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