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BUG: ngroups and len(groups) do not equal when grouping with a list of Grouper and column label (GH26326) #26374

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Merged
merged 20 commits into from
May 20, 2019
Merged

BUG: ngroups and len(groups) do not equal when grouping with a list of Grouper and column label (GH26326) #26374

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47a1057
BUG: ngroups and len(groups) do not equal when grouping with a list o…
shantanu-gontia May 13, 2019
cad3d6b
Sorted Imports in test_groupby.py
shantanu-gontia May 13, 2019
0dba40d
Updated test and edited bugfix message
shantanu-gontia May 13, 2019
bb3f6de
Merge remote-tracking branch 'upstream/master' into bug26326
shantanu-gontia May 13, 2019
dc76a2d
Merge remote-tracking branch 'upstream/master' into bug26326
shantanu-gontia May 14, 2019
648ddfa
Updated method to not check for subclasses
shantanu-gontia May 14, 2019
3aaa15c
Merge remote-tracking branch 'upstream/master' into bug26326
shantanu-gontia May 14, 2019
f8a3220
fixed under indent on line 264
shantanu-gontia May 14, 2019
ca6eff6
Updated release file
shantanu-gontia May 16, 2019
c3d5de2
Merge branch 'master' into bug26326
shantanu-gontia May 16, 2019
f8f3d8f
patched solution with modification of BaseGrouper
shantanu-gontia May 16, 2019
b8e4b34
updated whatsnew file with better wording
shantanu-gontia May 16, 2019
bfdea4c
fixed whatsnew release note message
shantanu-gontia May 16, 2019
49615db
added issue number to message
shantanu-gontia May 16, 2019
050fb89
fixed linting
shantanu-gontia May 16, 2019
bf48c41
Merge branch 'master' into bug26326
shantanu-gontia May 19, 2019
af63e6e
fixed release note msg
shantanu-gontia May 19, 2019
fe0405a
Added test message, refactor test code
shantanu-gontia May 19, 2019
ee4dffe
remove extraneous function
shantanu-gontia May 19, 2019
ea023de
update release note msg
shantanu-gontia May 19, 2019
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.25.0.rst
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Expand Up @@ -408,7 +408,7 @@ Groupby/Resample/Rolling
- Bug in :meth:`pandas.core.groupby.GroupBy.idxmax` and :meth:`pandas.core.groupby.GroupBy.idxmin` with datetime column would return incorrect dtype (:issue:`25444`, :issue:`15306`)
- Bug in :meth:`pandas.core.groupby.GroupBy.cumsum`, :meth:`pandas.core.groupby.GroupBy.cumprod`, :meth:`pandas.core.groupby.GroupBy.cummin` and :meth:`pandas.core.groupby.GroupBy.cummax` with categorical column having absent categories, would return incorrect result or segfault (:issue:`16771`)
- Bug in :meth:`pandas.core.groupby.GroupBy.nth` where NA values in the grouping would return incorrect results (:issue:`26011`)

- Bug in :meth:`pandas.core.groupby.ops.BaseGrouper.groups` in which creating a :class:`GroupBy` object with a key of type :class:`Grouper` would result in producing incorrect groups (:issue:`26326`)
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this is not user facing, can you reword a bit


Reshaping
^^^^^^^^^
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7 changes: 6 additions & 1 deletion pandas/core/groupby/ops.py
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Expand Up @@ -258,7 +258,12 @@ def groups(self):
if len(self.groupings) == 1:
return self.groupings[0].groups
else:
to_groupby = zip(*(ping.grouper for ping in self.groupings))
def is_basegrouper(self, obj):
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this is not needed

return obj.__class__.__name__ == self.__class__.__name__
to_groupby = zip(*(ping.grouper if not is_basegrouper(self,
ping.grouper)
else ping.grouper.groupings[0].grouper for ping
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Wouldn't this only work if the grouper was the first item? Would need something more generalizable

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I was wondering the same. Can Groupers be nested to more than one level?

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I think this would fail if your test was .groupby(['beta', pd.Grouper(level='alpha')]) instead of .groupby([pd.Grouper(level='alpha'), 'beta'])

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@shantanu-gontia shantanu-gontia May 13, 2019 •
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The problem is with the construction of the Groupings. The [0] indexes the sole BaseGrouper created inside the grouping due to the _get_grouper method. The order will be maintained. I have added another assertion to check this and it passed.

in self.groupings))
to_groupby = Index(to_groupby)
return self.axis.groupby(to_groupby)

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15 changes: 15 additions & 0 deletions pandas/tests/groupby/test_groupby.py
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Expand Up @@ -1736,3 +1736,18 @@ def test_groupby_multiindex_series_keys_len_equal_group_axis():
expected = pd.Series([3], index=ei)

assert_series_equal(result, expected)


def test_groupby_groups_in_BaseGrouper():
# GH 26326
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can you give a 1-line description of what this is testing

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sure. will do so in the next commit

mi = pd.MultiIndex.from_product([['A', 'B'],
['C', 'D']], names=['alpha', 'beta'])
df = pd.DataFrame({'foo': [1, 2, 1, 2], 'bar': [1, 2, 3, 4]},
index=mi)
grp1 = df.groupby([pd.Grouper(level='alpha'), 'beta'])
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can you call this

result =

and the nbggrp1 -> expected

then do then consecutively, e.g. like

result = df.groupby(....)
expected = ....

assert result.groups == expected.groups

result = df......
expected = ....

assert

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sure, looks cleaner that way.

grp2 = df.groupby(['beta', pd.Grouper(level='alpha')])
nbggrp1 = df.groupby(['alpha', 'beta'])
nbggrp2 = df.groupby(['beta', 'alpha'])

assert(grp1.groups == nbggrp1.groups)
assert(grp2.groups == nbggrp2.groups)