BUG: fix ngroups and len(groups) inconsistency when using [Grouper(freq=)] (GH33132) #33135
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falcaopetri
changed the title
| @@ -1863,6 +1863,17 @@ def test_groupby_groups_in_BaseGrouper(): | |||
| expected = df.groupby(["beta", "alpha"]) | |||
| assert result.groups == expected.groups | |||
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| # GH 33132 | |||
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can you make this a separate test
| result = df.groupby(["beta", pd.Grouper(level="alpha", freq='D')]) | ||
| assert result.ngroups == len(result) | ||
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| result = df.groupby([pd.Grouper(level="alpha", freq='D'), "beta"]) |
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linter is going to want double-quotes on 'D'
jreback
reviewed
Mar 30, 2020
| @@ -837,11 +838,22 @@ def names(self): | |||
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| @property | |||
| def groupings(self) -> "List[grouper.Grouping]": | |||
| codes, _, _ = self.group_info | |||
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I am not really sure what you are hoping to accomplish here.
| ] | ||
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| def __iter__(self): |
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the issue then len(Grouper) != ngroups right? why are you adding __iter__? rather than for example overriding __len__?
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Indeed changing __iter__ was a bad idea since this changes the behavior of resample. Anyway, iterating over a nested BinGrouper is somewhat part of the problem (check #33132 (comment) plz). #33303 probably has a better approach to resolve this.
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black pandasgit diff upstream/master -u -- "*.py" | flake8 --diff