import numpy as np
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from pandas import (
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DataFrame,
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MultiIndex,
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Series,
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)
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import pandas._testing as tm
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class TestDataFramePop:
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def test_pop(self, float_frame):
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float_frame.columns.name = "baz"
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float_frame.pop("A")
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assert "A" not in float_frame
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float_frame["foo"] = "bar"
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float_frame.pop("foo")
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assert "foo" not in float_frame
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assert float_frame.columns.name == "baz"
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# gh-10912: inplace ops cause caching issue
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a = DataFrame([[1, 2, 3], [4, 5, 6]], columns=["A", "B", "C"], index=["X", "Y"])
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b = a.pop("B")
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b += 1
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# original frame
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expected = DataFrame([[1, 3], [4, 6]], columns=["A", "C"], index=["X", "Y"])
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tm.assert_frame_equal(a, expected)
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# result
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expected = Series([2, 5], index=["X", "Y"], name="B") + 1
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tm.assert_series_equal(b, expected)
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def test_pop_non_unique_cols(self):
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df = DataFrame({0: [0, 1], 1: [0, 1], 2: [4, 5]})
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df.columns = ["a", "b", "a"]
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res = df.pop("a")
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assert type(res) == DataFrame
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assert len(res) == 2
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assert len(df.columns) == 1
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assert "b" in df.columns
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assert "a" not in df.columns
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assert len(df.index) == 2
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def test_mixed_depth_pop(self):
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arrays = [
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["a", "top", "top", "routine1", "routine1", "routine2"],
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["", "OD", "OD", "result1", "result2", "result1"],
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["", "wx", "wy", "", "", ""],
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]
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tuples = sorted(zip(*arrays))
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index = MultiIndex.from_tuples(tuples)
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df = DataFrame(np.random.randn(4, 6), columns=index)
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df1 = df.copy()
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df2 = df.copy()
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result = df1.pop("a")
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expected = df2.pop(("a", "", ""))
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tm.assert_series_equal(expected, result, check_names=False)
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tm.assert_frame_equal(df1, df2)
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assert result.name == "a"
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expected = df1["top"]
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df1 = df1.drop(["top"], axis=1)
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result = df2.pop("top")
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tm.assert_frame_equal(expected, result)
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tm.assert_frame_equal(df1, df2)
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