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BUG: subclassed .align returns normal DataFrame #13037

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BUG: subclassed .align returns normal DataFrame #13037

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34 changes: 20 additions & 14 deletions pandas/core/generic.py
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Expand Up @@ -4144,18 +4144,19 @@ def align(self, other, join='outer', axis=None, level=None, copy=True,
if isinstance(self, Series):
# this means other is a DataFrame, and we need to broadcast
# self
df = DataFrame(
dict((c, self) for c in other.columns),
**other._construct_axes_dict())
cons = self._constructor_expanddim
df = cons(dict((c, self) for c in other.columns),
**other._construct_axes_dict())
return df._align_frame(other, join=join, axis=axis,
level=level, copy=copy,
fill_value=fill_value, method=method,
limit=limit, fill_axis=fill_axis)
elif isinstance(other, Series):
# this means self is a DataFrame, and we need to broadcast
# other
df = DataFrame(dict((c, other) for c in self.columns),
**self._construct_axes_dict())
cons = other._constructor_expanddim
df = cons(dict((c, other) for c in self.columns),
**self._construct_axes_dict())
return self._align_frame(df, join=join, axis=axis, level=level,
copy=copy, fill_value=fill_value,
method=method, limit=limit,
Expand Down Expand Up @@ -4184,20 +4185,27 @@ def _align_frame(self, other, join='outer', axis=None, level=None,
ilidx, iridx = None, None
clidx, cridx = None, None

is_series = isinstance(self, ABCSeries)

if axis is None or axis == 0:
if not self.index.equals(other.index):
join_index, ilidx, iridx = self.index.join(
other.index, how=join, level=level, return_indexers=True)

if axis is None or axis == 1:
if not self.columns.equals(other.columns):
if not is_series and not self.columns.equals(other.columns):
join_columns, clidx, cridx = self.columns.join(
other.columns, how=join, level=level, return_indexers=True)

left = self._reindex_with_indexers({0: [join_index, ilidx],
1: [join_columns, clidx]},
copy=copy, fill_value=fill_value,
if is_series:
reindexers = {0: [join_index, ilidx]}
else:
reindexers = {0: [join_index, ilidx], 1: [join_columns, clidx]}

left = self._reindex_with_indexers(reindexers, copy=copy,
fill_value=fill_value,
allow_dups=True)
# other must be always DataFrame
right = other._reindex_with_indexers({0: [join_index, iridx],
1: [join_columns, cridx]},
copy=copy, fill_value=fill_value,
Expand All @@ -4212,10 +4220,8 @@ def _align_frame(self, other, join='outer', axis=None, level=None,
def _align_series(self, other, join='outer', axis=None, level=None,
copy=True, fill_value=None, method=None, limit=None,
fill_axis=0):
from pandas import DataFrame

# series/series compat
if isinstance(self, ABCSeries) and isinstance(other, ABCSeries):
# series/series compat, other must always be a Series
if isinstance(self, ABCSeries):
if axis:
raise ValueError('cannot align series to a series other than '
'axis 0')
Expand Down Expand Up @@ -4261,7 +4267,7 @@ def _align_series(self, other, join='outer', axis=None, level=None,
if copy and fdata is self._data:
fdata = fdata.copy()

left = DataFrame(fdata)
left = self._constructor(fdata)

if ridx is None:
right = other
Expand Down
21 changes: 21 additions & 0 deletions pandas/tests/frame/test_axis_select_reindex.py
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Expand Up @@ -597,6 +597,27 @@ def test_align_multiindex(self):
assert_frame_equal(expr, res1r)
assert_frame_equal(expr, res2l)

def test_align_series_combinations(self):
df = pd.DataFrame({'a': [1, 3, 5],
'b': [1, 3, 5]}, index=list('ACE'))
s = pd.Series([1, 2, 4], index=list('ABD'), name='x')

# frame + series
res1, res2 = df.align(s, axis=0)
exp1 = pd.DataFrame({'a': [1, np.nan, 3, np.nan, 5],
'b': [1, np.nan, 3, np.nan, 5]},
index=list('ABCDE'))
exp2 = pd.Series([1, 2, np.nan, 4, np.nan],
index=list('ABCDE'), name='x')

tm.assert_frame_equal(res1, exp1)
tm.assert_series_equal(res2, exp2)

# series + frame
res1, res2 = s.align(df)
tm.assert_series_equal(res1, exp2)
tm.assert_frame_equal(res2, exp1)

def test_filter(self):
# items
filtered = self.frame.filter(['A', 'B', 'E'])
Expand Down
54 changes: 54 additions & 0 deletions pandas/tests/frame/test_subclass.py
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Expand Up @@ -2,6 +2,8 @@

from __future__ import print_function

import numpy as np

from pandas import DataFrame, Series, MultiIndex, Panel
import pandas as pd
import pandas.util.testing as tm
Expand Down Expand Up @@ -156,3 +158,55 @@ def bar(self):
return self.i_dont_exist
with tm.assertRaisesRegexp(AttributeError, '.*i_dont_exist.*'):
A().bar

def test_subclass_align(self):
# GH 12983
df1 = tm.SubclassedDataFrame({'a': [1, 3, 5],
'b': [1, 3, 5]}, index=list('ACE'))
df2 = tm.SubclassedDataFrame({'c': [1, 2, 4],
'd': [1, 2, 4]}, index=list('ABD'))

res1, res2 = df1.align(df2, axis=0)
exp1 = tm.SubclassedDataFrame({'a': [1, np.nan, 3, np.nan, 5],
'b': [1, np.nan, 3, np.nan, 5]},
index=list('ABCDE'))
exp2 = tm.SubclassedDataFrame({'c': [1, 2, np.nan, 4, np.nan],
'd': [1, 2, np.nan, 4, np.nan]},
index=list('ABCDE'))
tm.assertIsInstance(res1, tm.SubclassedDataFrame)
tm.assert_frame_equal(res1, exp1)
tm.assertIsInstance(res2, tm.SubclassedDataFrame)
tm.assert_frame_equal(res2, exp2)

res1, res2 = df1.a.align(df2.c)
tm.assertIsInstance(res1, tm.SubclassedSeries)
tm.assert_series_equal(res1, exp1.a)
tm.assertIsInstance(res2, tm.SubclassedSeries)
tm.assert_series_equal(res2, exp2.c)

def test_subclass_align_combinations(self):
# GH 12983
df = tm.SubclassedDataFrame({'a': [1, 3, 5],
'b': [1, 3, 5]}, index=list('ACE'))
s = tm.SubclassedSeries([1, 2, 4], index=list('ABD'), name='x')

# frame + series
res1, res2 = df.align(s, axis=0)
exp1 = pd.DataFrame({'a': [1, np.nan, 3, np.nan, 5],
'b': [1, np.nan, 3, np.nan, 5]},
index=list('ABCDE'))
# name is lost when
exp2 = pd.Series([1, 2, np.nan, 4, np.nan],
index=list('ABCDE'), name='x')

tm.assertIsInstance(res1, tm.SubclassedDataFrame)
tm.assert_frame_equal(res1, exp1)
tm.assertIsInstance(res2, tm.SubclassedSeries)
tm.assert_series_equal(res2, exp2)

# series + frame
res1, res2 = s.align(df)
tm.assertIsInstance(res1, tm.SubclassedSeries)
tm.assert_series_equal(res1, exp2)
tm.assertIsInstance(res2, tm.SubclassedDataFrame)
tm.assert_frame_equal(res2, exp1)
2 changes: 1 addition & 1 deletion pandas/util/testing.py
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Expand Up @@ -2420,7 +2420,7 @@ def inner(*args, **kwargs):


class SubclassedSeries(Series):
_metadata = ['testattr']
_metadata = ['testattr', 'name']

@property
def _constructor(self):
Expand Down