fix Error Indexing DafaFrame with a 0-d array #22032
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| df = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b']) | ||
| ar = np.array(0) | ||
| msg = 'Cannot index by location index with a non-integer key' | ||
| tm.assert_raises_regex(TypeError, msg, |
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Can use assertraisesregex as a context here
| type(key) is not tuple) | ||
| return (is_list_like(key) | ||
| and not (isinstance(key, tuple) and type(key) is not tuple) | ||
| and not np.array(key).ndim == 0) |
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You're really just checking if you have a scalar. Is it possible to use (and potentially modify) is_scalar from pandas.core.dtypes.inference?
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Possibly! I'll look into that more tomorrow.
| @@ -890,6 +890,13 @@ def test_no_reference_cycle(self): | |||
| del df | |||
| assert wr() is None | |||
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| def test_zero_index_iloc_raises(self): | |||
| df = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b']) | |||
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Reference issue as a comment below the function def.
gfyoung
added
Indexing
| @@ -4178,6 +4178,8 @@ def _validate_indexer(self, form, key, kind): | |||
| pass | |||
| elif is_integer(key): | |||
| pass | |||
| elif np.array(key).ndim == 0: | |||
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pls don’t do this
you end up materializing the key which could be expensive
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Yea I wasn't really happy with it as is anyways and since it seems to break some tests I'll probably change it in the AM.
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Hmm..it seems after reverting my changes and taking a look at my test again that the test still passes. I think I have either a bad test or this was fixed on master before I looked at it? I'm gonna try to build from master and repro in the AM. |
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Yea confirmed. I checked on master today and we give out the expected error in this instance. |
closes #21946
git diff upstream/master -u -- "*.py" | flake8 --diff