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