import pytest from pandas import DataFrame import pandas._testing as tm class TestAssign: def test_assign(self): df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) original = df.copy() result = df.assign(C=df.B / df.A) expected = df.copy() expected["C"] = [4, 2.5, 2] tm.assert_frame_equal(result, expected) # lambda syntax result = df.assign(C=lambda x: x.B / x.A) tm.assert_frame_equal(result, expected) # original is unmodified tm.assert_frame_equal(df, original) # Non-Series array-like result = df.assign(C=[4, 2.5, 2]) tm.assert_frame_equal(result, expected) # original is unmodified tm.assert_frame_equal(df, original) result = df.assign(B=df.B / df.A) expected = expected.drop("B", axis=1).rename(columns={"C": "B"}) tm.assert_frame_equal(result, expected) # overwrite result = df.assign(A=df.A + df.B) expected = df.copy() expected["A"] = [5, 7, 9] tm.assert_frame_equal(result, expected) # lambda result = df.assign(A=lambda x: x.A + x.B) tm.assert_frame_equal(result, expected) def test_assign_multiple(self): df = DataFrame([[1, 4], [2, 5], [3, 6]], columns=["A", "B"]) result = df.assign(C=[7, 8, 9], D=df.A, E=lambda x: x.B) expected = DataFrame( [[1, 4, 7, 1, 4], [2, 5, 8, 2, 5], [3, 6, 9, 3, 6]], columns=list("ABCDE") ) tm.assert_frame_equal(result, expected) def test_assign_order(self): # GH 9818 df = DataFrame([[1, 2], [3, 4]], columns=["A", "B"]) result = df.assign(D=df.A + df.B, C=df.A - df.B) expected = DataFrame([[1, 2, 3, -1], [3, 4, 7, -1]], columns=list("ABDC")) tm.assert_frame_equal(result, expected) result = df.assign(C=df.A - df.B, D=df.A + df.B) expected = DataFrame([[1, 2, -1, 3], [3, 4, -1, 7]], columns=list("ABCD")) tm.assert_frame_equal(result, expected) def test_assign_bad(self): df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) # non-keyword argument msg = r"assign\(\) takes 1 positional argument but 2 were given" with pytest.raises(TypeError, match=msg): df.assign(lambda x: x.A) msg = "'DataFrame' object has no attribute 'C'" with pytest.raises(AttributeError, match=msg): df.assign(C=df.A, D=df.A + df.C) def test_assign_dependent(self): df = DataFrame({"A": [1, 2], "B": [3, 4]}) result = df.assign(C=df.A, D=lambda x: x["A"] + x["C"]) expected = DataFrame([[1, 3, 1, 2], [2, 4, 2, 4]], columns=list("ABCD")) tm.assert_frame_equal(result, expected) result = df.assign(C=lambda df: df.A, D=lambda df: df["A"] + df["C"]) expected = DataFrame([[1, 3, 1, 2], [2, 4, 2, 4]], columns=list("ABCD")) tm.assert_frame_equal(result, expected)