import json
import os
import re
import shutil
import tempfile
from enum import Enum

import numpy as np
import pandas as pd

from shapely.geometry import Point, Polygon, box

import geopandas
import geopandas._compat as compat
from geopandas import GeoDataFrame, GeoSeries, points_from_xy, read_file
from geopandas.array import GeometryArray, GeometryDtype, from_shapely

import pytest
from geopandas.testing import assert_geodataframe_equal, assert_geoseries_equal
from geopandas.tests.util import PACKAGE_DIR, validate_boro_df
from pandas.testing import assert_frame_equal, assert_index_equal, assert_series_equal


@pytest.fixture
def dfs(request):
    s1 = GeoSeries(
        [
            Polygon([(0, 0), (2, 0), (2, 2), (0, 2)]),
            Polygon([(2, 2), (4, 2), (4, 4), (2, 4)]),
        ]
    )
    s2 = GeoSeries(
        [
            Polygon([(1, 1), (3, 1), (3, 3), (1, 3)]),
            Polygon([(3, 3), (5, 3), (5, 5), (3, 5)]),
        ]
    )
    df1 = GeoDataFrame({"col1": [1, 2], "geometry": s1})
    df2 = GeoDataFrame({"col2": [1, 2], "geometry": s2})
    return df1, df2


@pytest.fixture(
    params=["union", "intersection", "difference", "symmetric_difference", "identity"]
)
def how(request):
    return request.param


@pytest.mark.usefixtures("_setup_class_nybb_filename")
class TestDataFrame:
    def setup_method(self):
        N = 10
        # self.nybb_filename attached via _setup_class_nybb_filename
        self.df = read_file(self.nybb_filename)
        # TODO re-write instance variables to be fixtures
        self.tempdir = tempfile.mkdtemp()
        self.crs = "epsg:4326"
        self.df2 = GeoDataFrame(
            [
                {"geometry": Point(x, y), "value1": x + y, "value2": x * y}
                for x, y in zip(range(N), range(N))
            ],
            crs=self.crs,
        )
        self.df3 = read_file(
            os.path.join(PACKAGE_DIR, "geopandas", "tests", "data", "null_geom.geojson")
        )

    def teardown_method(self):
        shutil.rmtree(self.tempdir)

    def test_df_init(self):
        assert type(self.df2) is GeoDataFrame
        if compat.HAS_PYPROJ:
            assert self.df2.crs == self.crs

    @pytest.mark.skipif(not compat.HAS_PYPROJ, reason="Requires pyproj")
    def test_different_geo_colname(self):
        from pyproj.exceptions import CRSError

        data = {
            "A": range(5),
            "B": range(-5, 0),
            "location": [Point(x, y) for x, y in zip(range(5), range(5))],
        }
        df = GeoDataFrame(data, crs=self.crs, geometry="location")
        locs = GeoSeries(data["location"], crs=self.crs)
        assert_geoseries_equal(df.geometry, locs)
        assert "geometry" not in df
        assert df.geometry.name == "location"
        # internal implementation detail
        assert df._geometry_column_name == "location"

        geom2 = [Point(x, y) for x, y in zip(range(5, 10), range(5))]
        with pytest.raises(CRSError):
            df.set_geometry(geom2, crs="dummy_crs")

    @pytest.mark.filterwarnings("ignore:Geometry is in a geographic CRS")
    def test_geo_getitem(self):
        data = {
            "A": range(5),
            "B": range(-5, 0),
            "location": [Point(x, y) for x, y in zip(range(5), range(5))],
        }
        df = GeoDataFrame(data, crs=self.crs, geometry="location")
        assert isinstance(df.geometry, GeoSeries)
        df["geometry"] = df["A"]
        assert isinstance(df.geometry, GeoSeries)
        assert df.geometry[0] == data["location"][0]
        # good if this changed in the future
        assert not isinstance(df["geometry"], GeoSeries)
        assert isinstance(df["location"], GeoSeries)

        df["buff"] = df.buffer(1)
        assert isinstance(df["buff"], GeoSeries)

        df["array"] = from_shapely([Point(x, y) for x, y in zip(range(5), range(5))])
        assert isinstance(df["array"], GeoSeries)

        data["geometry"] = [Point(x + 1, y - 1) for x, y in zip(range(5), range(5))]
        df = GeoDataFrame(data, crs=self.crs)
        assert isinstance(df.geometry, GeoSeries)
        assert isinstance(df["geometry"], GeoSeries)
        # good if this changed in the future
        assert not isinstance(df["location"], GeoSeries)

    def test_getitem_no_geometry(self):
        res = self.df2[["value1", "value2"]]
        assert isinstance(res, pd.DataFrame)
        assert not isinstance(res, GeoDataFrame)

        # with different name
        df = self.df2.copy()
        df = df.rename(columns={"geometry": "geom"}).set_geometry("geom")
        assert isinstance(df, GeoDataFrame)
        res = df[["value1", "value2"]]
        assert isinstance(res, pd.DataFrame)
        assert not isinstance(res, GeoDataFrame)

        df["geometry"] = np.arange(len(df))
        res = df[["value1", "value2", "geometry"]]
        assert isinstance(res, pd.DataFrame)
        assert not isinstance(res, GeoDataFrame)

    def test_geo_setitem(self):
        data = {
            "A": range(5),
            "B": np.arange(5.0),
            "geometry": [Point(x, y) for x, y in zip(range(5), range(5))],
        }
        df = GeoDataFrame(data)
        s = GeoSeries([Point(x, y + 1) for x, y in zip(range(5), range(5))])

        expected = s.copy()

        # setting geometry column
        for vals in [s, s.values]:
            df["geometry"] = vals
            assert_geoseries_equal(df["geometry"], expected)
            assert_geoseries_equal(df.geometry, expected)

        # non-aligned values
        s2 = GeoSeries([Point(x, y + 1) for x, y in zip(range(6), range(6))])
        df["geometry"] = s2
        assert_geoseries_equal(df["geometry"], expected)
        assert_geoseries_equal(df.geometry, expected)

        # setting other column with geometry values -> preserve geometry type
        for vals in [s, s.values]:
            df["other_geom"] = vals
            assert isinstance(df["other_geom"].values, GeometryArray)

        # overwriting existing non-geometry column -> preserve geometry type
        data = {
            "A": range(5),
            "B": np.arange(5.0),
            "other_geom": range(5),
            "geometry": [Point(x, y) for x, y in zip(range(5), range(5))],
        }
        df = GeoDataFrame(data)
        for vals in [s, s.values]:
            df["other_geom"] = vals
            assert isinstance(df["other_geom"].values, GeometryArray)

    def test_geometry_property(self):
        assert_geoseries_equal(
            self.df.geometry,
            self.df["geometry"],
            check_dtype=True,
            check_index_type=True,
        )

        df = self.df.copy()
        new_geom = [
            Point(x, y) for x, y in zip(range(len(self.df)), range(len(self.df)))
        ]
        df.geometry = new_geom

        new_geom = GeoSeries(new_geom, index=df.index, crs=df.crs)
        assert_geoseries_equal(df.geometry, new_geom)
        assert_geoseries_equal(df["geometry"], new_geom)

        if compat.HAS_PYPROJ:
            # new crs
            gs = new_geom.to_crs(crs="epsg:3857")
            df.geometry = gs
            assert df.crs == "epsg:3857"

    def test_geometry_property_errors(self):
        with pytest.raises(AttributeError):
            df = self.df.copy()
            del df["geometry"]
            df.geometry

        # list-like error
        with pytest.raises(ValueError):
            df = self.df2.copy()
            df.geometry = "value1"

        # list-like error
        with pytest.raises(ValueError):
            df = self.df.copy()
            df.geometry = "apple"

        # non-geometry error
        with pytest.raises(TypeError):
            df = self.df.copy()
            df.geometry = list(range(df.shape[0]))

        with pytest.raises(KeyError):
            df = self.df.copy()
            del df["geometry"]
            df["geometry"]

        # ndim error
        with pytest.raises(ValueError):
            df = self.df.copy()
            df.geometry = df

    def test_rename_geometry(self):
        assert self.df.geometry.name == "geometry"
        df2 = self.df.rename_geometry("new_name")
        assert df2.geometry.name == "new_name"
        df2 = self.df.rename_geometry("new_name", inplace=True)
        assert df2 is None
        assert self.df.geometry.name == "new_name"

        # existing column error
        msg = "Column named Shape_Area already exists"
        with pytest.raises(ValueError, match=msg):
            df2 = self.df.rename_geometry("Shape_Area")
        with pytest.raises(ValueError, match=msg):
            self.df.rename_geometry("Shape_Area", inplace=True)

    def test_set_geometry(self):
        geom = GeoSeries([Point(x, y) for x, y in zip(range(5), range(5))])
        original_geom = self.df.geometry
        expected = geom.copy()
        expected.crs = self.df.crs

        df2 = self.df.set_geometry(geom)
        assert df2 is not self.df
        assert_geoseries_equal(df2.geometry, expected)
        assert_geoseries_equal(self.df.geometry, original_geom)
        assert_geoseries_equal(self.df["geometry"], self.df.geometry)
        # unknown column
        with pytest.raises(ValueError):
            self.df.set_geometry("nonexistent-column")

        # ndim error
        with pytest.raises(ValueError):
            self.df.set_geometry(self.df)

    @pytest.mark.skipif(not compat.HAS_PYPROJ, reason="Requires pyproj")
    def test_set_geometry_crs(self):
        geom = GeoSeries([Point(x, y) for x, y in zip(range(5), range(5))])

        # new crs - setting should default to GeoSeries' crs
        gs = GeoSeries(geom, crs="epsg:3857")
        new_df = self.df.set_geometry(gs)
        assert new_df.crs == "epsg:3857"

        # explicit crs overrides self and dataframe
        new_df = self.df.set_geometry(gs, crs="epsg:26909")
        assert new_df.crs == "epsg:26909"
        assert new_df.geometry.crs == "epsg:26909"

        # Series should use dataframe's
        new_df = self.df.set_geometry(geom.values)
        assert new_df.crs == self.df.crs
        assert new_df.geometry.crs == self.df.crs

    def test_set_geometry_col(self):
        g = self.df.geometry
        g_simplified = g.simplify(100)
        self.df["simplified_geometry"] = g_simplified.copy()
        df2 = self.df.set_geometry("simplified_geometry")

        # Drop is false by default
        assert "simplified_geometry" in df2
        assert_geoseries_equal(df2.geometry, g_simplified)

        # If True, drops column and renames to geometry
        with pytest.warns(FutureWarning):
            df3 = self.df.set_geometry("simplified_geometry", drop=True)
        assert "simplified_geometry" not in df3
        assert_geoseries_equal(df3.geometry, g_simplified)

    def test_set_geometry_inplace(self):
        geom = [Point(x, y) for x, y in zip(range(5), range(5))]
        ret = self.df.set_geometry(geom, inplace=True)
        assert ret is None
        geom = GeoSeries(geom, index=self.df.index, crs=self.df.crs)
        assert_geoseries_equal(self.df.geometry, geom)

    def test_set_geometry_series(self):
        # Test when setting geometry with a Series that
        # alignment will occur
        #
        # Reverse the index order
        # Set the Series to be Point(i,i) where i is the index
        self.df.index = range(len(self.df) - 1, -1, -1)

        d = {}
        for i in range(len(self.df)):
            d[i] = Point(i, i)
        g = GeoSeries(d)
        # At this point, the DataFrame index is [4,3,2,1,0] and the
        # GeoSeries index is [0,1,2,3,4]. Make sure set_geometry aligns
        # them to match indexes
        df = self.df.set_geometry(g)

        for i, r in df.iterrows():
            assert i == r["geometry"].x
            assert i == r["geometry"].y

    def test_set_geometry_empty(self):
        df = pd.DataFrame(columns=["a", "geometry"], index=pd.DatetimeIndex([]))
        result = df.set_geometry("geometry")
        assert isinstance(result, GeoDataFrame)
        assert isinstance(result.index, pd.DatetimeIndex)

    def test_set_geometry_np_int(self):
        self.df.loc[:, 0] = self.df.geometry
        df = self.df.set_geometry(np.int64(0))
        assert df.geometry.name == 0

    def test_get_geometry_invalid(self):
        df = GeoDataFrame()
        # no column "geometry" ever added
        df["geom"] = self.df.geometry
        msg_geo_col_none = "active geometry column to use has not been set. "

        with pytest.raises(AttributeError, match=msg_geo_col_none):
            df.geometry
        # "geometry" originally present but dropped (but still a gdf)
        col_subset_drop_geometry = ["BoroCode", "BoroName", "geom2"]
        df2 = self.df.copy().assign(geom2=self.df.geometry)[col_subset_drop_geometry]
        with pytest.raises(AttributeError, match="is not present."):
            df2.geometry

        msg_other_geo_cols_present = "There are columns with geometry data type"
        msg_no_other_geo_cols = "There are no existing columns with geometry data type"
        with pytest.raises(AttributeError, match=msg_other_geo_cols_present):
            df2.geometry

        with pytest.raises(AttributeError, match=msg_no_other_geo_cols):
            GeoDataFrame().geometry

    def test_get_geometry_geometry_inactive(self):
        # https://github.com/geopandas/geopandas/issues/2574
        df = self.df.assign(geom2=self.df.geometry).set_geometry("geom2")
        df = df.loc[:, ["BoroName", "geometry"]]
        assert df._geometry_column_name == "geom2"
        msg_geo_col_missing = "is not present. "
        # Check that df.geometry raises if active geometry column is missing,
        # it should not fall back to column named "geometry"
        with pytest.raises(AttributeError, match=msg_geo_col_missing):
            df.geometry

    @pytest.mark.skipif(not compat.HAS_PYPROJ, reason="Requires pyproj")
    def test_override_existing_crs_warning(self):
        with pytest.warns(
            DeprecationWarning,
            match="Overriding the CRS of a GeoSeries that already has CRS",
        ):
            self.df.geometry.crs = "epsg:2100"

        with pytest.warns(
            DeprecationWarning,
            match="Overriding the CRS of a GeoDataFrame that already has CRS",
        ):
            self.df.crs = "epsg:4326"

    def test_active_geometry_name(self):
        # default single active called "geometry"
        assert self.df.active_geometry_name == "geometry"

        # one GeoSeries, not active
        no_active = GeoDataFrame({"foo": self.df.BoroName, "bar": self.df.geometry})
        assert no_active.active_geometry_name is None
        assert no_active.set_geometry("bar").active_geometry_name == "bar"

        # multiple, none active
        multiple = GeoDataFrame({"foo": self.df.geometry, "bar": self.df.geometry})
        assert multiple.active_geometry_name is None
        assert multiple.set_geometry("foo").active_geometry_name == "foo"
        assert multiple.set_geometry("bar").active_geometry_name == "bar"

    def test_align(self):
        df = self.df2

        res1, res2 = df.align(df)
        assert_geodataframe_equal(res1, df)
        assert_geodataframe_equal(res2, df)

        res1, res2 = df.align(df.copy())
        assert_geodataframe_equal(res1, df)
        assert_geodataframe_equal(res2, df)

        if compat.HAS_PYPROJ:
            # assert crs is / is not preserved on mixed dataframes
            df_nocrs = df.copy().set_crs(None, allow_override=True)
            res1, res2 = df.align(df_nocrs)
            assert_geodataframe_equal(res1, df)
            assert res1.crs is not None
            assert_geodataframe_equal(res2, df_nocrs)
            assert res2.crs is None

        # mixed GeoDataFrame / DataFrame
        df_nogeom = pd.DataFrame(df.drop("geometry", axis=1))
        res1, res2 = df.align(df_nogeom, axis=0)
        assert_geodataframe_equal(res1, df)
        assert type(res2) is pd.DataFrame
        assert_frame_equal(res2, df_nogeom)

        # same as above but now with actual alignment
        df1 = df.iloc[1:].copy()
        df2 = df.iloc[:-1].copy()

        exp1 = df.copy()
        exp1.iloc[0] = np.nan
        exp2 = df.copy()
        exp2.iloc[-1] = np.nan
        res1, res2 = df1.align(df2)
        assert_geodataframe_equal(res1, exp1)
        assert_geodataframe_equal(res2, exp2)

        if compat.HAS_PYPROJ:
            df2_nocrs = df2.copy().set_crs(None, allow_override=True)
            exp2_nocrs = exp2.copy().set_crs(None, allow_override=True)
            res1, res2 = df1.align(df2_nocrs)
            assert_geodataframe_equal(res1, exp1)
            assert res1.crs is not None
            assert_geodataframe_equal(res2, exp2_nocrs)
            assert res2.crs is None

        df2_nogeom = pd.DataFrame(df2.drop("geometry", axis=1))
        exp2_nogeom = pd.DataFrame(exp2.drop("geometry", axis=1))
        res1, res2 = df1.align(df2_nogeom, axis=0)
        assert_geodataframe_equal(res1, exp1)
        assert type(res2) is pd.DataFrame
        assert_frame_equal(res2, exp2_nogeom)

    @pytest.mark.skipif(not compat.HAS_PYPROJ, reason="Requires pyproj")
    def test_to_json(self):
        text = self.df.to_json(to_wgs84=True)
        data = json.loads(text)
        assert data["type"] == "FeatureCollection"
        assert len(data["features"]) == 5
        assert "id" in data["features"][0].keys()

        # check it converts to WGS84
        coord = data["features"][0]["geometry"]["coordinates"][0][0][0]
        np.testing.assert_allclose(coord, [-74.0505080640324, 40.5664220341941])

    def test_to_json_missing_geom_errors_nicely(self):
        df = self.df.copy()
        # mock doing some operation where the tracking of the active geometry
        # column is lost
        df._geometry_column_name = None
        msg = re.escape(
            "You are calling a geospatial method on the GeoDataFrame, but the "
            "active geometry column to use has not been set"
        )
        with pytest.raises(AttributeError, match=msg):
            df.to_json()

    def test_to_json_wgs84_false(self):
        text = self.df.to_json()
        data = json.loads(text)
        # check it doesn't convert to WGS84
        coord = data["features"][0]["geometry"]["coordinates"][0][0][0]
        assert coord == [970217.0223999023, 145643.33221435547]

    def test_to_json_no_crs(self):
        self.df.geometry.array.crs = None
        with pytest.raises(ValueError, match="CRS is not set"):
            self.df.to_json(to_wgs84=True)

    @pytest.mark.filterwarnings(
        "ignore:Geometry column does not contain geometry:UserWarning"
    )
    def test_to_json_geom_col(self):
        df = self.df.copy()
        df["geom"] = df["geometry"]
        df["geometry"] = np.arange(len(df))
        df.set_geometry("geom", inplace=True)

        text = df.to_json()
        data = json.loads(text)
        assert data["type"] == "FeatureCollection"
        assert len(data["features"]) == 5

    def test_to_json_only_geom_column(self):
        text = self.df[["geometry"]].to_json()
        data = json.loads(text)
        assert len(data["features"]) == 5
        assert "id" in data["features"][0].keys()

    def test_to_json_na(self):
        # Set a value as nan and make sure it's written
        self.df.loc[self.df["BoroName"] == "Queens", "Shape_Area"] = np.nan

        text = self.df.to_json()
        data = json.loads(text)
        assert len(data["features"]) == 5
        for f in data["features"]:
            props = f["properties"]
            assert len(props) == 4
            if props["BoroName"] == "Queens":
                assert props["Shape_Area"] is None

    def test_to_json_bad_na(self):
        # Check that a bad na argument raises error
        with pytest.raises(ValueError):
            self.df.to_json(na="garbage")

    def test_to_json_dropna(self):
        self.df.loc[self.df["BoroName"] == "Queens", "Shape_Area"] = np.nan
        self.df.loc[self.df["BoroName"] == "Bronx", "Shape_Leng"] = np.nan

        text = self.df.to_json(na="drop")
        data = json.loads(text)
        assert len(data["features"]) == 5
        for f in data["features"]:
            props = f["properties"]
            if props["BoroName"] == "Queens":
                assert len(props) == 3
                assert "Shape_Area" not in props
                # Just make sure setting it to nan in a different row
                # doesn't affect this one
                assert "Shape_Leng" in props
            elif props["BoroName"] == "Bronx":
                assert len(props) == 3
                assert "Shape_Leng" not in props
                assert "Shape_Area" in props
            else:
                assert len(props) == 4

    def test_to_json_keepna(self):
        self.df.loc[self.df["BoroName"] == "Queens", "Shape_Area"] = np.nan
        self.df.loc[self.df["BoroName"] == "Bronx", "Shape_Leng"] = np.nan

        text = self.df.to_json(na="keep")
        data = json.loads(text)
        assert len(data["features"]) == 5
        for f in data["features"]:
            props = f["properties"]
            assert len(props) == 4
            if props["BoroName"] == "Queens":
                assert np.isnan(props["Shape_Area"])
                # Just make sure setting it to nan in a different row
                # doesn't affect this one
                assert "Shape_Leng" in props
            elif props["BoroName"] == "Bronx":
                assert np.isnan(props["Shape_Leng"])
                assert "Shape_Area" in props

    def test_to_json_drop_id(self):
        text = self.df.to_json(drop_id=True)
        data = json.loads(text)
        assert len(data["features"]) == 5
        for f in data["features"]:
            assert "id" not in f.keys()

    def test_to_json_drop_id_only_geom_column(self):
        text = self.df[["geometry"]].to_json(drop_id=True)
        data = json.loads(text)
        assert len(data["features"]) == 5
        for f in data["features"]:
            assert "id" not in f.keys()

    def test_to_json_with_duplicate_columns(self):
        df = GeoDataFrame(
            data=[[1, 2, 3]], columns=["a", "b", "a"], geometry=[Point(1, 1)]
        )
        with pytest.raises(
            ValueError, match="GeoDataFrame cannot contain duplicated column names."
        ):
            df.to_json()

    def test_copy(self):
        df2 = self.df.copy()
        assert type(df2) is GeoDataFrame
        assert self.df.crs == df2.crs

    def test_empty_copy(self):
        # https://github.com/geopandas/geopandas/issues/2765
        df = GeoDataFrame()
        df2 = df.copy()
        assert type(df2) is GeoDataFrame
        df3 = df.copy(deep=True)
        assert type(df3) is GeoDataFrame

    def test_no_geom_copy(self):
        df = GeoDataFrame(pd.DataFrame({"a": [1, 2, 3]}))
        assert type(df) is GeoDataFrame
        assert type(df.copy()) is GeoDataFrame

    def test_empty(self):
        df = GeoDataFrame({"geometry": []})
        assert df.geometry.dtype == "geometry"
        df = GeoDataFrame({"a": []}, geometry="a")
        assert df.geometry.dtype == "geometry"
        df = GeoDataFrame(geometry=[])
        assert df.geometry.dtype == "geometry"

    def test_bool_index(self):
        # Find boros with 'B' in their name
        df = self.df[self.df["BoroName"].str.contains("B")]
        assert len(df) == 2
        boros = df["BoroName"].values
        assert "Brooklyn" in boros
        assert "Bronx" in boros
        assert type(df) is GeoDataFrame

    def test_coord_slice_points(self):
        assert self.df2.cx[-2:-1, -2:-1].empty
        assert_frame_equal(self.df2, self.df2.cx[:, :])
        assert_frame_equal(self.df2.loc[5:], self.df2.cx[5:, :])
        assert_frame_equal(self.df2.loc[5:], self.df2.cx[:, 5:])
        assert_frame_equal(self.df2.loc[5:], self.df2.cx[5:, 5:])

    def test_from_dict(self):
        data = {"A": [1], "geometry": [Point(0.0, 0.0)]}
        df = GeoDataFrame.from_dict(data, crs=3857)
        if compat.HAS_PYPROJ:
            assert df.crs == "epsg:3857"
        else:
            assert df.crs is None
        assert df._geometry_column_name == "geometry"

        data = {"B": [1], "location": [Point(0.0, 0.0)]}
        df = GeoDataFrame.from_dict(data, geometry="location")
        assert df._geometry_column_name == "location"

    def test_from_features(self, nybb_filename):
        fiona = pytest.importorskip("fiona")
        with fiona.open(nybb_filename) as f:
            features = list(f)
            crs = f.crs_wkt

        df = GeoDataFrame.from_features(features, crs=crs)
        validate_boro_df(df, case_sensitive=True)
        if compat.HAS_PYPROJ:
            assert df.crs == crs
        else:
            assert df.crs is None

    def test_from_features_unaligned_properties(self):
        p1 = Point(1, 1)
        f1 = {
            "type": "Feature",
            "properties": {"a": 0},
            "geometry": p1.__geo_interface__,
        }

        p2 = Point(2, 2)
        f2 = {
            "type": "Feature",
            "properties": {"b": 1},
            "geometry": p2.__geo_interface__,
        }

        p3 = Point(3, 3)
        f3 = {
            "type": "Feature",
            "properties": None,
            "geometry": p3.__geo_interface__,
        }

        df = GeoDataFrame.from_features([f1, f2, f3])

        result = df[["a", "b"]]
        expected = pd.DataFrame.from_dict(
            [{"a": 0, "b": np.nan}, {"a": np.nan, "b": 1}, {"a": np.nan, "b": np.nan}]
        )
        assert_frame_equal(expected, result)

    def test_from_features_empty_properties(self):
        geojson_properties_object = """{
          "type": "FeatureCollection",
          "features": [
            {
              "type": "Feature",
              "properties": {},
              "geometry": {
                "type": "Polygon",
                "coordinates": [
                  [
                    [
                      11.3456529378891,
                      46.49461446367692
                    ],
                    [
                      11.345674395561216,
                      46.494097442978195
                    ],
                    [
                      11.346918940544128,
                      46.49385370294394
                    ],
                    [
                      11.347616314888,
                      46.4938352377453
                    ],
                    [
                      11.347514390945435,
                      46.49466985846028
                    ],
                    [
                      11.3456529378891,
                      46.49461446367692
                    ]
                  ]
                ]
              }
            }
          ]
        }"""

        geojson_properties_null = """{
          "type": "FeatureCollection",
          "features": [
            {
              "type": "Feature",
              "properties": null,
              "geometry": {
                "type": "Polygon",
                "coordinates": [
                  [
                    [
                      11.3456529378891,
                      46.49461446367692
                    ],
                    [
                      11.345674395561216,
                      46.494097442978195
                    ],
                    [
                      11.346918940544128,
                      46.49385370294394
                    ],
                    [
                      11.347616314888,
                      46.4938352377453
                    ],
                    [
                      11.347514390945435,
                      46.49466985846028
                    ],
                    [
                      11.3456529378891,
                      46.49461446367692
                    ]
                  ]
                ]
              }
            }
          ]
        }"""

        # geoJSON with empty properties
        gjson_po = json.loads(geojson_properties_object)
        gdf1 = GeoDataFrame.from_features(gjson_po)

        # geoJSON with null properties
        gjson_null = json.loads(geojson_properties_null)
        gdf2 = GeoDataFrame.from_features(gjson_null)

        assert_frame_equal(gdf1, gdf2)

    def test_from_features_geom_interface_feature(self):
        class Placemark:
            def __init__(self, geom, val):
                self.__geo_interface__ = {
                    "type": "Feature",
                    "properties": {"a": val},
                    "geometry": geom.__geo_interface__,
                }

        p1 = Point(1, 1)
        f1 = Placemark(p1, 0)
        p2 = Point(3, 3)
        f2 = Placemark(p2, 0)
        df = GeoDataFrame.from_features([f1, f2])
        assert sorted(df.columns) == ["a", "geometry"]
        assert df.geometry.tolist() == [p1, p2]

    def test_from_feature_collection(self):
        data = {
            "name": ["a", "b", "c"],
            "lat": [45, 46, 47.5],
            "lon": [-120, -121.2, -122.9],
        }

        df = pd.DataFrame(data)
        geometry = [Point(xy) for xy in zip(df["lon"], df["lat"])]
        gdf = GeoDataFrame(df, geometry=geometry)
        # from_features returns sorted columns
        expected = gdf[["geometry", "name", "lat", "lon"]]

        # test FeatureCollection
        res = GeoDataFrame.from_features(gdf.__geo_interface__)
        assert_frame_equal(res, expected)

        # test list of Features
        res = GeoDataFrame.from_features(gdf.__geo_interface__["features"])
        assert_frame_equal(res, expected)

        # test __geo_interface__ attribute (a GeoDataFrame has one)
        res = GeoDataFrame.from_features(gdf)
        assert_frame_equal(res, expected)

    def test_dataframe_to_geodataframe(self):
        df = pd.DataFrame(
            {"A": range(len(self.df)), "location": np.array(self.df.geometry)},
            index=self.df.index,
        )
        gf = df.set_geometry("location", crs=self.df.crs)
        assert isinstance(df, pd.DataFrame)
        assert isinstance(gf, GeoDataFrame)
        assert_geoseries_equal(gf.geometry, self.df.geometry)
        assert gf.geometry.name == "location"
        assert "geometry" not in gf

        with pytest.warns(FutureWarning):
            gf2 = df.set_geometry("location", crs=self.df.crs, drop=True)
        assert isinstance(df, pd.DataFrame)
        assert isinstance(gf2, GeoDataFrame)
        assert gf2.geometry.name == "geometry"
        assert "geometry" in gf2
        assert "location" not in gf2
        assert "location" in df

        # should be a copy
        df.loc[0, "A"] = 100
        assert gf.loc[0, "A"] == 0
        assert gf2.loc[0, "A"] == 0

        with pytest.raises(ValueError):
            df.set_geometry("location", inplace=True)

    def test_dataframe_not_manipulated(self):
        df = pd.DataFrame(
            {
                "A": range(len(self.df)),
                "latitude": self.df.geometry.centroid.y,
                "longitude": self.df.geometry.centroid.x,
            },
            index=self.df.index,
        )
        df_copy = df.copy()
        gf = GeoDataFrame(
            df,
            geometry=points_from_xy(df["longitude"], df["latitude"]),
            crs=self.df.crs,
        )
        assert type(df) is pd.DataFrame
        assert "geometry" not in df
        assert_frame_equal(df, df_copy)
        assert isinstance(gf, GeoDataFrame)
        assert hasattr(gf, "geometry")

        # ensure mutating columns in gf doesn't update df
        gf.loc[0, "A"] = 7
        assert_frame_equal(df, df_copy)
        gf["A"] = 3
        assert_frame_equal(df, df_copy)

    def test_geodataframe_geointerface(self):
        assert self.df.__geo_interface__["type"] == "FeatureCollection"
        assert len(self.df.__geo_interface__["features"]) == self.df.shape[0]

    def test_geodataframe_iterfeatures(self):
        df = self.df.iloc[:1].copy()
        df.loc[0, "BoroName"] = np.nan
        # when containing missing values
        # null: output the missing entries as JSON null
        result = next(iter(df.iterfeatures(na="null")))["properties"]
        assert result["BoroName"] is None
        # drop: remove the property from the feature.
        result = next(iter(df.iterfeatures(na="drop")))["properties"]
        assert "BoroName" not in result.keys()
        # keep: output the missing entries as NaN
        result = next(iter(df.iterfeatures(na="keep")))["properties"]
        assert np.isnan(result["BoroName"])

        # test for checking that the (non-null) features are python scalars and
        # not numpy scalars
        assert type(df.loc[0, "Shape_Leng"]) is np.float64
        # null
        result = next(iter(df.iterfeatures(na="null")))
        assert isinstance(result["properties"]["Shape_Leng"], float)
        # drop
        result = next(iter(df.iterfeatures(na="drop")))
        assert isinstance(result["properties"]["Shape_Leng"], float)
        # keep
        result = next(iter(df.iterfeatures(na="keep")))
        assert isinstance(result["properties"]["Shape_Leng"], float)

        # when only having numerical columns
        df_only_numerical_cols = df[["Shape_Leng", "Shape_Area", "geometry"]]
        assert type(df_only_numerical_cols.loc[0, "Shape_Leng"]) is np.float64
        # null
        result = next(iter(df_only_numerical_cols.iterfeatures(na="null")))
        assert isinstance(result["properties"]["Shape_Leng"], float)
        # drop
        result = next(iter(df_only_numerical_cols.iterfeatures(na="drop")))
        assert isinstance(result["properties"]["Shape_Leng"], float)
        # keep
        result = next(iter(df_only_numerical_cols.iterfeatures(na="keep")))
        assert isinstance(result["properties"]["Shape_Leng"], float)

        with pytest.raises(
            ValueError, match="GeoDataFrame cannot contain duplicated column names."
        ):
            df_with_duplicate_columns = df[
                ["Shape_Leng", "Shape_Leng", "Shape_Area", "geometry"]
            ]
            list(df_with_duplicate_columns.iterfeatures())

        # geometry not set
        df = GeoDataFrame({"values": [0, 1], "geom": [Point(0, 1), Point(1, 0)]})
        with pytest.raises(AttributeError):
            list(df.iterfeatures())

    def test_geodataframe_iterfeatures_non_scalars(self):
        # When some features in geodataframe are non-scalar values
        df = GeoDataFrame(
            {"geometry": [Point(1, 2)], "non-scalar": [[1, 2]], "test_col": None}
        )
        # null
        expected = {"non-scalar": [1, 2], "test_col": None}
        result = next(iter(df.iterfeatures(na="null"))).get("properties")
        assert expected == result
        # drop
        expected = {"non-scalar": [1, 2]}
        result = next(iter(df.iterfeatures(na="drop"))).get("properties")
        assert expected == result
        # keep
        expected = {"non-scalar": [1, 2], "test_col": None}
        result = next(iter(df.iterfeatures(na="keep"))).get("properties")
        assert expected == result

    def test_geodataframe_geojson_no_bbox(self):
        geo = self.df.to_geo_dict(na="null", show_bbox=False)
        assert "bbox" not in geo.keys()
        for feature in geo["features"]:
            assert "bbox" not in feature.keys()

    def test_geodataframe_geojson_bbox(self):
        geo = self.df.to_geo_dict(na="null", show_bbox=True)
        assert "bbox" in geo.keys()
        assert len(geo["bbox"]) == 4
        assert isinstance(geo["bbox"], tuple)
        for bound in geo["bbox"]:
            assert not isinstance(bound, np.float64)
        for feature in geo["features"]:
            assert "bbox" in feature.keys()

    def test_pickle(self):
        import pickle

        df2 = pickle.loads(pickle.dumps(self.df))
        assert_geodataframe_equal(self.df, df2)

    def test_pickle_method(self):
        filename = os.path.join(self.tempdir, "df.pkl")
        self.df.to_pickle(filename)
        unpickled = pd.read_pickle(filename)
        assert_frame_equal(self.df, unpickled)
        assert self.df.crs == unpickled.crs

    def test_estimate_utm_crs(self):
        pyproj = pytest.importorskip("pyproj")

        assert self.df.estimate_utm_crs() == pyproj.CRS("EPSG:32618")
        assert self.df.estimate_utm_crs("NAD83") == pyproj.CRS("EPSG:26918")

    def test_to_wkb(self):
        wkbs0 = [
            (  # POINT (0 0)
                b"\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00"
                b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00"
            ),
            (  # POINT (1 1)
                b"\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00"
                b"\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?"
            ),
        ]
        wkbs1 = [
            (  # POINT (2 2)
                b"\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00"
                b"\x00\x00@\x00\x00\x00\x00\x00\x00\x00@"
            ),
            (  # POINT (3 3)
                b"\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00"
                b"\x00\x08@\x00\x00\x00\x00\x00\x00\x08@"
            ),
        ]
        gs0 = GeoSeries.from_wkb(wkbs0)
        gs1 = GeoSeries.from_wkb(wkbs1)
        gdf = GeoDataFrame({"geom_col0": gs0, "geom_col1": gs1})

        expected_df = pd.DataFrame({"geom_col0": wkbs0, "geom_col1": wkbs1})
        assert_frame_equal(expected_df, gdf.to_wkb())

    def test_to_wkt(self):
        wkts0 = ["POINT (0 0)", "POINT (1 1)"]
        wkts1 = ["POINT (2 2)", "POINT (3 3)"]
        gs0 = GeoSeries.from_wkt(wkts0)
        gs1 = GeoSeries.from_wkt(wkts1)
        gdf = GeoDataFrame({"gs0": gs0, "gs1": gs1})

        expected_df = pd.DataFrame({"gs0": wkts0, "gs1": wkts1})
        assert_frame_equal(expected_df, gdf.to_wkt())

    @pytest.mark.parametrize("how", ["left", "inner", "right"])
    @pytest.mark.parametrize("predicate", ["intersects", "within", "contains"])
    def test_sjoin(self, how, predicate, naturalearth_cities, naturalearth_lowres):
        """
        Basic test for availability of the GeoDataFrame method. Other
        sjoin tests are located in /tools/tests/test_sjoin.py
        """
        left = read_file(naturalearth_cities)
        right = read_file(naturalearth_lowres)

        expected = geopandas.sjoin(left, right, how=how, predicate=predicate)
        result = left.sjoin(right, how=how, predicate=predicate)
        assert_geodataframe_equal(result, expected)

    @pytest.mark.parametrize("how", ["left", "inner", "right"])
    @pytest.mark.parametrize("distance", [0, 3])
    @pytest.mark.skipif(
        not compat.GEOS_GE_310,
        reason="`dwithin` requires GEOS 3.10",
    )
    def test_sjoin_dwithin(self, how, distance):
        """
        Basic test for predicate='dwithin' availability of the GeoDataFrame method.
        Other sjoin tests are located in /tools/tests/test_sjoin.py
        """
        left = GeoDataFrame(geometry=points_from_xy([0, 1, 2], [0, 1, 1]))
        right = GeoDataFrame(geometry=[box(0, 0, 1, 1)])

        expected = geopandas.sjoin(
            left, right, how=how, predicate="dwithin", distance=distance
        )
        result = left.sjoin(right, how=how, predicate="dwithin", distance=distance)
        assert_geodataframe_equal(result, expected)

    @pytest.mark.parametrize("how", ["left", "inner", "right"])
    @pytest.mark.parametrize("max_distance", [None, 1])
    @pytest.mark.parametrize("distance_col", [None, "distance"])
    @pytest.mark.filterwarnings("ignore:Geometry is in a geographic CRS:UserWarning")
    def test_sjoin_nearest(
        self, how, max_distance, distance_col, naturalearth_cities, naturalearth_lowres
    ):
        """
        Basic test for availability of the GeoDataFrame method. Other
        sjoin tests are located in /tools/tests/test_sjoin.py
        """
        left = read_file(naturalearth_cities)
        right = read_file(naturalearth_lowres)

        expected = geopandas.sjoin_nearest(
            left, right, how=how, max_distance=max_distance, distance_col=distance_col
        )
        result = left.sjoin_nearest(
            right, how=how, max_distance=max_distance, distance_col=distance_col
        )
        assert_geodataframe_equal(result, expected)

    def test_clip(self, naturalearth_cities, naturalearth_lowres):
        """
        Basic test for availability of the GeoDataFrame method. Other
        clip tests are located in /tools/tests/test_clip.py
        """
        left = read_file(naturalearth_cities)
        world = read_file(naturalearth_lowres)
        south_america = world[world["continent"] == "South America"]

        expected = geopandas.clip(left, south_america)
        result = left.clip(south_america)
        assert_geodataframe_equal(result, expected)

    def test_clip_sorting(self, naturalearth_cities, naturalearth_lowres):
        """
        Test sorting of geodataframe when clipping.
        """
        cities = read_file(naturalearth_cities)
        world = read_file(naturalearth_lowres)
        south_america = world[world["continent"] == "South America"]

        unsorted_clipped_cities = geopandas.clip(cities, south_america, sort=False)
        sorted_clipped_cities = geopandas.clip(cities, south_america, sort=True)

        expected_sorted_index = pd.Index(
            [55, 59, 62, 88, 101, 114, 122, 169, 181, 189, 210, 230, 236, 238, 239]
        )

        assert not (
            sorted(unsorted_clipped_cities.index) == unsorted_clipped_cities.index
        ).all()
        assert (
            sorted(sorted_clipped_cities.index) == sorted_clipped_cities.index
        ).all()
        assert_index_equal(expected_sorted_index, sorted_clipped_cities.index)

    def test_overlay(self, dfs, how):
        """
        Basic test for availability of the GeoDataFrame method. Other
        overlay tests are located in tests/test_overlay.py
        """
        df1, df2 = dfs

        expected = geopandas.overlay(df1, df2, how=how)
        result = df1.overlay(df2, how=how)
        assert_geodataframe_equal(result, expected)


def check_geodataframe(df, geometry_column="geometry"):
    assert isinstance(df, GeoDataFrame)
    assert isinstance(df.geometry, GeoSeries)
    assert isinstance(df[geometry_column], GeoSeries)
    assert df._geometry_column_name == geometry_column
    assert df.geometry.name == geometry_column
    assert isinstance(df.geometry.values, GeometryArray)
    assert isinstance(df.geometry.dtype, GeometryDtype)


class TestConstructor:
    def test_dict(self):
        data = {
            "A": range(3),
            "B": np.arange(3.0),
            "geometry": [Point(x, x) for x in range(3)],
        }
        df = GeoDataFrame(data)
        check_geodataframe(df)

        # with specifying other kwargs
        df = GeoDataFrame(data, index=list("abc"))
        check_geodataframe(df)
        assert_index_equal(df.index, pd.Index(list("abc")))

        df = GeoDataFrame(data, columns=["B", "A", "geometry"])
        check_geodataframe(df)
        assert_index_equal(df.columns, pd.Index(["B", "A", "geometry"]))

        df = GeoDataFrame(data, columns=["A", "geometry"])
        check_geodataframe(df)
        assert_index_equal(df.columns, pd.Index(["A", "geometry"]))
        assert_series_equal(df["A"], pd.Series(range(3), name="A"))

    def test_dict_of_series(self):
        data = {
            "A": pd.Series(range(3)),
            "B": pd.Series(np.arange(3.0)),
            "geometry": GeoSeries([Point(x, x) for x in range(3)]),
        }

        df = GeoDataFrame(data)
        check_geodataframe(df)

        df = GeoDataFrame(data, index=pd.Index([1, 2]))
        check_geodataframe(df)
        assert_index_equal(df.index, pd.Index([1, 2]))
        assert df["A"].tolist() == [1, 2]

        # one non-series -> length is not correct
        data = {
            "A": pd.Series(range(3)),
            "B": np.arange(3.0),
            "geometry": GeoSeries([Point(x, x) for x in range(3)]),
        }
        with pytest.raises(ValueError):
            GeoDataFrame(data, index=[1, 2])

    def test_dict_specified_geometry(self):
        data = {
            "A": range(3),
            "B": np.arange(3.0),
            "other_geom": [Point(x, x) for x in range(3)],
        }

        df = GeoDataFrame(data, geometry="other_geom")
        check_geodataframe(df, "other_geom")

        with pytest.raises(ValueError):
            df = GeoDataFrame(data, geometry="geometry")

        # when no geometry specified -> works but raises error once
        # trying to access geometry
        df = GeoDataFrame(data)

        with pytest.raises(AttributeError):
            _ = df.geometry

        df = df.set_geometry("other_geom")
        check_geodataframe(df, "other_geom")

        # combined with custom args
        df = GeoDataFrame(data, geometry="other_geom", columns=["B", "other_geom"])
        check_geodataframe(df, "other_geom")
        assert_index_equal(df.columns, pd.Index(["B", "other_geom"]))
        assert_series_equal(df["B"], pd.Series(np.arange(3.0), name="B"))

        df = GeoDataFrame(data, geometry="other_geom", columns=["other_geom", "A"])
        check_geodataframe(df, "other_geom")
        assert_index_equal(df.columns, pd.Index(["other_geom", "A"]))
        assert_series_equal(df["A"], pd.Series(range(3), name="A"))

    def test_array(self):
        data = {
            "A": range(3),
            "B": np.arange(3.0),
            "geometry": [Point(x, x) for x in range(3)],
        }
        a = np.array([data["A"], data["B"], data["geometry"]], dtype=object).T

        df = GeoDataFrame(a, columns=["A", "B", "geometry"])
        check_geodataframe(df)

        df = GeoDataFrame(a, columns=["A", "B", "other_geom"], geometry="other_geom")
        check_geodataframe(df, "other_geom")

    def test_from_frame(self):
        data = {
            "A": range(3),
            "B": np.arange(3.0),
            "geometry": [Point(x, x) for x in range(3)],
        }
        gpdf = GeoDataFrame(data)
        pddf = pd.DataFrame(data)
        check_geodataframe(gpdf)
        assert type(pddf) is pd.DataFrame

        for df in [gpdf, pddf]:
            res = GeoDataFrame(df)
            check_geodataframe(res)

            res = GeoDataFrame(df, index=pd.Index([0, 2]))
            check_geodataframe(res)
            assert_index_equal(res.index, pd.Index([0, 2]))
            assert res["A"].tolist() == [0, 2]

            res = GeoDataFrame(df, columns=["geometry", "B"])
            check_geodataframe(res)
            assert_index_equal(res.columns, pd.Index(["geometry", "B"]))

            with pytest.raises(ValueError):
                GeoDataFrame(df, geometry="other_geom")

    def test_from_frame_specified_geometry(self):
        data = {
            "A": range(3),
            "B": np.arange(3.0),
            "other_geom": [Point(x, x) for x in range(3)],
        }

        gpdf = GeoDataFrame(data, geometry="other_geom")
        check_geodataframe(gpdf, "other_geom")
        pddf = pd.DataFrame(data)

        for df in [gpdf, pddf]:
            res = GeoDataFrame(df, geometry="other_geom")
            check_geodataframe(res, "other_geom")

        # gdf from gdf should preserve active geometry column name
        df = GeoDataFrame(gpdf)
        check_geodataframe(df, "other_geom")

    def test_only_geometry(self):
        exp = GeoDataFrame(
            {"geometry": [Point(x, x) for x in range(3)], "other": range(3)}
        )[["geometry"]]

        df = GeoDataFrame(geometry=[Point(x, x) for x in range(3)])
        check_geodataframe(df)
        assert_geodataframe_equal(df, exp)

        df = GeoDataFrame({"geometry": [Point(x, x) for x in range(3)]})
        check_geodataframe(df)
        assert_geodataframe_equal(df, exp)

        df = GeoDataFrame(
            {"other_geom": [Point(x, x) for x in range(3)]}, geometry="other_geom"
        )
        check_geodataframe(df, "other_geom")
        exp = exp.rename(columns={"geometry": "other_geom"}).set_geometry("other_geom")
        assert_geodataframe_equal(df, exp)

    def test_no_geometries(self):
        # keeps GeoDataFrame class (no DataFrame)
        data = {"A": range(3), "B": np.arange(3.0)}
        df = GeoDataFrame(data)
        assert type(df) is GeoDataFrame

        gdf = GeoDataFrame({"x": [1]})
        assert list(gdf.x) == [1]

    def test_empty(self):
        df = GeoDataFrame()
        assert type(df) is GeoDataFrame

        df = GeoDataFrame({"A": [], "B": []}, geometry=[])
        assert type(df) is GeoDataFrame

    def test_column_ordering(self):
        geoms = [Point(1, 1), Point(2, 2), Point(3, 3)]
        gs = GeoSeries(geoms)
        gdf = GeoDataFrame(
            {"a": [1, 2, 3], "geometry": gs},
            columns=["geometry", "a"],
            geometry="geometry",
        )
        check_geodataframe(gdf)
        assert list(gdf.columns) == ["geometry", "a"]

        # with non-default index
        gdf = GeoDataFrame(
            {"a": [1, 2, 3], "geometry": gs},
            columns=["geometry", "a"],
            index=pd.Index([0, 0, 1]),
            geometry="geometry",
        )
        check_geodataframe(gdf)
        assert list(gdf.columns) == ["geometry", "a"]

    def test_do_not_preserve_series_name_in_constructor(self):
        # GH3337
        # GeoDataFrame(... geometry=...) should always create geom col "geometry"
        geoms = [Point(1, 1), Point(2, 2), Point(3, 3)]
        gs = GeoSeries(geoms)
        gdf = GeoDataFrame({"a": [1, 2, 3]}, geometry=gs)
        check_geodataframe(gdf, geometry_column="geometry")
        # still get "geometry", even with custom geoseries name
        gs = GeoSeries(geoms, name="my_geom")
        gdf = GeoDataFrame({"a": [1, 2, 3]}, geometry=gs)
        check_geodataframe(gdf, geometry_column="geometry")

    def test_overwrite_geometry(self):
        # GH602
        data = pd.DataFrame({"geometry": [1, 2, 3], "col1": [4, 5, 6]})
        geoms = pd.Series([Point(i, i) for i in range(3)])
        # passed geometry kwarg should overwrite geometry column in data
        res = GeoDataFrame(data, geometry=geoms)
        assert_geoseries_equal(res.geometry, GeoSeries(geoms))

    def test_repeat_geo_col(self):
        df = pd.DataFrame(
            [
                {"geometry": Point(x, y), "geom": Point(x, y)}
                for x, y in zip(range(3), range(3))
            ],
        )
        # explicitly prevent construction of gdf with repeat geometry column names
        # two columns called "geometry", geom col inferred
        df2 = df.rename(columns={"geom": "geometry"})
        with pytest.raises(ValueError):
            GeoDataFrame(df2)
        # ensure case is caught when custom geom column name is used
        # two columns called "geom", geom col explicit
        df3 = df.rename(columns={"geometry": "geom"})
        with pytest.raises(ValueError):
            GeoDataFrame(df3, geometry="geom")

    @pytest.mark.parametrize("dtype", ["geometry", "object"])
    def test_multiindex_with_geometry_label(self, dtype):
        # DataFrame with MultiIndex where "geometry" label corresponds to
        # multiple columns
        df = pd.DataFrame([[Point(0, 0), Point(1, 1)], [Point(2, 2), Point(3, 3)]])
        df = df.astype(dtype)
        df.columns = pd.MultiIndex.from_product([["geometry"], [0, 1]])
        # don't error in constructor
        gdf = GeoDataFrame(df)
        with pytest.raises(AttributeError, match=".*geometry .* has not been set.*"):
            gdf.geometry
        res_gdf = gdf.set_geometry(("geometry", 0))
        assert res_gdf.shape == gdf.shape
        assert isinstance(res_gdf.geometry, GeoSeries)

    def test_default_geo_colname_none(self):
        match = "You are adding a column named 'geometry' to a GeoDataFrame"
        gdf = GeoDataFrame({"a": [1, 2]})

        gdf2 = gdf.copy()
        geo_col = GeoSeries.from_xy([1, 3], [3, 3])
        with pytest.warns(FutureWarning, match=match):
            gdf2["geometry"] = geo_col
        assert gdf2._geometry_column_name == "geometry"
        gdf4 = gdf.copy()
        with pytest.warns(FutureWarning, match=match):
            gdf4.geometry = geo_col
        assert gdf4._geometry_column_name == "geometry"

        # geo col name should only change if we add geometry
        gdf5 = gdf.copy()
        with pytest.warns(
            UserWarning, match="Geometry column does not contain geometry"
        ):
            gdf5["geometry"] = "foo"
        assert gdf5._geometry_column_name is None
        with pytest.warns(FutureWarning, match=match):
            gdf3 = gdf.copy().assign(geometry=geo_col)
        assert gdf3._geometry_column_name == "geometry"

        # Check that adding a GeoSeries to a column called "geometry" to a
        # gdf without an active geometry column some time after the init does not
        # warn / set the active geometry column
        gdf6 = gdf.copy()
        gdf6["geom2"] = geo_col
        gdf6["geom3"] = geo_col
        gdf6 = gdf6.set_geometry("geom2")
        subset = gdf6[["a", "geom3"]]  # this has a missing active geometry col
        assert subset._geometry_column_name == "geom2"
        subset["geometry"] = geo_col
        # adding column called geometry shouldn't auto-set
        assert subset._geometry_column_name == "geom2"

    def test_multiindex_geometry_colname_2_level(self):
        # GH1763 https://github.com/geopandas/geopandas/issues/1763
        crs = "EPSG:4326"
        df = pd.DataFrame(
            [[1, 0], [0, 1]], columns=[["location", "location"], ["x", "y"]]
        )
        x_col = df["location", "x"]
        y_col = df["location", "y"]

        gdf = GeoDataFrame(df, crs=crs, geometry=points_from_xy(x_col, y_col))
        if compat.HAS_PYPROJ:
            assert gdf.crs == crs
            assert gdf.geometry.crs == crs
        assert gdf.geometry.dtype == "geometry"
        assert gdf._geometry_column_name == "geometry"
        assert gdf.geometry.name == "geometry"

    def test_multiindex_geometry_colname_3_level(self):
        # GH1763 https://github.com/geopandas/geopandas/issues/1763
        # Note 3-level case uses different code paths in pandas, it is not redundant
        crs = "EPSG:4326"
        df = pd.DataFrame(
            [[1, 0], [0, 1]],
            columns=[
                ["foo", "foo"],
                ["location", "location"],
                ["x", "y"],
            ],
        )

        x_col = df["foo", "location", "x"]
        y_col = df["foo", "location", "y"]

        gdf = GeoDataFrame(df, crs=crs, geometry=points_from_xy(x_col, y_col))
        if compat.HAS_PYPROJ:
            assert gdf.crs == crs
            assert gdf.geometry.crs == crs
        assert gdf.geometry.dtype == "geometry"
        assert gdf._geometry_column_name == "geometry"
        assert gdf.geometry.name == "geometry"

    def test_multiindex_geometry_colname_3_level_new_col(self):
        crs = "EPSG:4326"
        df = pd.DataFrame(
            [[1, 0], [0, 1]],
            columns=[
                ["foo", "foo"],
                ["location", "location"],
                ["x", "y"],
            ],
        )

        x_col = df["foo", "location", "x"]
        y_col = df["foo", "location", "y"]
        df["geometry"] = GeoSeries.from_xy(x_col, y_col)
        df2 = df.copy()
        gdf = df.set_geometry("geometry", crs=crs)
        if compat.HAS_PYPROJ:
            assert gdf.crs == crs
        assert gdf._geometry_column_name == "geometry"
        assert gdf.geometry.name == "geometry"
        # test again setting with tuple col name
        gdf = df2.set_geometry(("geometry", "", ""), crs=crs)
        if compat.HAS_PYPROJ:
            assert gdf.crs == crs
        assert gdf._geometry_column_name == ("geometry", "", "")
        assert gdf.geometry.name == ("geometry", "", "")

    def test_assign_cols_using_index(self, nybb_filename):
        df = read_file(nybb_filename)
        other_df = pd.DataFrame({"foo": range(5), "bar": range(5)})
        expected = pd.concat([df, other_df], axis=1)
        df[other_df.columns] = other_df
        assert_geodataframe_equal(df, expected)

    def test_geometry_colname_enum(self):
        # ensure that other classes to geometry arg in GeoDataFrame
        # with `name` attribute are not assumed to be (Geo)Series
        class Fruit(Enum):
            apple = 1
            pear = 2

        df = pd.DataFrame(
            {Fruit.apple: [1, 2], Fruit.pear: GeoSeries.from_xy([1, 2], [3, 4])}
        )
        res = GeoDataFrame(df, geometry=Fruit.pear)
        assert res.active_geometry_name == Fruit.pear

    def test_geometry_nan_scalar(self):
        gdf = GeoDataFrame(
            data=[[np.nan, np.nan]],
            columns=["geometry", "something"],
            crs="EPSG:4326",
        )
        assert gdf.shape == (1, 2)
        assert gdf.active_geometry_name == "geometry"
        assert gdf.geometry[0] is None
        if compat.HAS_PYPROJ:
            assert gdf.crs == "EPSG:4326"

    def test_geometry_nan_array(self):
        gdf = GeoDataFrame(
            {
                "geometry": [np.nan, None, pd.NA],
                "something": [np.nan, np.nan, np.nan],
            },
            crs="EPSG:4326",
        )
        assert gdf.shape == (3, 2)
        assert gdf.active_geometry_name == "geometry"
        assert gdf.geometry.isna().all()
        if compat.HAS_PYPROJ:
            assert gdf.crs == "EPSG:4326"


@pytest.mark.skipif(not compat.HAS_PYPROJ, reason="pyproj not available")
def test_geodataframe_crs():
    gdf = GeoDataFrame(columns=["geometry"])
    gdf.crs = "IGNF:ETRS89UTM28"
    assert gdf.crs.to_authority() == ("IGNF", "ETRS89UTM28")


def test_geodataframe_nocrs_json():
    # no CRS, no crs field
    gdf = GeoDataFrame(columns=["geometry"])
    gdf_geojson = json.loads(gdf.to_json())
    assert "crs" not in gdf_geojson

    # WGS84, no crs field (default as per spec)
    gdf.crs = 4326
    gdf_geojson = json.loads(gdf.to_json())
    assert "crs" not in gdf_geojson


@pytest.mark.skipif(not compat.HAS_PYPROJ, reason="pyproj not available")
def test_geodataframe_crs_json():
    gdf = GeoDataFrame(columns=["geometry"])
    gdf.crs = 25833
    gdf_geojson = json.loads(gdf.to_json())
    assert "crs" in gdf_geojson
    assert gdf_geojson["crs"] == {
        "type": "name",
        "properties": {"name": "urn:ogc:def:crs:EPSG::25833"},
    }
    gdf_geointerface = gdf.__geo_interface__
    assert "crs" not in gdf_geointerface


@pytest.mark.skipif(not compat.HAS_PYPROJ, reason="pyproj not available")
@pytest.mark.parametrize(
    "crs",
    ["+proj=cea +lon_0=0 +lat_ts=45 +x_0=0 +y_0=0 +ellps=WGS84 +units=m", "IGNF:WGS84"],
)
def test_geodataframe_crs_nonrepresentable_json(crs):
    gdf = GeoDataFrame(
        [Point(1000, 1000)],
        columns=["geometry"],
        crs=crs,
    )
    with pytest.warns(
        UserWarning, match="GeoDataFrame's CRS is not representable in URN OGC"
    ):
        gdf_geojson = json.loads(gdf.to_json())
    assert "crs" not in gdf_geojson


def test_geodataframe_crs_colname():
    # https://github.com/geopandas/geopandas/issues/2942
    gdf = GeoDataFrame({"crs": [1], "geometry": [Point(1, 1)]})
    assert gdf.crs is None
    assert gdf["crs"].iloc[0] == 1
    assert getattr(gdf, "crs") is None

    # https://github.com/geopandas/geopandas/issues/3501
    gdf = GeoDataFrame({"crs": [1]}, geometry=[Point(1, 1)])
    assert gdf.crs is None
    assert gdf["crs"].iloc[0] == 1
    assert getattr(gdf, "crs") is None

    # test multiindex handling
    df = pd.DataFrame([[1, 0], [0, 1]], columns=[["crs", "crs"], ["x", "y"]])
    x_col = df["crs", "x"]
    y_col = df["crs", "y"]

    gdf = GeoDataFrame(df, geometry=points_from_xy(x_col, y_col))
    assert gdf.crs is None
    assert gdf["crs"].iloc[0].to_list() == [1, 0]
    assert getattr(gdf, "crs") is None


@pytest.mark.parametrize("geo_col_name", ["geometry", "polygons"])
def test_set_geometry_supply_colname(dfs, geo_col_name):
    df, _ = dfs
    if geo_col_name != "geometry":
        df = df.rename_geometry(geo_col_name)
    df["centroid"] = df.geometry.centroid
    res = df.set_geometry("centroid")
    assert res.active_geometry_name == "centroid"
    assert geo_col_name in res.columns

    # Test that drop=False explicitly warns
    deprecated = "The `drop` keyword argument is deprecated"
    with pytest.warns(FutureWarning, match=deprecated):
        res2 = df.set_geometry("centroid", drop=False)
    assert_geodataframe_equal(res, res2)

    with pytest.warns(FutureWarning, match=deprecated):
        res3 = df.set_geometry("centroid", drop=True)
    # drop=True should preserve previous geometry col name (keep old behaviour)
    assert res3.active_geometry_name == geo_col_name
    assert "centroid" not in res3.columns

    # Test that alternative suggested without using drop=True is equivalent
    assert_geodataframe_equal(
        res3,
        df.set_geometry("centroid")
        .drop(columns=geo_col_name)
        .rename_geometry(geo_col_name),
    )


@pytest.mark.parametrize("geo_col_name", ["geometry", "polygons"])
def test_set_geometry_supply_arraylike(dfs, geo_col_name):
    df, _ = dfs
    if geo_col_name != "geometry":
        df = df.rename_geometry(geo_col_name)
    centroids = df.geometry.centroid
    res = df.set_geometry(centroids)
    assert res.active_geometry_name == geo_col_name
    # drop should do nothing if the column already exists
    match_str = (
        "The `drop` keyword argument is deprecated and has no effect when "
        "`col` is an array-like value"
    )
    with pytest.warns(
        FutureWarning,
        match=match_str,
    ):
        res2 = df.set_geometry(centroids, drop=True)
    assert res2.active_geometry_name == geo_col_name

    centroids = centroids.rename("centroids")
    res3 = df.set_geometry(centroids)
    # Should preserve the geoseries name
    # (and old geometry column should be kept)
    assert res3.active_geometry_name == "centroids"
    assert geo_col_name in res3.columns

    # Drop should not remove previous active geometry colname for arraylike inputs
    with pytest.warns(
        FutureWarning,
        match=match_str,
    ):
        res4 = df.set_geometry(centroids, drop=True)
    assert res4.active_geometry_name == "centroids"
    assert geo_col_name in res4.columns


@pytest.mark.filterwarnings("error::FutureWarning")
def test_reduce_geometry_array():
    """
    Check for a FutureWarning.

    `geopandas.array.GeometryArray._reduce` issues a FutureWarning if
    the parameter `keepdims` is not set.
    `GeometryArray` inherits from `pandas.api.extensions.ExtensionArray`
    and its `_reduce` is overridden in `GeometryArray`.
    This warning is issued with pandas 2.2.2 (tested).
    """
    GeoDataFrame({"geometry": []}).all()


class GDFChild(GeoDataFrame):
    def custom_method(self):
        return "this is a custom output"


def test_inheritance(dfs):
    df, _ = dfs
    df.loc[:, "col2"] = ["a"] * len(df)

    dfc = GDFChild(df)

    dfc2 = dfc.rename_geometry("geometry2")

    children = [
        dfc,
        dfc.iloc[[0]],
        dfc.loc[dfc.col1 == 1],
        dfc.dissolve(),
        dfc[["col2", "geometry"]],
        dfc.copy(),
        dfc2,
        dfc2.iloc[[0]],
        dfc2.loc[dfc.col1 == 1],
        dfc2.dissolve(),
        dfc2[["col2", "geometry2"]],
        dfc2.copy(),
    ]

    for v in children:
        assert isinstance(v, GDFChild)
        assert v.custom_method() == "this is a custom output"

    df2 = dfc2.drop(columns=["geometry2"])

    assert not isinstance(df2, GDFChild)
