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ENH: Add ignore_index for df.drop_duplicates #30405
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| Original file line number | Diff line number | Diff line change |
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@@ -4587,6 +4587,7 @@ def drop_duplicates( | |
| subset: Optional[Union[Hashable, Sequence[Hashable]]] = None, | ||
| keep: Union[str, bool] = "first", | ||
| inplace: bool = False, | ||
| ignore_index: bool = False, | ||
| ) -> Optional["DataFrame"]: | ||
| """ | ||
| Return DataFrame with duplicate rows removed. | ||
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@@ -4606,6 +4607,10 @@ def drop_duplicates( | |
| - False : Drop all duplicates. | ||
| inplace : bool, default False | ||
| Whether to drop duplicates in place or to return a copy. | ||
| ignore_index : bool, default False | ||
| If True, the resulting axis will be labeled 0, 1, …, n - 1. | ||
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| .. versionadded:: 1.0.0 | ||
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| Returns | ||
| ------- | ||
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@@ -4621,9 +4626,16 @@ def drop_duplicates( | |
| if inplace: | ||
| (inds,) = (-duplicated)._ndarray_values.nonzero() | ||
| new_data = self._data.take(inds) | ||
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| if ignore_index: | ||
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| new_data.axes[1] = ibase.default_index(len(inds)) | ||
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| self._update_inplace(new_data) | ||
| else: | ||
| return self[-duplicated] | ||
| result = self[-duplicated] | ||
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| if ignore_index: | ||
| result.index = ibase.default_index(sum(-duplicated)) | ||
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| return result | ||
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| return None | ||
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@@ -477,3 +477,46 @@ def test_drop_duplicates_inplace(): | |
| expected = orig2.drop_duplicates(["A", "B"], keep=False) | ||
| result = df2 | ||
| tm.assert_frame_equal(result, expected) | ||
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| @pytest.mark.parametrize( | ||
| "origin_dict, output_dict, ignore_index, output_index", | ||
| [ | ||
| ({"A": [2, 2, 3]}, {"A": [2, 3]}, True, [0, 1]), | ||
| ({"A": [2, 2, 3]}, {"A": [2, 3]}, False, [0, 2]), | ||
| ({"A": [2, 2, 3], "B": [2, 2, 4]}, {"A": [2, 3], "B": [2, 4]}, True, [0, 1]), | ||
| ({"A": [2, 2, 3], "B": [2, 2, 4]}, {"A": [2, 3], "B": [2, 4]}, False, [0, 2]), | ||
| ], | ||
| ) | ||
| def test_drop_duplicates_ignore_index_inplace_false( | ||
| origin_dict, output_dict, ignore_index, output_index | ||
| ): | ||
| # GH 30114 | ||
| df = DataFrame(origin_dict) | ||
| result = df.drop_duplicates(ignore_index=ignore_index) | ||
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| expected = DataFrame(output_dict, index=output_index) | ||
| tm.assert_frame_equal(result, expected) | ||
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| # to verify if original dataframe is not mutated | ||
| tm.assert_frame_equal(df, DataFrame(origin_dict)) | ||
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| @pytest.mark.parametrize( | ||
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| "origin_dict, output_dict, ignore_index, output_index", | ||
| [ | ||
| ({"A": [2, 2, 3]}, {"A": [2, 3]}, True, [0, 1]), | ||
| ({"A": [2, 2, 3]}, {"A": [2, 3]}, False, [0, 2]), | ||
| ({"A": [2, 2, 3], "B": [2, 2, 4]}, {"A": [2, 3], "B": [2, 4]}, True, [0, 1]), | ||
| ({"A": [2, 2, 3], "B": [2, 2, 4]}, {"A": [2, 3], "B": [2, 4]}, False, [0, 2]), | ||
| ], | ||
| ) | ||
| def test_drop_duplicates_ignore_index_inplace_true( | ||
| origin_dict, output_dict, ignore_index, output_index | ||
| ): | ||
| # GH 30114, to check if correct when inplace is True | ||
| df = DataFrame(origin_dict) | ||
| df.drop_duplicates(ignore_index=ignore_index, inplace=True) | ||
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| expected = DataFrame(output_dict, index=output_index) | ||
| tm.assert_frame_equal(df, expected) | ||
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