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import numpy as np
import pandas as pd
import geopandas
from geopandas import GeoDataFrame, read_file
from pandas.testing import assert_frame_equal
import pytest
@pytest.fixture
def nybb_polydf():
nybb_filename = geopandas.datasets.get_path("nybb")
nybb_polydf = read_file(nybb_filename)
nybb_polydf = nybb_polydf[["geometry", "BoroName", "BoroCode"]]
nybb_polydf = nybb_polydf.rename(columns={"geometry": "myshapes"})
nybb_polydf = nybb_polydf.set_geometry("myshapes")
nybb_polydf["manhattan_bronx"] = 5
nybb_polydf.loc[3:4, "manhattan_bronx"] = 6
return nybb_polydf
@pytest.fixture
def merged_shapes(nybb_polydf):
# Merged geometry
manhattan_bronx = nybb_polydf.loc[3:4]
others = nybb_polydf.loc[0:2]
collapsed = [others.geometry.unary_union, manhattan_bronx.geometry.unary_union]
merged_shapes = GeoDataFrame(
{"myshapes": collapsed},
geometry="myshapes",
index=pd.Index([5, 6], name="manhattan_bronx"),
crs=nybb_polydf.crs,
)
return merged_shapes
@pytest.fixture
def first(merged_shapes):
first = merged_shapes.copy()
first["BoroName"] = ["Staten Island", "Manhattan"]
first["BoroCode"] = [5, 1]
return first
@pytest.fixture
def expected_mean(merged_shapes):
test_mean = merged_shapes.copy()
test_mean["BoroCode"] = [4, 1.5]
return test_mean
def test_geom_dissolve(nybb_polydf, first):
test = nybb_polydf.dissolve("manhattan_bronx")
assert test.geometry.name == "myshapes"
assert test.geom_almost_equals(first).all()
def test_dissolve_retains_existing_crs(nybb_polydf):
assert nybb_polydf.crs is not None
test = nybb_polydf.dissolve("manhattan_bronx")
assert test.crs is not None
def test_dissolve_retains_nonexisting_crs(nybb_polydf):
nybb_polydf.crs = None
test = nybb_polydf.dissolve("manhattan_bronx")
assert test.crs is None
def first_dissolve(nybb_polydf, first):
test = nybb_polydf.dissolve("manhattan_bronx")
assert_frame_equal(first, test, check_column_type=False)
def test_mean_dissolve(nybb_polydf, first, expected_mean):
test = nybb_polydf.dissolve("manhattan_bronx", aggfunc="mean")
assert_frame_equal(expected_mean, test, check_column_type=False)
test = nybb_polydf.dissolve("manhattan_bronx", aggfunc=np.mean)
assert_frame_equal(expected_mean, test, check_column_type=False)
def test_multicolumn_dissolve(nybb_polydf, first):
multi = nybb_polydf.copy()
multi["dup_col"] = multi.manhattan_bronx
multi_test = multi.dissolve(["manhattan_bronx", "dup_col"], aggfunc="first")
first_copy = first.copy()
first_copy["dup_col"] = first_copy.index
first_copy = first_copy.set_index([first_copy.index, "dup_col"])
assert_frame_equal(multi_test, first_copy, check_column_type=False)
def test_reset_index(nybb_polydf, first):
test = nybb_polydf.dissolve("manhattan_bronx", as_index=False)
comparison = first.reset_index()
assert_frame_equal(comparison, test, check_column_type=False)
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