done

lib/python3.11/site-packages/pandas/tests/frame/methods/test_pop.py

@@ -0,0 +1,72 @@
+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)