hLddlmZddlZddlZddlmZddlZddlZddlm Z ddl m Z ddl Z ddl mZddlmZddlZddlmZmZdd lmZdd lmZd d lmZd d lmZd dlmZm Z m!Z!m"Z"m#Z#m$Z$m%Z%d dl&m'Z'ejPr ddl)Z)ddl*m+Z+ d ddZ,dZ-ddZ.Gddee Z/y)) annotationsN)Any)Series)SingleBlockManager)GeometryCollection) BaseGeometry) GeoPandasBase_delegate_property_explore_geoseries plot_series)_compat)doc) GeometryDtype from_shapelyfrom_wkbfrom_wktpoints_from_xyto_wkbto_wkt)is_geometry_type)Callablec \ td|||d|S#t$rtd||d|cYSwxYw)zA flexible constructor for GeoSeries._constructor, which needs to be able to fall back to a Series (if a certain operation does not produce geometries). )dataindexcrs)rr) GeoSeries TypeErrorr)rrrkwargss F/var/www/html/immo/lib/python3.12/site-packages/geopandas/geoseries.py$_geoseries_constructor_with_fallbackr$'sB8Cd%SCFCC 874u7778s ++cddlm}|jdk(jdkDrV|jddk(r|j d}nd}|t ||s||}d|_|S|j|}|S)zLShared logic for _constructor_expanddim and _constructor_from_mgr_expanddim.r GeoDataFramegeometryrN) geopandasr'dtypessumshapecolumnsr_geometry_column_name set_geometry)dfr' geo_col_names r#_expanddim_logicr24s& Z$$&* 88A;! ::a=LL  '7<8H'Ib!B'+B $ I.B IcJtj|g|i|}t|SN)pd DataFramer2)rargsr"r0s r#_geoseries_expanddimr9Gs' d ,T ,V ,B B r3cbeZdZdZd+d,fd Zej jdZed-dZ ed.dZ ed.dZ ed.dZ ed.dZ ed/d Ze d0 d1d Ze d0 d1d Zed+d-d Ze d0 d2d Zed-dZed3dZ d4 d5dZedZdZedZdZfdZdZeej>dZ eej>dZ!eej>d6d7fd Z"d.fd Z#d.dZ$d.fd Z%d.dZ&d8d9fd Z'd:dZ(ee)d Z*ee+d!Z,d;d-d"Z-e.j^ d< d=d#Z0d4d>d$Z1d?d@d%Z2 dA dBd&Z3dCdDd'Z4d.d(Z5dEd)Z6d;dFd*Z7xZ8S)Gr uV 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 c t|ds0t|tjrit|jdrS|rQt|dr |j n|jj }|s|j }n||k(s tdt|trMt|jdjts&td|jdjdt|tr| t|nd}|g|z}|jdd}t!|s&|jddt#j$5d }t#j&d |t(t#j&d |t*tj|f||d |} ddd jt,k7rL| j.r| jd k(s|| j1t,} ntd| jd| j3} d |j4_ t9||}| j:}| j<}t? ||f||d ||j s||_yy#1swYxYw#t$rYdwxYw#t$rtd| jdwxYw)NrzCRS 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. rzKNon geometry data passed to GeoSeries constructor, received data of dtype ''rnamedtypez"The default dtype for empty Seriesignorerr=float64T)!hasattr isinstancer6rarrayrcopy ValueErrorrblocksr>rr!rlenpoprwarningscatch_warningsfilterwarningsDeprecationWarning FutureWarningobjectemptyastypeto_numpyflags writeablerrr=super__init__) selfrrrr"data_crsnr= empty_msgs __class__s r#rVzGeoSeries.__init__s D% 4+ E0J#*4#7txxTZZ^^Hyy{3$L d. /dkk!n22MB//3{{1~/C/C.DAG dL )$/E QA6A:Dzz&$'% JJw %((* FA '')=OP'')]KIIdE%dEfE Fww& GG9 4(A#33477)1> ::>> 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 xr res r#rgz GeoSeries.xs0"#t,,r3ctd|S)aReturn 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 GeoSeries.m yrhres r#rjz GeoSeries.y2"#t,,r3ctd|S)aReturn 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 GeoSeries.m zrhres r#rmz GeoSeries.z/rkr3ctd|S)aReturn the m coordinate of point geometries in a GeoSeries. Requires Shapely >= 2.1. .. versionadded:: 1.1.0 Returns ------- pandas.Series Examples -------- >>> from shapely.geometry import Point >>> s = geopandas.GeoSeries.from_wkt( ... [ ... "POINT M (2 3 5)", ... "POINT M (1 2 3)", ... ] ... ) >>> s 0 POINT M (2 3 5) 1 POINT M (1 2 3) dtype: geometry >>> s.m 0 5.0 1 3.0 dtype: float64 See Also -------- GeoSeries.x GeoSeries.y GeoSeries.z mrhres r#roz GeoSeries.mJsL"#t,,r3c vddlm}|j|fi|}t|j|j S)aAlternate 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 rr&r)r)r' from_filer r(r)clsfilenamer"r'r0s r#rrzGeoSeries.from_filers4J + #\ # #H 7 7"&&11r3c :|jt|f|||d|S)a#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. - fix: an effort is made to fix invalid input geometries (e.g. close unclosed rings). If this is not possible, they are returned as ``None`` without a warning. Requires GEOS >= 3.11 and shapely >= 2.1. kwargs Additional arguments passed to the Series constructor, e.g. ``name``. Returns ------- GeoSeries See Also -------- GeoSeries.from_wkt Examples -------- >>> wkbs = [ ... ( ... b"\x01\x01\x00\x00\x00\x00\x00\x00\x00" ... b"\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?" ... ), ... ( ... b"\x01\x01\x00\x00\x00\x00\x00\x00\x00" ... b"\x00\x00\x00@\x00\x00\x00\x00\x00\x00\x00@" ... ), ... ( ... b"\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00" ... b"\x00\x08@\x00\x00\x00\x00\x00\x00\x08@" ... ), ... ] >>> s = geopandas.GeoSeries.from_wkb(wkbs) >>> s 0 POINT (1 1) 1 POINT (2 2) 2 POINT (3 3) dtype: geometry rr on_invalid)_from_wkb_or_wktrrsrrrrwr"s r#rzGeoSeries.from_wkbs3|$s## d "'SZ KQ  r3c :|jt|f|||d|S)aAlternate 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. - fix: an effort is made to fix invalid input geometries (e.g. close unclosed rings). If this is not possible, they are returned as ``None`` without a warning. Requires GEOS >= 3.11 and shapely >= 2.1. 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 rv)rxrrys r#rzGeoSeries.from_wkts3l$s## d "'SZ KQ  r3c H|t|trxt|trh|jj|jrC|5t|tr1|jj|jr |j}|t ||||f||d|S)aRAlternate 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 rqrr)rCrrequalsr)rsrgrjrmrrr"s r#from_xyzGeoSeries.from_xys~V =1f%q&)GGNN177+Y:a#8QWW^^AGG=T>!Qs3T5cTVTTr3c t|tr,||j|}n |j}|j}|||||fd|i|S)z1Create a GeoSeries from either WKT or WKB values.)rrwr)rCrreindexrrb)rsfrom_wkb_or_wkt_functionrrrrwr"s r#rxzGeoSeries._from_wkb_or_wktNs_ dF # ||E* ;;D $Tsz J    r3c ,ddlm}|||fi|S)a 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 r)arrow_to_geometry_array)geopandas.io._geoarrowr)rsarrr"rs r# from_arrowzGeoSeries.from_arrowes> C*3/:6::r3c6ddlm}|d|ijS)aReturns 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)} rr&r()r)r'__geo_interface__)rWr's r#rzGeoSeries.__geo_interface__s, +Z./AAAr3c hddlm}|d|i|j}|j||fd|i|y)a 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 rr&r(rrN)r)r'rto_file)rWrtdriverrr"r'rs r#rzGeoSeries.to_files7F +Z.djjA Xv=U=f=r3ctSr5)r$res r# _constructorzGeoSeries._constructors33r3ct|tsJt|jdjtst j ||Stj ||S)Nr)rCrrGr>rr _from_mgrr )rWmgraxess r#_constructor_from_mgrzGeoSeries._constructor_from_mgrsQ#1222#**Q---}=##C. .""3--r3ctSr5)r9res r#_constructor_expanddimz GeoSeries._constructor_expanddims##r3cXtjj||}t|Sr5)r6r7rr2)rWrrr0s r#_constructor_expanddim_from_mgrz)GeoSeries._constructor_expanddim_from_mgrs# \\ # #C .##r3ctt||i|}t|turt|_|j |_|S)z>Wrap a generic pandas method to ensure it returns a GeoSeries.)getattrrUtyperr r\r)rWmtdr8r"valr\s r#_wrapped_pandas_methodz GeoSeries._wrapped_pandas_methods@#gegs#T4V4 9 %CMhhCG r3c&|jd|S)N __getitem__r)rWkeys r#rzGeoSeries.__getitem__ s**=#>>r3c.|jdg|i|S)N sort_indexrrWr8r"s r#rzGeoSeries.sort_index s*t**<I$I&IIr3c.|jdg|i|S)Ntakerrs r#rzGeoSeries.takes*t**6CDCFCCr3c |||d<ntjsd|d<t| |fd|i|}t |t r)|j |j|j d|S)N convert_dtypeTr8)inplace)compat PANDAS_GE_21rUapplyrCr rset_crs)rWfuncrr8r"resultr\s r#rzGeoSeries.applyso  $&3F? #&&*.'t9$9&9 fi (xx#txx6 r3c t|S)ai 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 )rUisnarWr\s r#rzGeoSeries.isna&sLw|~r3c"|jS)z4Alias for `isna` method. See `isna` for more detail.)rres r#isnullzGeoSeries.isnullNsyy{r3c|jjrtjdtdt |S)aq 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 aGeoSeries.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. Given a GeoSeries 's', you can use '~s.is_empty & s.notna()' to get back the old behaviour. To further ignore this warning, you can do: import warnings; warnings.filterwarnings('ignore', 'GeoSeries.notna', UserWarning)r^)r_)is_emptyanyrJra UserWarningrUnotnars r#rzGeoSeries.notnaRs=L ==    MM2 w}r3c"|jS)z6Alias for `notna` method. See `notna` for more detail.)rres r#notnullzGeoSeries.notnullszz|r3c B| t}t|d|||d|S)aD 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 )rclimitrr)rrUfillna)rWrcrrr"r\s r#rzGeoSeries.fillnas.R =&(Ew~RER6RRr3clt|tr$tj|j |Sy)zAllow 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". F)rCrnpr geom_equals)rWothers r# __contains__zGeoSeries.__contains__s+ e\ *66$**512 2r3c t|g|i|Sr5r rs r#plotzGeoSeries.plots41$1&11r3c t|g|i|S)z;Explore with an interactive map based on folium/leaflet.js.r rs r#explorezGeoSeries.explores"$8888r3cddlm}tj|jj d\}}||j |||}t|||jj|S)uK 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 r)_get_index_for_partsT) return_index) ignore_index index_partsr|) basershapely get_partsrb_datarr r __finalize__)rWrrr geometries outer_idxrs r#explodezGeoSeries.explodesdb / ' 1 1$++2C2CRV W I$ JJ %#  5dhh?LLTRRr3cddlm}||j|}n||j|}|s&|j|j|k(s t d|s|j }n|}||j_|S)uV 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 r)CRSzThe 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.)pyprojrfrom_user_input from_epsgrrFrErD)rWrepsgrallow_overriderrs r#rzGeoSeries.set_crs/sd  ?%%c*C  --%C$(("6txx3L  YY[FF  r3c|t|jj|||j|jS)ut Return 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 )rrr@)r rbto_crsrr=)rWrrs r#rzGeoSeries.to_crss5X KK  3T  2$**499  r3c8|jj|S)uHReturn 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 )rbestimate_utm_crs)rW datum_names r#rzGeoSeries.estimate_utm_crssH{{++J77r3c N|jdjdd|||d|S)aReturn 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", "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]}' See Also -------- GeoSeries.to_file : write GeoSeries to file r(null)na show_bboxdrop_idto_wgs84r)to_frameto_json)rWrrrr"s r#rzGeoSeries.to_json s9h1t}}Z(00 Gh RX  r3c \tt|jfd|i||jS)aConvert 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 hexr)rrrDr)rWrr"s r#rzGeoSeries.to_wkbDs(*fTZZ;S;F;4::NNr3c Xtt|jfi||jS)aConvert 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 r)rrrDr)rWr"s r#rzGeoSeries.to_wkt[s$BfTZZ262$**EEr3cddlm}m}m}|j |jnd}|j dk(r8|t j|j|||j|\}} nW|j dk(r6|t j|j||j\}} ntd|||| S) a 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 ] r) GeoArrowArrayconstruct_geometry_arrayconstruct_wkb_arraygeoarrow) include_z field_namer interleavedwkb)rrz3Expected geometry encoding 'WKB' or 'geoarrow' got ) rrrrr=lowerrrDrasarrayrF) rWgeometry_encodingrrrrrrfieldgeom_arrs r#to_arrowzGeoSeries.to_arrow~sB  #'))"7TYYR  " " $ 26$#%HH' OE8 $ $ &% /1 4::&:488OE8()+  UH--r3c4tj||||S)aClip 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,) )maskkeep_geom_typesort)r)clip)rWrrrs r#rzGeoSeries.clipsr~~dnSWXXr3NNNr Any | None)returnr )rr)rtos.PathLike | typing.IOrr )NNraise)rrrr )rrrrrwstrrr )rdict)NN)rtrrz str | Noner bool | None)Nr)rr )NFN)rbool)rr )FF)NNFF)rrr int | Nonerr rr )rrrr rr )zWGS 84)rr)TFF)rr rr rr rr)F)rr rr)WKBTN)rr rr )9__name__ __module__ __qualname____doc__rVr rsetterpropertyr(rgrjrmro classmethodrrrrr~rxrrrrrrrrrrr6rrrrrrrrrrrrr rrrrequires_pyprojrrrrrrrr __classcell__)r\s@r#r r NsZJXM^ ) )--2--4--4%-%-N(2(2TBI? $.? ? ? BBI7 $.7 7 7 r2U2Uh !  "*        , ; ;DBB8"! F>)F>F> F>X44.$$$? ^JJ ^DD ^ &P4lKSZ  22 99<SB $ d dd d  ddLN `$8P 6 6 6  6 6 pO.!FF[.z9Y9Yr3r rrr5)0 __future__rtypingrJrnumpyrpandasr6rpandas.core.internalsrrshapely.geometryrshapely.geometry.baserr)geopandas.baser r geopandas.explorer geopandas.plottingrrrr _decoratorrrDrrrrrrrrr TYPE_CHECKINGoscollections.abcrr$r2r9r rr3r#r$s" 4/.<0*#  (.2 8 * 8& FY vFYr3