Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

ENH: Add ignore_index for df.drop_duplicates #30405

Merged
merged 15 commits into from
Dec 27, 2019
Merged
Show file tree
Hide file tree
Changes from 7 commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion doc/source/whatsnew/v1.0.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -474,7 +474,7 @@ Other API changes
Supplying anything else than ``how`` to ``**kwargs`` raised a ``TypeError`` previously (:issue:`29388`)
- When testing pandas, the new minimum required version of pytest is 5.0.1 (:issue:`29664`)
- :meth:`Series.str.__iter__` was deprecated and will be removed in future releases (:issue:`28277`).

- Add ``ignore_index`` to :meth:`DataFrame.drop_duplicates` to reset index (:issue:`30114`)
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

reverse the ordering here, e.g. .drop_duplicates has gained the ignore_index keyword.

move to other enhancements

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

moved and rephrased!


.. _whatsnew_1000.api.documentation:

Expand Down
11 changes: 10 additions & 1 deletion pandas/core/frame.py
Original file line number Diff line number Diff line change
Expand Up @@ -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.
Expand All @@ -4606,6 +4607,8 @@ 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.

Returns
-------
Expand All @@ -4621,9 +4624,15 @@ def drop_duplicates(
if inplace:
(inds,) = (-duplicated)._ndarray_values.nonzero()
new_data = self._data.take(inds)

if ignore_index:
new_data.axes[1] = ibase.default_index(len(inds))
self._update_inplace(new_data)
else:
return self[-duplicated]
result = self[-duplicated]
if ignore_index:
return result.reset_index(drop=True)
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

here you have to copy before you update the index

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

i did not use copy, but .index assignment, and i think it is also correct.

return result

return None

Expand Down
20 changes: 20 additions & 0 deletions pandas/tests/frame/test_duplicates.py
Original file line number Diff line number Diff line change
Expand Up @@ -477,3 +477,23 @@ def test_drop_duplicates_inplace():
expected = orig2.drop_duplicates(["A", "B"], keep=False)
result = df2
tm.assert_frame_equal(result, expected)


@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(
origin_dict, output_dict, ignore_index, output_index
):
# GH 30114
df = DataFrame(origin_dict)
result = df.drop_duplicates(ignore_index=ignore_index)

expected = DataFrame(output_dict, index=output_index)
tm.assert_frame_equal(result, expected)