **kwargs) if isinstance(result, GeoSeries): if self.crs is not None: result.set_crs(self.crs, inplace=True) return result def isna(self) -> Series: """ Detect missing values. Historically, NA values in a GeoSeries could be represented by empty geometric objects, in addition to standard representations such as None and np.nan. This behaviour is changed in version 0.6.0, and now only actual missing values return True. To detect empty geometries, use ``GeoSeries.is_empty`` instead. Returns ------- A boolean pandas Series of the same size as the GeoSeries, True where a value is NA. Examples -------- >>> from shapely.geometry import Polygon >>> s = geopandas.GeoSeries( ... [Polygon([(0, 0), (1, 1), (0, 1)]), None, Polygon([])] ... ) >>> s 0 POLYGON ((0 0, 1 1, 0 1, 0 0)) 1 None 2 POLYGON EMPTY dtype: geometry >>> s.isna() 0 False 1 True 2 False dtype: bool See Also -------- GeoSeries.notna : inverse of isna GeoSeries.is_empty : detect empty geometries """ return super().isna() def isnull(self) -> Series: """Alias for `isna` method. See `isna` for more detail.""" return self.isna() def notna(self) -> Series: """ Detect non-missing values. Historically, NA values in a GeoSeries could be represented by empty geometric objects, in addition to standard representations such as None and np.nan. This behaviour is changed in version 0.6.0, and now only actual missing values return False. To detect empty geometries, use ``~GeoSeries.is_empty`` instead. Returns ------- A boolean pandas Series of the same size as the GeoSeries, False where a value is NA. Examples -------- >>> from shapely.geometry import Polygon >>> s = geopandas.GeoSeries( ... [Polygon([(0, 0), (1, 1), (0, 1)]), None, Polygon([])] ... ) >>> s 0 POLYGON ((0 0, 1 1, 0 1, 0 0)) 1 None 2 POLYGON EMPTY dtype: geometry >>> s.notna() 0 True 1 False 2 True dtype: bool See Also -------- GeoSeries.isna : inverse of notna GeoSeries.is_empty : detect empty geometries """ if self.is_empty.any(): warnings.warn( "GeoSeries.notna() previously returned False for both missing (None) " "and empty geometries. Now, it only returns False for missing values. " "Since the calling GeoSeries contains empty geometries, the result " "has changed compared to previous versions of GeoPandas.\n" "Given a GeoSeries 's', you can use '~s.is_empty & s.notna()' to get " "back the old behaviour.\n\n" "To further ignore this warning, you can do: \n" "import warnings; warnings.filterwarnings('ignore', " "'GeoSeries.notna', UserWarning)", UserWarning, stacklevel=2, ) return super().notna() def notnull(self) -> Series: """Alias for `notna` method. See `notna` for more detail.""" return self.notna() def fillna(self, value=None, inplace: bool = False, limit=None, **kwargs): """ Fill NA values with geometry (or geometries). Parameters ---------- value : shapely geometry or GeoSeries, default None If None is passed, NA values will be filled with GEOMETRYCOLLECTION EMPTY. If a shapely geometry object is passed, it will be used to fill all missing values. If a ``GeoSeries`` or ``GeometryArray`` are passed, missing values will be filled based on the corresponding index locations. If pd.NA or np.nan are passed, values will be filled with ``None`` (not GEOMETRYCOLLECTION EMPTY). limit : int, default None This is the maximum number of entries along the entire axis where NaNs will be filled. Must be greater than 0 if not None. Returns ------- GeoSeries Examples -------- >>> from shapely.geometry import Polygon >>> s = geopandas.GeoSeries( ... [ ... Polygon([(0, 0), (1, 1), (0, 1)]), ... None, ... Polygon([(0, 0), (-1, 1), (0, -1)]), ... ] ... ) >>> s 0 POLYGON ((0 0, 1 1, 0 1, 0 0)) 1 None 2 POLYGON ((0 0, -1 1, 0 -1, 0 0)) dtype: geometry Filled with an empty polygon. >>> s.fillna() 0 POLYGON ((0 0, 1 1, 0 1, 0 0)) 1 GEOMETRYCOLLECTION EMPTY 2 POLYGON ((0 0, -1 1, 0 -1, 0 0)) dtype: geometry Filled with a specific polygon. >>> s.fillna(Polygon([(0, 1), (2, 1), (1, 2)])) 0 POLYGON ((0 0, 1 1, 0 1, 0 0)) 1 POLYGON ((0 1, 2 1, 1 2, 0 1)) 2 POLYGON ((0 0, -1 1, 0 -1, 0 0)) dtype: geometry Filled with another GeoSeries. >>> from shapely.geometry import Point >>> s_fill = geopandas.GeoSeries( ... [ ... Point(0, 0), ... Point(1, 1), ... Point(2, 2), ... ] ... ) >>> s.fillna(s_fill) 0 POLYGON ((0 0, 1 1, 0 1, 0 0)) 1 POINT (1 1) 2 POLYGON ((0 0, -1 1, 0 -1, 0 0)) dtype: geometry See Also -------- GeoSeries.isna : detect missing values """ if value is None: value = GeometryCollection() return super().fillna(value=value, limit=limit, inplace=inplace, **kwargs) def __contains__(self, other) -> bool: """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 @doc(plot_series) def plot(self, *args, **kwargs): return plot_series(self, *args, **kwargs) @doc(_explore_geoseries) def explore(self, *args, **kwargs): """Interactive map based on folium/leaflet.js""" return _explore_geoseries(self, *args, **kwargs) def explode(self, ignore_index=False, index_parts=False) -> GeoSeries: """ Explode multi-part geometries into multiple single geometries. Single rows can become multiple rows. This is analogous to PostGIS's ST_Dump(). The 'path' index is the second level of the returned MultiIndex Parameters ---------- ignore_index : bool, default False If True, the resulting index will be labelled 0, 1, …, n - 1, ignoring `index_parts`. index_parts : boolean, default False If True, the resulting index will be a multi-index (original index with an additional level indicating the multiple geometries: a new zero-based index for each single part geometry per multi-part geometry). Returns ------- A GeoSeries with a MultiIndex. The levels of the MultiIndex are the original index and a zero-based integer index that counts the number of single geometries within a multi-part geometry. Examples -------- >>> from shapely.geometry import MultiPoint >>> s = geopandas.GeoSeries( ... [MultiPoint([(0, 0), (1, 1)]), MultiPoint([(2, 2), (3, 3), (4, 4)])] ... ) >>> s 0 MULTIPOINT ((0 0), (1 1)) 1 MULTIPOINT ((2 2), (3 3), (4 4)) dtype: geometry >>> s.explode(index_parts=True) 0 0 POINT (0 0) 1 POINT (1 1) 1 0 POINT (2 2) 1 POINT (3 3) 2 POINT (4 4) dtype: geometry See also -------- GeoDataFrame.explode """ from .base import _get_index_for_parts geometries, outer_idx = shapely.get_parts(self.values._data, return_index=True) index = _get_index_for_parts( self.index, outer_idx, ignore_index=ignore_index, index_parts=index_parts, ) return GeoSeries(geometries, index=index, crs=self.crs).__finalize__(self) # # Additional methods # @compat.requires_pyproj def set_crs( self, crs: Optional[Any] = None, epsg: Optional[int] = None, inplace: bool = False, allow_override: bool = False, ): """ Set the Coordinate Reference System (CRS) of a ``GeoSeries``. Pass ``None`` to remove CRS from the ``GeoSeries``. Notes ----- The underlying geometries are not transformed to this CRS. To transform the geometries to a new CRS, use the ``to_crs`` method. Parameters ---------- crs : pyproj.CRS | None, optional The value can be anything accepted by :meth:`pyproj.CRS.from_user_input() `, such as an authority string (eg "EPSG:4326") or a WKT string. epsg : int, optional if `crs` is specified EPSG code specifying the projection. inplace : bool, default False If True, the CRS of the GeoSeries will be changed in place (while still returning the result) instead of making a copy of the GeoSeries. allow_override : bool, default False If the the GeoSeries already has a CRS, allow to replace the existing CRS, even when both are not equal. Returns ------- GeoSeries 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: geometry Setting CRS to a GeoSeries without one: >>> s.crs is None True >>> s = s.set_crs('epsg:3857') >>> s.crs # doctest: +SKIP Name: WGS 84 / Pseudo-Mercator Axis Info [cartesian]: - X[east]: Easting (metre) - Y[north]: Northing (metre) Area of Use: - name: World - 85°S to 85°N - bounds: (-180.0, -85.06, 180.0, 85.06) Coordinate Operation: - name: Popular Visualisation Pseudo-Mercator - method: Popular Visualisation Pseudo Mercator Datum: World Geodetic System 1984 - Ellipsoid: WGS 84 - Prime Meridian: Greenwich Overriding existing CRS: >>> s = s.set_crs(4326, allow_override=True) Without ``allow_override=True``, ``set_crs`` returns an error if you try to override CRS. See Also -------- GeoSeries.to_crs : re-project to another CRS """ from pyproj import CRS if crs is not None: crs = CRS.from_user_input(crs) elif epsg is not None: crs = CRS.from_epsg(epsg) if not allow_override and self.crs is not None and not self.crs == crs: raise ValueError( "The GeoSeries already has a CRS which is not equal to the passed " "CRS. Specify 'allow_override=True' to allow replacing the existing " "CRS without doing any transformation. If you actually want to " "transform the geometries, use 'GeoSeries.to_crs' instead." ) if not inplace: result = self.copy() else: result = self result.array.crs = crs return result def to_crs( self, crs: Optional[Any] = None, epsg: Optional[int] = None ) -> GeoSeries: """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`` or ``epsg`` may be specified for output. This method will transform all points in all objects. It has no notion of 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 : pyproj.CRS, optional if `epsg` is specified The value can be anything accepted by :meth:`pyproj.CRS.from_user_input() `, such as an authority string (eg "EPSG:4326") or a WKT string. epsg : int, optional if `crs` is specified EPSG code specifying output projection. Returns ------- GeoSeries Examples -------- >>> from shapely.geometry import Point >>> s = geopandas.GeoSeries([Point(1, 1), Point(2, 2), Point(3, 3)], crs=4326) >>> s 0 POINT (1 1) 1 POINT (2 2) 2 POINT (3 3) dtype: geometry >>> s.crs # doctest: +SKIP Name: WGS 84 Axis Info [ellipsoidal]: - Lat[north]: Geodetic latitude (degree) - Lon[east]: Geodetic longitude (degree) Area of Use: - name: World - bounds: (-180.0, -90.0, 180.0, 90.0) Datum: World Geodetic System 1984 - Ellipsoid: WGS 84 - Prime Meridian: Greenwich >>> s = s.to_crs(3857) >>> s 0 POINT (111319.491 111325.143) 1 POINT (222638.982 222684.209) 2 POINT (333958.472 334111.171) dtype: geometry >>> s.crs # doctest: +SKIP Name: WGS 84 / Pseudo-Mercator Axis Info [cartesian]: - X[east]: Easting (metre) - Y[north]: Northing (metre) Area of Use: - name: World - 85°S to 85°N - bounds: (-180.0, -85.06, 180.0, 85.06) Coordinate Operation: - name: Popular Visualisation Pseudo-Mercator - method: Popular Visualisation Pseudo Mercator Datum: World Geodetic System 1984 - Ellipsoid: WGS 84 - Prime Meridian: Greenwich See Also -------- GeoSeries.set_crs : assign CRS """ return GeoSeries( self.values.to_crs(crs=crs, epsg=epsg), index=self.index, name=self.name ) def estimate_utm_crs(self, datum_name: str = "WGS 84"): """Returns the estimated UTM CRS based on the bounds of the dataset. .. versionadded:: 0.9 Parameters ---------- datum_name : str, optional The name of the datum to use in the query. Default is WGS 84. Returns ------- pyproj.CRS Examples -------- >>> import geodatasets >>> df = geopandas.read_file( ... geodatasets.get_path("geoda.chicago_health") ... ) >>> df.geometry.estimate_utm_crs() # doctest: +SKIP Name: WGS 84 / UTM zone 16N Axis Info [cartesian]: - E[east]: Easting (metre) - N[north]: Northing (metre) Area of Use: - name: Between 90°W and 84°W, northern hemisphere between equator and 84°N, ... - bounds: (-90.0, 0.0, -84.0, 84.0) Coordinate Operation: - name: UTM zone 16N - method: Transverse Mercator Datum: World Geodetic System 1984 ensemble - Ellipsoid: WGS 84 - Prime Meridian: Greenwich """ return self.values.estimate_utm_crs(datum_name) def to_json( self, show_bbox: bool = True, drop_id: bool = False, to_wgs84: bool = False, **kwargs, ) -> str: """ Returns a GeoJSON string representation of the GeoSeries. Parameters ---------- show_bbox : bool, optional, default: True Include bbox (bounds) in the geojson drop_id : bool, default: False Whether to retain the index of the GeoSeries as the id property in the generated GeoJSON. Default is False, but may want True if the index is just arbitrary row numbers. to_wgs84: bool, optional, default: False If the CRS is set on the active geometry column it is exported as WGS84 (EPSG:4326) to meet the `2016 GeoJSON specification `_. Set to True to force re-projection and set to False to ignore CRS. False by default. *kwargs* that will be passed to json.dumps(). Returns ------- JSON string 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: geometry >>> s.to_json() '{"type": "FeatureCollection", "features": [{"id": "0", "type": "Feature", "pr\ operties": {}, "geometry": {"type": "Point", "coordinates": [1.0, 1.0]}, "bbox": [1.0,\ 1.0, 1.0, 1.0]}, {"id": "1", "type": "Feature", "properties": {}, "geometry": {"type"\ : "Point", "coordinates": [2.0, 2.0]}, "bbox": [2.0, 2.0, 2.0, 2.0]}, {"id": "2", "typ\ e": "Feature", "properties": {}, "geometry": {"type": "Point", "coordinates": [3.0, 3.\ 0]}, "bbox": [3.0, 3.0, 3.0, 3.0]}], "bbox": [1.0, 1.0, 3.0, 3.0]}' See Also -------- GeoSeries.to_file : write GeoSeries to file """ return self.to_frame("geometry").to_json( na="null", show_bbox=show_bbox, drop_id=drop_id, to_wgs84=to_wgs84, **kwargs ) def to_wkb(self, hex: bool = False, **kwargs) -> Series: """ Convert GeoSeries geometries to WKB Parameters ---------- hex : bool If true, export the WKB as a hexadecimal string. The default is to return a binary bytes object. kwargs Additional keyword args will be passed to :func:`shapely.to_wkb`. Returns ------- Series WKB representations of the geometries See also -------- GeoSeries.to_wkt """ return Series(to_wkb(self.array, hex=hex, **kwargs), index=self.index) def to_wkt(self, **kwargs) -> Series: """ Convert GeoSeries geometries to WKT Parameters ---------- kwargs Keyword args will be passed to :func:`shapely.to_wkt`. Returns ------- Series WKT representations of the geometries 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: geometry >>> s.to_wkt() 0 POINT (1 1) 1 POINT (2 2) 2 POINT (3 3) dtype: object See also -------- GeoSeries.to_wkb """ return Series(to_wkt(self.array, **kwargs), index=self.index) def to_arrow(self, geometry_encoding="WKB", interleaved=True, include_z=None): """Encode a GeoSeries to GeoArrow format. See https://geoarrow.org/ for details on the GeoArrow specification. This functions returns a generic Arrow array object implementing the `Arrow PyCapsule Protocol`_ (i.e. having an ``__arrow_c_array__`` method). This object can then be consumed by your Arrow implementation of choice that supports this protocol. .. _Arrow PyCapsule Protocol: https://arrow.apache.org/docs/format/CDataInterface/PyCapsuleInterface.html .. versionadded:: 1.0 Parameters ---------- geometry_encoding : {'WKB', 'geoarrow' }, default 'WKB' The GeoArrow encoding to use for the data conversion. interleaved : bool, default True Only relevant for 'geoarrow' encoding. If True, the geometries' coordinates are interleaved in a single fixed size list array. If False, the coordinates are stored as separate arrays in a struct type. include_z : bool, default None Only relevant for 'geoarrow' encoding (for WKB, the dimensionality of the individial geometries is preserved). If False, return 2D geometries. If True, include the third dimension in the output (if a geometry has no third dimension, the z-coordinates will be NaN). By default, will infer the dimensionality from the input geometries. Note that this inference can be unreliable with empty geometries (for a guaranteed result, it is recommended to specify the keyword). Returns ------- GeoArrowArray A generic Arrow array object with geometry data encoded to GeoArrow. Examples -------- >>> from shapely.geometry import Point >>> gser = geopandas.GeoSeries([Point(1, 2), Point(2, 1)]) >>> gser 0 POINT (1 2) 1 POINT (2 1) dtype: geometry >>> arrow_array = gser.to_arrow() >>> arrow_array The returned array object needs to be consumed by a library implementing the Arrow PyCapsule Protocol. For example, wrapping the data as a pyarrow.Array (requires pyarrow >= 14.0): >>> import pyarrow as pa >>> array = pa.array(arrow_array) >>> array [ 0101000000000000000000F03F0000000000000040, 01010000000000000000000040000000000000F03F ] """ import pyarrow as pa from geopandas.io._geoarrow import ( GeoArrowArray, construct_geometry_array, construct_wkb_array, ) field_name = self.name if self.name is not None else "" if geometry_encoding.lower() == "geoarrow": if Version(pa.__version__) < Version("10.0.0"): raise ValueError("Converting to 'geoarrow' requires pyarrow >= 10.0.") field, geom_arr = construct_geometry_array( np.array(self.array), include_z=include_z, field_name=field_name, crs=self.crs, interleaved=interleaved, ) elif geometry_encoding.lower() == "wkb": field, geom_arr = construct_wkb_array( np.asarray(self.array), field_name=field_name, crs=self.crs ) else: raise ValueError( "Expected geometry encoding 'WKB' or 'geoarrow' " f"got {geometry_encoding}" ) return GeoArrowArray(field, geom_arr) def clip(self, mask, keep_geom_type: bool = False, sort=False) -> GeoSeries: """Clip points, lines, or polygon geometries to the mask extent. Both layers must be in the same Coordinate Reference System (CRS). The GeoSeries will be clipped to the full extent of the `mask` object. If there are multiple polygons in mask, data from the GeoSeries will be clipped to the total boundary of all polygons in mask. Parameters ---------- mask : GeoDataFrame, GeoSeries, (Multi)Polygon, list-like Polygon vector layer used to clip `gdf`. The mask's geometry is dissolved into one geometric feature and intersected with GeoSeries. If the mask is list-like with four elements ``(minx, miny, maxx, maxy)``, ``clip`` will use a faster rectangle clipping (:meth:`~GeoSeries.clip_by_rect`), possibly leading to slightly different results. keep_geom_type : boolean, default False If True, return only geometries of original type in case of intersection resulting in multiple geometry types or GeometryCollections. If False, return all resulting geometries (potentially mixed-types). sort : boolean, default False If True, the order of rows in the clipped GeoSeries will be preserved at small performance cost. If False the order of rows in the clipped GeoSeries will be random. Returns ------- GeoSeries Vector data (points, lines, polygons) from `gdf` clipped to polygon boundary from mask. See also -------- clip : top-level function for clip Examples -------- Clip points (grocery stores) with polygons (the Near West Side community): >>> import geodatasets >>> chicago = geopandas.read_file( ... geodatasets.get_path("geoda.chicago_health") ... ) >>> near_west_side = chicago[chicago["community"] == "NEAR WEST SIDE"] >>> groceries = geopandas.read_file( ... geodatasets.get_path("geoda.groceries") ... ).to_crs(chicago.crs) >>> groceries.shape (148, 8) >>> nws_groceries = groceries.geometry.clip(near_west_side) >>> nws_groceries.shape (7,) """ return geopandas.clip(self, mask=mask, keep_geom_type=keep_geom_type, sort=sort)