{"action":"created","comment":{"url":"https://api.github.com/repos/pandas-dev/pandas/pulls/comments/211896440","pull_request_review_id":148411325,"id":211896440,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIxMTg5NjQ0MA==","diff_hunk":"@@ -263,6 +263,21 @@ def test_drop_duplicates_tuple():\n     tm.assert_frame_equal(result, expected)\n \n \n+@pytest.mark.parametrize('df', [\n+    DataFrame(),\n+    DataFrame(columns=[]),\n+    DataFrame(columns=['A', 'B', 'C']),\n+    DataFrame(index=[]),\n+    DataFrame(index=['A', 'B', 'C'])\n+])\n+def test_drop_duplicates_empty(df):\n+    # GH 20516\n+    result = df.drop_duplicates()\n+    if df.columns.empty is False:\n+        df = DataFrame(columns=[])\n+    tm.assert_frame_equal(result, df)","path":"pandas/tests/frame/test_duplicates.py","position":16,"original_position":16,"commit_id":"68d69dbd8fa592f3a5120a92717a9ef7d00f7a41","original_commit_id":"68d69dbd8fa592f3a5120a92717a9ef7d00f7a41","user":{"login":"datapythonista","id":10058240,"node_id":"MDQ6VXNlcjEwMDU4MjQw","avatar_url":"https://avatars2.githubusercontent.com/u/10058240?v=4","gravatar_id":"","url":"https://api.github.com/users/datapythonista","html_url":"https://github.com/datapythonista","followers_url":"https://api.github.com/users/datapythonista/followers","following_url":"https://api.github.com/users/datapythonista/following{/other_user}","gists_url":"https://api.github.com/users/datapythonista/gists{/gist_id}","starred_url":"https://api.github.com/users/datapythonista/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/datapythonista/subscriptions","organizations_url":"https://api.github.com/users/datapythonista/orgs","repos_url":"https://api.github.com/users/datapythonista/repos","events_url":"https://api.github.com/users/datapythonista/events{/privacy}","received_events_url":"https://api.github.com/users/datapythonista/received_events","type":"User","site_admin":false},"body":"This tests feels a bit tricky to me. So, when there are columns, we set them to an empty list. So, that would be the same as simply using as expected value `DataFrame(columns=[])`, or am I missing something?\r\n\r\nBut not sure if I'm missing something, but I'd expect `DataFrame(columns=['A', 'B', 'C']).drop_duplicates()` to keep the columns. Any reason to drop 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